Intrinsic Disorder in Tetratricopeptide Repeat Proteins

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International Journal of Molecular Sciences

Article Intrinsic Disorder in Tetratricopeptide Repeat Proteins

1, 1, 1, 2 Nathan W. Van Bibber †, Cornelia Haerle †, Roy Khalife †, Bin Xue and Vladimir N. Uversky 1,3,4,* 1 Department of Molecular Medicine Morsani College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd., Tampa, FL 33612, USA; [email protected] (N.W.V.B.); [email protected] (C.H.); [email protected] (R.K.) 2 Department of Cell Biology, Microbiology and Molecular Biology, School of Natural Sciences and Mathematics, College of Arts and Sciences, University of South Florida, Tampa, FL 33620, USA; [email protected] 3 USF Health Byrd Alzheimer’s Research Institute, Morsani College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd., Tampa, FL 33612, USA 4 Institute for Biological Instrumentation, Russian Academy of Sciences, Federal Research Center “Pushchino Scientiﬁc Center for Biological Research of the Russian Academy of Sciences”, 4 Institutskaya St., Pushchino, 142290 Moscow Region, Russia * Correspondence: [email protected]; Tel.: +1-813-974-5816; Fax: +1-813-974-7357 These authors contributed equally to this work. † Received: 21 April 2020; Accepted: 22 May 2020; Published: 25 May 2020

Abstract: Among the realm of repeat containing proteins that commonly serve as “scaffolds” promoting protein-protein interactions, there is a family of proteins containing between 2 and 20 tetratricopeptide repeats (TPRs), which are functional motifs consisting of 34 amino acids. The most distinguishing feature of TPR domains is their ability to stack continuously one upon the other, with these stacked repeats being able to affect interaction with binding partners either sequentially or in combination. It is known that many repeat-containing proteins are characterized by high levels of intrinsic disorder, and that many protein tandem repeats can be intrinsically disordered. Furthermore, it seems that TPR-containing proteins share many characteristics with hybrid proteins containing ordered domains and intrinsically disordered protein regions. However, there has not been a systematic analysis of the intrinsic disorder status of TPR proteins. To fill this gap, we analyzed 166 human TPR proteins to determine the degree to which proteins containing TPR motifs are affected by intrinsic disorder. Our analysis revealed that these proteins are characterized by different levels of intrinsic disorder and contain functional disordered regions that are utilized for protein-protein interactions and often serve as targets of various posttranslational modifications.

Keywords: tetratricopeptide repeat; intrinsically disordered protein; intrinsically disordered protein region; protein-protein interaction; posttranslational modiﬁcation

1. Introduction The predominant “lock-and-key” model of protein functionality, according to which the biological function of a protein is determined by its highly ordered structure defined by its unique amino acid sequence [1], has obscured the fact that proteins without unique structure might also have biological functions. Intrinsic disorder (ID) in proteins, a phenomenon that describes the lack of a stable, ordered secondary and/or tertiary structure in functional proteins, had been largely ignored for decades after its first appearance in a scientific publication in 1936 [2]. This ignorance of the importance of ID resulted, in part, from the use of numerous unrelated terms associated with the same phenomenon and has

Int. J. Mol. Sci. 2020, 21, 3709; doi:10.3390/ijms21103709 www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2020, 21, 3709 2 of 35 been a contributing factor in keeping ID in obscurity for so long. As a result of the lack of consistent nomenclature, whenever an ID protein (IDP) or protein region (IDPR) was described, it was taken as a new discovery and looked upon as an odd exception to the classic protein structure-function paradigm, but was not identified as evidence towards the phenomenon of ID. The emergence of informatics in general, with its ability to make information and its analysis more readily available, and bioinformatics in particular, by providing sophisticated databases and tools for protein analyses, led to a breakthrough in ID biology. Since the beginning of the 21st century, the number of publications about IDPs and IDPRs has skyrocketed, led primarily by publications from four research groups [3–6]. Over the last couple of decades IDPs and hybrid proteins containing ordered domains and IDPRs have been recognized as “one of the main types of proteins” [7], constituting a very sizable and functionally significant class of proteins [5,8–13]. Disorder content in proteomes increases as organism complexity increases [8–10,12,14], indicating that IDPs are heavily involved in, and often a crucial factor for, a multitude of biological processes [3,5,6,15–19], and the interaction between IDPRs and structured domains can increase functional versatility [20]. Furthermore, IDPs/IDPRs are characterized by a very complex and heterogeneous spatiotemporal structural organization, possessing regions that are ordered or disordered to different degree. Examples include foldons (independent foldable units of a protein), inducible foldons (disordered regions that can fold at least in part due to the interaction with binding partners), non-foldons (non-foldable protein regions), semi-foldons (regions that are always in a semi-folded form), and unfoldons (ordered regions that have to undergo an order-to-disorder transition to become functional) [21–24]. Astonishingly, given its only very recent acceptance into the scientific world, the natural abundance of disorder in the proteome has been shown to be at approximately 60%, meaning approximately 60% of proteins in eukaryotes display at least some degree of disorder [5,8–13,25–40]. The lack of a stable or ordered tertiary structure in IDPs/IDPRs enables their structural plasticity and binding promiscuity which make intrinsic disorder a major factor in protein-protein-interactions [5,11,21,23,41,42], a process that is essential for various biological functions. Furthermore, complex and highly heterogeneous structural ‘anatomy’ of IDPs/IDPRs contributes to their specific molecular ‘physiology’, where differently (dis)ordered structural elements possess well-defined specific functions [43], thereby allowing a protein molecule to be multifunctional (i.e., involved in interaction with, regulation of, and controlled by multiple structurally unrelated partners) [44]. Nevertheless, these same features that are functionally advantageous in tightly regulated disordered proteins can become detrimental, when ID in proteins runs amok. Referred to as D2 phenomenon [45,46], disorder in intrinsically disordered proteins is strongly associated with a number of diseases, the most devastating diseases of our time, as the majority of human cancer-associated proteins [47], as well as many proteins associated with amyloidoses [48], cardiovascular disease [49], diabetes [50], and neurodegeneration [51,52] are either completely disordered or contain long IDPRs. An important feature of IDPs/IDPRs is the frequent presence of the tandem repeats in their amino acid sequences. Tandem repeats correspond to a specific bias in the amino acid sequence, where a pattern of one or more amino acid is repeated, and these repetitions are either directly adjacent to each other or are located in a very close proximity. Nature often uses tandem repeats in “scaffolding proteins” to promote protein-protein interactions and regulation of many key signaling pathways; i.e., biological functions central for all living cells. In fact, scaffolding proteins are modular proteins capable of interaction with multiple members of a signaling pathway, tethering them into complexes, and often modulating and regulating the function of these associated proteins. In this way, scaffold proteins are responsible for the assembly and regulation of multimolecular signaling complexes. Therefore, it is not surprising that there are several families of protein repeats including: Armadillo repeats [53], Ankyrin repeats [54], HEAT repeats [55], leucine-rich repeats [56], Kelch-like repeats [57], WD40 (also known as WD or β-transducin) repeats [58], Pentatricopeptide repeats [59], and Tetratricopeptide Repeats (TPR). It was shown that many repeat-containing proteins are characterized by high levels of intrinsic disorder, and that many protein tandem repeats can be intrinsically disordered [60–65]. Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 3 of 35

Int. J. Mol. Sci. 2020 21 characterized by, high, 3709 levels of intrinsic disorder, and that many protein tandem repeats can3 of be 35 intrinsically disordered [60–65]. TPRTPR proteinsproteins containcontain betweenbetween twotwo andand 20 repeats of the TPR motif consisting of 34 amino acids. DespiteDespite thethe lacklack ofof fullyfully invariantinvariant residuesresidues inin suchsuch domains,domains, theythey areare characterizedcharacterized byby aa degeneratedegenerate consensusconsensus sequencesequence containing containing a a pattern pattern of of small small and and large large hydrophobic hydrophobic amino amino acids acids [66 [66]], which, which can can be identifiedbe identified by most by general most general sequence sequence analysis analysis programs programs [67], as well [67] as, by as a well specialized as by computational a specialized tool,computational TPRpred [tool,68,69 TPRpred]. What distinguishes [68,69]. What thedistinguishes TPR domain the most TPR fromdomain other most classes from ofother repeats classes is its of abilityrepeats to isstack its ability repeats to stack continuously repeats continuously one upon the one other upon (where the other the helices (where within the helices each repeatwithinstack each togetherrepeat stack with together helices inwith adjacent helices TPRs in adjacent to form TPRs a right-handed to form a right superhelix-handed [70 superhelix]), with these [70] repeats), with these then arepeatffectings then interaction affecting with interaction their binding with partnerstheir binding either partners sequentially either or sequentially in combination, or in makingcombination, TPRs “muchmaking better TPRs suited“much to better be bi-functional suited to be andbi-functional multi-functional and multi molecules,-functional where molecules, complex where interactions complex betweeninteractions molecules between are moleculesprogrammed are in programmed line” [71]. These in line” distinct [71] properties. These distinct of TPR containing properties proteins of TPR makecontaining them proteins a promising make field them of researcha promising particularly field of research in medical, particularly pharmaceutical in medical, and biotechnological pharmaceutical applications.and biotechnological In addition applications. to their inherent In addition binding to plasticity their inherent and functional binding plasticity diversity, and the basicfunctional TPR scadiversity,ffold can the be basic redesigned TPR scaffold to modulate can be bindingredesigned specificity to modulate and/or binding affinity specificity toward desired and/or peptideaffinity ligandstoward [66 desired] and TPR peptide containing ligands proteins [66] and can TPR be inhibited containing by designed proteins ligandscan be [inhibited67]. This designability by designed isligands illustrated [67].by This Figure designability1, where crystal is illustrated structures by of Figure proteins 1, containing where crystal two, three, structures and 20 of copies proteins of thecontaining consensus two, TPR three, motifs and are 20 shown.copies of the consensus TPR motifs are shown.

FigureFigure 1.1. StructuralStructural characterizationcharacterization of of TPR-containing TPR-containing proteins proteins showing showing the the ability ability of of TPR TPR domains domains to beto be stacked stacked continuously continuously one one upon upon the the other. other. Shown Shown here here are are crystal crystal structures structuresof of artiﬁcialartificial proteinsproteins speciallyspecially designed to contain contain two two (PDB (PDB ID: ID: 1NA3, 1NA3, [72] [72])) (A),), threethree (PDB (PDB ID: ID: 1NA3, 1NA3, [72 [72]]) (B) ),(B or), 20or copies20 copies of the of consensusthe consensus TPR motif TPR (motifC and (DC) (PDBand D ID:) (PDB 2AVP, ID: [73 ]),2AVP, i.e., CTPR2, [73]), i.e., CTPR3, CTPR2, and CTPR20,CTPR3, respectively.and CTPR20, To emphasize respectively. the ability To emphasi of TPR proteinsze the ability to form speciﬁcof TPR superhelical proteins to structure, form specific plots C andsuperhelicalD show two structure, projections plots (side C and view D show and top two view, projections respectively) (side view of CTPR20. and top view, respectively) of CTPR20. TPR domains are present in a number of proteins, where they serve as versatile interaction modules and mediators of the formation of multiprotein complexes [67]. TPR proteins are found in all eukaryotic TPR domains are present in a number of proteins, where they serve as versatile interaction and prokaryotic organisms, where they provide important functions in regulating diverse biological modules and mediators of the formation of multiprotein complexes [67]. TPR proteins are found in processes (e.g., biomineralization, protein import, vesicle fusion, organelle targeting, and pathogenesis all eukaryotic and prokaryotic organisms, where they provide important functions in regulating of bacteria) [67]. Although TPR proteins are traditionally associated with binding of short linear peptide diverse biological processes (e.g., biomineralization, protein import, vesicle fusion, organelle motifs, in fact, they utilize a wide range of molecular recognition modes, being able to interact with targeting, and pathogenesis of bacteria) [67]. Although TPR proteins are traditionally associated with short linear peptides and large globular domains [71]. As a result, they are involved in a wide spectrum binding of short linear peptide motifs, in fact, they utilize a wide range of molecular recognition of cellular processes. For example, by mediating protein-protein interactions and forming multiprotein modes, being able to interact with short linear peptides and large globular domains [71]. As a result, complexes with cellular and viral proteins through their multiple TPR motifs, interferon-induced they are involved in a wide spectrum of cellular processes. For example, by mediating protein-protein protein with tetratricopeptide repeats (IFIT) play a number of important roles in host innate immunity, interactions and forming multiprotein complexes with cellular and viral proteins through their antiviral immune response, virus-induced translation initiation, replication, double-stranded RNA

Int. J. Mol. Sci. 2020, 21, 3709 4 of 35 signaling, and recognition of pathogen-associated molecular patterns (PAMPs) [74,75]. Although typically TPR proteins do not have enzymatic activities, ubiquitously transcribed X-chromosome tetratricopeptide repeat protein (UTX) is known to serve as H3K27 demethylase catalyzing the demethylation of di- and tri-methylated histone H3 lysine 27 (H3K27) [76], thereby being linked to homeotic gene expression, embryonic development, and cellular reprogramming [77], whereas a co-chaperone CHIP (the C terminal Hsp70 binding protein), in addition to using its TPR domains to interact with Hsp70 and Hsp90 chaperones, serves as an E3 ubiquitin ligase utilizing a modified RING finger domain (U-box) [78]. Some TPR proteins might act as chaperones (e.g., the members of the UCS (UNC-45/CRO1/She4p) family of proteins are specific chaperones for the folding, assembly, and function of myosin [79]). Among various biological functions ascribed to the TPR proteins are: control of proteins responsible for organization and homeostasis of the endoplasmic reticulum [80]; regulation of the biosynthesis of the photosynthetic apparatus via involvement in almost all of the steps crucial for biogenesis of the thylakoid membranes [81]; assistance in the de novo assembly and stability of a multi-component pigment-protein complex, photosystem II (PSII) [82]; the quality control of secretory and membrane proteins mislocalized to the cytosol [83]; control of limb regeneration in crickets [84] and plastid protein import [85]. Also, in biotechnology, because of their binding versatility and designability, TPR repeats are used for the creation of repeat protein scaffolds serving as a basis of the biomolecular templating of functional hybrid nanostructures [86,87]. The particular structure of the TPR motif, a helix-turn-helix conformation, linked to the next repeat by a short loop [71] forming an overall super-helix structure [67], has been characterized as an “exceptionally versatile fold capable of mediating protein-protein interactions via varied mechanisms” [71]. For example, a short peptide may bind to the TPR concave groove and an extended peptide may bind to the TPR concave groove. The TPR motif is capable of binding interacting partners of various secondary structures, and TPR proteins are known to be co-chaperones, binding to chaperones and assisting them in their task of helping proteins to fold. TPR-containing proteins share many characteristics with hybrid proteins containing ordered domains and IDPRs. Like other IDPR-containing proteins TPR-containing proteins are naturally abundant (using bioinformatics tools, more than 5000 TPR-containing proteins were found in different organisms [67]) and are involved in many biological functions, including protein-protein interactions. Furthermore, similar to other IDPs/IDPRs, mutations in TPR-containing proteins have been associated with a variety of human diseases, such as chronic granulomatous disease or Leber’s congenital amaurosis [66,67]. Therefore, in this paper we analyzed the degree to which proteins containing TPR motifs are affected by intrinsic disorder. Data on the prevalence of intrinsic disorder in human TPR proteins may suggest yet another possible route for the sophisticated pathogenicity attributed to these proteins.

2. Results and Discussion

2.1. Per-Residue Intrinsic Disorder Predisposition of Human TPR Proteins In this study, we analyzed 166 human proteins containing TPR domains. The amino acid sequence of these proteins ranged in length from 151 to 4471 residues. Figure2A presents the length distribution of 166 human TPR proteins and shows that most abundant are proteins are between 500–700 residues in length. Figure2B shows that human TPR proteins contain from one to 28 TPR repeats, with majority proteins possessing three repeats. Peculiarities of the distribution of TPR repeats within the amino acid sequences of TPR proteins are illustrated by Figure2C, which indicates although TPR repeats can be found in diﬀerent parts of proteins, they are less likely to be C-terminal. Int. J. Mol. Sci. 2020, 21, 3709 5 of 35 Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 5 of 35

FigureFigure 2. 2.Some Some characteristics characteristics of 166 of human166 human TPR proteins TPR proteins analyzed analyzed in this study. in this (A study.) Length (A) distribution Length ofdistribution studied proteins. of studied (B) proteins. Quantiﬁcation (B) Quantification of the number of the of TPRnumber repeats of TPR in therepeats individual in the individual proteins. (C) Quantiﬁcationproteins. (C) ofQuantification the peculiarities of the of TPR peculiarities repeat distribution of TPR repeat within distribution the amino within acid sequences the amino of acid human TPRsequences proteins: of N, human M, C, TPR N-M, proteins: M-C, N-C, N, M, and C, N-M-C N-M, correspondM-C, N-C, and to the N- preferentialM-C correspond potion to of the TPR repeatspreferential within potion N-terminal of TPR (N),repeats middle within (M), N- orterminal C-terminal (N), middle (C) parts (M), of or the C- sequenceterminal (C) and parts their of various the combinations.sequence and (theirD) Correlation various combinations. between the (D number) Correlation of TPR between repeat the in querynumber proteins of TPR andrepeat their in query intrinsic disorderproteins status. and their intrinsic disorder status.

MoreMore than than half half of of humanhuman TPRTPR proteins (85) (85) contain contain only only TPR TPR repeats repeats and and do do not not include include other other functionalfunctional domains. domains. However,However, manymany TPR proteins, proteins, in in addition addition to to TPR TPR repeats, repeats, include include othe otherr protein protein interactioninteraction modules, modules, suchsuch asas coiled-coilcoiled-coil regions regions (11 (11 proteins), proteins), ankyrin ankyrin repeats repeats (seven (seven proteins), proteins), WD WD repeatsrepeats (four (four proteins), proteins), HEATHEAT repeatsrepeats (two(two proteins), armadillo armadillo repeats repeats (one (one protein), protein), SH3 SH3 domains domains (four proteins), zinc finger motifs of different type (eight proteins), as well as the bipartite CS (four proteins), zinc finger motifs of different type (eight proteins), as well as the bipartite CS domains, domains, which are ~100-residue protein-protein interaction modules named after CHORD- which are ~100-residue protein-protein interaction modules named after CHORD-containing proteins containing proteins and SGT1 (two proteins), a heat shock chaperonin-binding motif STI1 (three and SGT1 (two proteins), a heat shock chaperonin-binding motif STI1 (three proteins), RanBD domains proteins), RanBD domains that interact with and stabilize the GTP-bound form of Ran (the Ras-like that interact with and stabilize the GTP-bound form of Ran (the Ras-like nuclear small GTPase) (seven nuclear small GTPase) (seven proteins), and GoLoco or G-protein regulatory (GPR) motif found in proteins),various G and-protein GoLoco regulators or G-protein (two proteins). regulatory There (GPR) are also motif some found catalytic in variousdomains G-protein in several of regulators these (twoproteins, proteins). such Thereas PPIase are FKBPalso some-type catalytic domain ( domainssix proteins), in several SAM-dependent of these proteins, MTase PRMT such- astype PPIase 1 FKBP-typedomain, helicase domain domain, (six proteins), serine/threonine SAM-dependent-protein phosphatase MTase PRMT-type domain, PI3K/PI4K 1 domain, kinase helicase domain, domain, serineand /thethreonine-protein Fe2OG dioxygenase phosphatase domain, domain,suggesting PI3K that/PI4K some kinase enzyme domain, utilize andTPR themotifs Fe2OG for interaction dioxygenase domain,with their suggesting partners.Disorder that some predisposition enzyme utilize of TPR human motifs TPR for proteins interaction was with evaluated their partners.Disorder using a set of predispositiondisorder predictors of human from the TPR PONDR proteins family. was The evaluated use multiple using computational a set of disorder tools predictors for prediction from of the PONDRintrinsic family. disorde Ther in use proteins multiple is an computational accepted practice tools in for the prediction field. Since of different intrinsic computational disorder in proteins tools is anuse accepted different practice attributes in the(such field. as amino Since acid different composition, computational hydropathy, tools sequence use different complexity, attributes etc.) (such and as aminomodels acid for composition, to calculate hydropathy, a disorder predisposition sequence complexity, score for etc.) every and a modelsmino acid for toresidue calculate in a a query disorder predispositionprotein, it is a scorecommon for everysituation, amino when acid different residue tools in a will query generate protein, rather it is different a common outputs. situation, when different tools will generate rather different outputs.

Int. J. Mol. Sci. 2020, 21, 3709 6 of 35

There is no an accepted consensus of which disorder predictor is the best in evaluating disorder predisposition of a query protein. In reality, since different computational tools are sensitive to different disorder-related aspects of the amino acid sequence, all of them contain some useful information. The per-residue disorder predisposition scores are on a scale from 0 to 1, where values of 0 indicate fully ordered residues, and values of 1 indicate fully disordered residues. Values above the threshold of 0.5 are considered disordered residues, whereas residues with disorder scores between 0.25 and 0.5 are considered flexible residues. For each protein, per-residue disorder predisposition values are summarized to produce global disorder predictions for the protein. The predicted average disorder score is defined by taking the arithmetic mean over all the residues to give the overall mean disorder score on the same 0 to 1 scale. The predicted percent disorder for each protein is defined as the ratio of the number of disordered residues (i.e., residues with the predicted disorder scores greater than 0.5) to the total number of residues and is given as a percentage. Based on their levels of average intrinsic disorder score, proteins were classified as highly ordered (average disorder score < 0.25), moderately disordered (average disorder score between 0.25 and 0.5) and highly disordered (average disorder score 0.5). Similarly, proteins can be classified based on their percent of predicted disordered residues ≥ (PPDR). Here, two arbitrary cutoffs for the levels of intrinsic disorder are used to classify proteins as highly ordered (PPDR < 10%), moderately disordered (10% PPDR < 30%) and highly disordered ≤ (PPDR 30%) [88]. The frequency distribution for the PPDR score for all three predictors are shown in ≥ Figure3 and corresponding data are outlined below. Our analysis revealed that for disorder predictions generated by PONDR® VLXT for 166 human TPR proteins, the average predicted disorder score ranged from 0.11 to 0.67 with a mean of 0.34. The overall percent of disorder ranged from 3.1% to 73.2% with a mean of 30.2% (Figure3A). The longest disordered region in query proteins ranged from 10 residues to 348 residues with a mean of 61 residues (Table1).

Table 1. Distribution of the number of disordered regions (# DR) and longest disordered region (Longest DR) for the PONDR® VLXT and PONDR® VSL2 predictors.

PONDR® VLXT PONDR® VSL2 # DR Longest DR # DR Longest DR Min 3 10 3 11 Average 14.5 61.2 14.0 128.5 Max 61 348 68 818

According to the PONDR® VSL2-based analysis, the average prediction score for 166 human TPR proteins ranged from 0.25 to 0.79 with a mean of 0.45. The overall percent disorder score ranged from 11.9% to 90.4% with a mean of 37.9% (Figure3B). The longest disordered region ranged from 11 residues to 818 residues with a mean of 129 residues (Table1). PONDR ® FIT is a meta-predictor that incorporates predictions from several diﬀerent sources [89]. For PONDR® FIT, the average prediction score ranged from 0.16 to 0.68 with a mean of 0.31. The overall percent disorder score ranged from 1.9% to 74.9% with a mean of 22.3% (Figure3C). Curiously, Figure2D shows that there is no obvious correlation between the number of TPR motifs in human TPR proteins and their extent of disorder. Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 6 of 35 Int. J. Mol. Sci. 2020, 21, 3709 7 of 35

50 40 30 20 Frequency 10 0

VLXT % Disorder Score

1.8% 0.6% 0.0% 3.6% 6.6% <=10 (10-20] (20-30] 12.0% 21.7% (30-40] (40-50] 26.5% 27.1% (50-60] (60-70] (70-80]

(A)

40 30 20

Frequency 10 0

VSL2 % Disorder Score

1.2% 0.6% <=10 2.4% 0.0% 4.8% (10-20]

17.5% (20-30] (30-40] 20.5% (40-50] 22.3% (50-60] 15.7% (60-70] 15.1% (70-80] (80-90]

(B)

Figure 3. Cont.

Int. J. Mol. Sci. 2020, 21, 3709 8 of 35 Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 7 of 35

60 50 40 30 20 Frequency 10 0

PONDR-FIT % Disorder Score

2.4% 0.6% 2.4% 0.0% <=10 (10-20] 9.0% (20-30] 28.9% 15.1% (30-40] (40-50] 16.9% (50-60] 24.7% (60-70] (70-80]

(C)

FigureFigure 3.3. Frequency distributions distributions of of the the percent percent of ofpredicted predicted disorder disorder in 166 in166 human human TPR TPR proteins proteins as asevaluated evaluated by by PONDR PONDR® VLXT® VLXT (A (),A ), PONDR PONDR® VSL2® VSL2 (B), (B ), and and PONDR PONDR® ®FITFIT (C ().C ).(A (A) )Frequency Frequency distributiondistribution ofof predictedpredicted percent of disorder evaluated by PONDR PONDR®® VLXT;VLXT; (B (B) Frequency) Frequency distribution distribution ofof predictedpredicted percentpercent ofof disorder evaluated by PONDR ® VSL2;VSL2; (C (C) )Frequency Frequency distribution distribution of of predicted predicted percentpercent ofof disorderdisorder evaluatedevaluated by PONDR® FIT.FIT.

AsThere it was is no already an accepted emphasized, consensus based of onwhich their disorder content ofpredictor disordered is the residues, best in evaluating proteins are disorder typically groupedpredisposition into three of a categories: query protein. highly In reality, ordered since (0%–10%), different moderately computational disordered tools are (10%–30%), sensitive and to highlydifferent disordered disorder- (greaterrelated aspects than 30%). of the A breakdown amino acid of sequence, these categories all of them based contain on the someoutputs useful of all threeinformation. disorder predictors utilized in this study can be seen in Figure4. This analysis clearly shows that the majorityThe per of-residue human disorder TPR proteins predisposition are either scores moderately are on or a highly scale from disordered. 0 to 1, where values of 0 indicateSince fully the ordered average disorderresidues, scoreand values (ADS) of of 1 a indicate given protein fully disordered is not directly residues. related Values to its PPDR above value the (e.g.,threshold theoretically, of 0.5 are a considered protein with disordered the PPDR residues, of 100% whereas might residues have the with ADS disorder ranging scores from between 0.5 to 1.0; whereas0.25 and a0.5 protein are considered with the PPDRflexible of residues. 0% might For have each any protein, ADS < per0.5),-residue Figure 5disorder represents predisposition the ADS vs. PPDRvalues plotsare summarized generated forto produce human TPRglobal proteins disorder based predictions on the for results the protein. of their The analysis predicted by PONDRaverage ® VLXT,disorder PONDR score is® definedVSL2, and by taking PONDR the® arithmeticFIT. This ﬁguremean over provides all the further residues support to give to the the overall idea that mean the majoritydisorder ofscore TPR on proteins the same are 0 either to 1 scale moderately. The predicted or highly percent disordered. disorder This for analysis each protein allowed is defined us to select as thethe most ratio disordered of the number proteins of disordered in the set, residues which were (i.e., deﬁned residues here with as the proteins predicted possessing disorder ADS scores0.5 ≥ andgreater/or PPDR than 0.5)30% to the by total any ofnumber the PONDR of residues® VLXT, and PONDRis given ®asVSL2, a percentage. and PONDR Based® onFIT their predictors levels of or ≥ anyaverage their intrinsic combination. disorder We score, found proteins that 59 (35.5%)were classified of TPR as proteins highly satisfyordered these (average criteria. disorder score < 0.25), moderately disordered (average disorder score between 0.25 and 0.5) and highly disordered (average disorder score ≥ 0.5). Similarly, proteins can be classified based on their percent of predicted disordered residues (PPDR). Here, two arbitrary cutoffs for the levels of intrinsic disorder are used to classify proteins as highly ordered (PPDR < 10%), moderately disordered (10% ≤ PPDR < 30%) and highly disordered (PPDR ≥ 30%) [88]. The frequency distribution for the PPDR score for all three predictors are shown in Figure 3 and corresponding data are outlined below. Our analysis revealed that for disorder predictions generated by PONDR® VLXT for 166 human TPR proteins, the average predicted disorder score ranged from 0.11 to 0.67 with a mean of 0.34. The overall percent of disorder ranged from 3.1% to 73.2% with a mean of 30.2% (Figure 3A). The longest

Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 8 of 35

disordered region in query proteins ranged from 10 residues to 348 residues with a mean of 61 residues (Table 1). According to the PONDR® VSL2-based analysis, the average prediction score for 166 human TPR proteins ranged from 0.25 to 0.79 with a mean of 0.45. The overall percent disorder score ranged from 11.9% to 90.4% with a mean of 37.9% (Figure 3B). The longest disordered region ranged from 11 residues to 818 residues with a mean of 129 residues (Table 1). PONDR® FIT is a meta-predictor that incorporates predictions from several different sources [89]. For PONDR® FIT, the average prediction score ranged from 0.16 to 0.68 with a mean of 0.31. The overall percent disorder score ranged from 1.9% to 74.9% with a mean of 22.3% (Figure 3C).

Table 1. Distribution of the number of disordered regions (# DR) and longest disordered region (Longest DR) for the PONDR® VLXT and PONDR® VSL2 predictors.

PONDR® VLXT PONDR® VSL2 # DR Longest DR # DR Longest DR Min 3 10 3 11 Average 14.5 61.2 14.0 128.5 Max 61 348 68 818 Int. J. Mol. Sci. 2020, 21, 3709 9 of 35 Curiously, Figure 2D shows that there is no obvious correlation between the number of TPR motifs in human TPR proteins and their extent of disorder.

120

100

Frequency 40

Int. J. Mol. Sci. 2020, 21, x FOR0 PEER REVIEW 9 of 35 0-10 Ordered 10-30 Moderately Disordered >30 Highly Disordered As it was alreadyVLXT emphasized, % Disorder Score basedVSL2 % on Disorder their Score contentPONDR-FIT of disordered % Disorder Score residues, proteins are typically grouped into three categories: highly ordered (0%–10%), moderately disordered (10%–30%), ® ® and highly disorderedPONDR® VLXT (greater % Disorder than 30%). A breakdownPONDR VSL2 of %these categories basedPONDR on FITthe % outputs of Disorder Disorder all three disorder predictors utilized in this study can be seen in Figure 4. This analysis clearly shows 0-10 Ordered 3.6% that the majority of human TPR proteins are either moderately0.0% or highly disordered. 39.8% Since the average disorder score (ADS) of a given protein is not directly29.5% related to its PPDR28.9% value (e.g., 10-30theoretically, a protein with the PPDR of 100% might have the ADS ranging from 0.5 to 1.0; Moderately whereasDisordered a protein with the PPDR of 0% might have any ADS < 0.5), Figure 5 represents the ADS vs. PPDR>30 plots Highly generated for human TPR proteins based on the results of their analysis by PONDR® 47.6% Disordered ® 48.8% ® VLXT, PONDR VSL2, and PONDR FIT. This60.2% figure provides further support to the idea that the majority of TPR proteins are either moderately or highly disordered. This analysis allowed41.6% us to select the most disordered proteins in the set, which were defined here as proteins® possessing ADS® ≥ 0.5 Figure 4. DistributionFigure 4. Distribution of proteins of proteins based based on percent on percent disorder disorder scorescore from from PONDR PONDR® VLXT,VLXT, PONDR PONDR® ® ® ® and/or PPDR ≥ 30% by any of® the PONDR VLXT, PONDR VSL2, and PONDR FIT predictors or VSL2, and PONDRVSL2, and® PONDRFIT. The FIT. category The category 0%–10% 0%–10% are are considered considered highly highly ordered ordered proteins, proteins, 10%–30% 10%–30% are are any thmoderatelyeir combination. disordered,moderately We disordered, and found greater and that greater than 59 (35.5%) 30%than 30% are are highlyof highlyTPR disordered. disorderedproteins. satisfy these criteria.

Figure 5. Plots correlating the average disorder scores and PPDRs for human TPR proteins based on Figure 5. Plots correlating the average disorder scores and PPDRs for human TPR proteins based on the results of PONDR® VLXT, PONDR® VSL2, and PONDR® FIT analyses. Dashed lines represent the results of PONDR® VLXT, PONDR® VSL2, and PONDR® FIT analyses. Dashed lines represent boundaries separating ordered (ADS < 0.25, PPDR < 10%), moderately disordered (0.25 ADS < 0.5, boundaries separating ordered (ADS < 0.25, PPDR < 10%), moderately disordered (0.25 ≤≤ ADS < 0.5, 10% PPDR < 30%), and highly disordered proteins (ADS 0.5, PPDR 30%). 10% ≤≤ PPDR < 30%), and highly disordered proteins (ADS ≥ 0.5, PPDR ≥≥ 30%). Agreement between the outputs of diﬀerent intrinsic disorder predictors for a set of query proteins can beAgreement assessed in between the form the of a outputs 3D scatter of differentplot, where intrinsic the average disorder disorder predictors scores for (or aaverage set of PPDRquery values)proteins generated can be assessed by disorder in the predictors form of are a 3D plotted scatter against plot, each where other the for average all the disorder proteins (Figure scores 6 (or). average PPDR values) generated by disorder predictors are plotted against each other for all the proteins (Figure 6). Since some of the human TPR proteins are associated with various diseases, to see if such disease-associated TPR proteins have stronger tendency for intrinsic disorder than proteins whose disease associations are unknown, we included information from UniProt on query protein associated disease or mutagenesis (Figure 6). These analyses clearly demonstrated that there is a rather good agreement between the outputs of PONDR® VLXT, PONDR® VSL2, and PONDR® FIT for 166 human TPR proteins. This conclusion follows from the fact that the majority of points corresponding to human TPR proteins are located either on or in the close proximity to the diagonal in the corresponding 3D plots. Furthermore, proteins associated with disease or mutagenesis did not demonstrate exceptionally high levels of intrinsic disorder.

Int. J. Mol. Sci. 2020, 21, 3709 10 of 35

Since some of the human TPR proteins are associated with various diseases, to see if such disease-associated TPR proteins have stronger tendency for intrinsic disorder than proteins whose disease associations are unknown, we included information from UniProt on query protein associated disease or mutagenesis (Figure6). These analyses clearly demonstrated that there is a rather good agreement between the outputs of PONDR® VLXT, PONDR® VSL2, and PONDR® FIT for 166 human TPR proteins. This conclusion follows from the fact that the majority of points corresponding to human TPR proteins are located either on or in the close proximity to the diagonal in the corresponding 3D plots. Furthermore, proteins associated with disease or mutagenesis did not demonstrate exceptionally Int.high J. Mol. levels Sci. 20 of20 intrinsic, 21, x FOR disorder. PEER REVIEW 10 of 35

Figure 6. Three-dimensional scatterplots comparing the average disorder scores and average PPDR Figure 6. Three-dimensional scatterplots comparing the average disorder scores and average PPDR values generated by three different predictors. On the left panel: average disorder scores generated by valuesPONDR generated® VLXT, by PONDR three different® VSL2, andpredictors. PONDR On® FITthe alongleft panel: the x,average y, and zdisorder axes, respectively. scores generated On the ® ® ® byright PONDR panel: VLXT, PPDR PONDR evaluated VSL2, by PONDR and PONDR® VLXT, FIT PONDR along® theVSL2, x, y, and PONDRz axes, respectively® FIT along. On the the x, y, ® ® ® rightand zpanel: axes, respectively.PPDR evaluated Proteins by PONDR shown in redVLXT, had PONDR no associated VSL2, disease and PONDR or mutagenesis FIT along information the x, y, in andUniProt, z axes, while respectively. those shown Proteins in green shown had in both red had associated no associated disease disease and mutagenesis or mutagenesis information. information Those inin UniProt, blue had while only associatedthose shown disease in green information, had both andassociated those and disease those and in yellowmutagenesis had only information. associated Thosemutagenesis in blue information. had only associated disease information, and those and those in yellow had only associated mutagenesis information. 2.2. Binary Classification of the Intrinsic Disorder Status of Human TPR Proteins 2.2. Binary Classification of the Intrinsic Disorder Status of Human TPR Proteins Important information pertaining to the global classification of disorder status of query proteins canImportant be obtained information from the analysis pertaining of binary to the disorderglobal classification predictors (i.e., of disorder computational status of tools query that proteins classify canproteins be obtained as wholly from ordered the analy orsis wholly of binary disordered). disorder predictors The usefulness (i.e., computational of this approach tools is basedthat classify on the proteinsprinciple as di whollyfferences ordered in the criteriaor wholly used disordered). by different The binary usefulness predictors, of this such approach as the charge-hydropathy is based on the principle(CH) plot differences [4,14] and in the the cumulative criteria used distribution by different function binary (CDF) predictors, plot [14 ,90 such]. CH-plot as the charge utilizes- hydropathyinformation (CH) on absolute plot [4,14] mean and net the charge cumulative of a query distribution protein and function its mean (CDF) hydropathy plot [14,90] as the. CH only-plot two utilizesparameters information for classifying on absolute query mean proteins net charge as proteins of a query with substantial protein and amounts its mean of hydropathy extended disorder as the only two parameters for classifying query proteins as proteins with substantial amounts of extended disorder (native coils and native pre-molten globules) or proteins with compact globular conformations (native molten globules and ordered proteins) [14,91]. On the other hand, CDF analysis uses the PONDR outputs to discriminate all types of disorder (native coils, native molten globules and native pre-molten globules) from ordered proteins [14]. Therefore, the combined CH- CDF plot gives an opportunity for unique assessment of intrinsic disorder in several categories, allowing predictive classification of proteins into structurally different classes [90,92,93]. To generate a corresponding CH-CDF plot, the coordinates of a query protein are calculated as a distance from the boundary in the CH-plot (Y-coordinate) and an average distance of the respective CDF curve from the CDF boundary (X-coordinate). In the CH-CDF plot, the x-axis separates proteins predicted by CH-plot to be intrinsically disordered (positive y values) or compact (negative y values), whereas the y-axis separates proteins predicted by CDF to be ordered (positive x values) or

Int. J. Mol. Sci. 2020, 21, 3709 11 of 35

(native coils and native pre-molten globules) or proteins with compact globular conformations (native molten globules and ordered proteins) [14,91]. On the other hand, CDF analysis uses the PONDR outputs to discriminate all types of disorder (native coils, native molten globules and native pre-molten globules) from ordered proteins [14]. Therefore, the combined CH-CDF plot gives an opportunity for unique assessment of intrinsic disorder in several categories, allowing predictive classification of proteins into structurally different classes [90,92,93]. To generate a corresponding CH-CDF plot, the coordinates of a query protein are calculated as a distance from the boundary in the CH-plot (Y-coordinate) and an average distance of the respective CDF curve from the CDF boundary (X-coordinate). In the CH-CDF plot, the x-axis separates proteins predicted by CH-plot to be intrinsically disordered (positive y values) or compact (negative y values), Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 11 of 35 whereas the y-axis separates proteins predicted by CDF to be ordered (positive x values) or intrinsically disorderedintrinsically (negative disordered x values). (negative Therefore, x values) proteins. Therefore, can proteins be classified can be by classified their position by their within position each quadrantwithin each of the quadrant resultant of CH-CDF the resultant plot. Here,CH-CDF the lower-rightplot. Here, quadrantthe lower (Q1)-right includes quadrant ordered (Q1) proteinsincludes (i.e.,ordered those proteins predicted (i.e., as those ordered predicted and compact as ordered by and both compact CDF and by CH); both theCDF lower-left and CH); quadrant the lower (Q2)-left containsquadrant proteins (Q2) contains predicted proteins to be predicted disordered to bybe CDFdisordered but compact by CDF by but CH-plot compact (i.e., by native CH-plot molten (i.e., globulesnative molten or hybrid globules proteins or hybrid containing proteins sizable containing levels ofsizable order levels and disorder); of order and the disorder); upper-left the quadrant upper- (Q3)left quadrant contains proteins (Q3) contains predicted proteins to be disorderedpredicted to by be both disordered methods (i.e.,by both proteins methods with (i.e., extended proteins disorder, with suchextended as native disorder, coils and such native as native pre-molten coils and globules); native and pre- themolten upper-right globules); quadrant and the (Q4) upper contains-right proteinsquadrant predicted (Q4) contains to be disorderedproteins predicted by CH-plot to butbe disordered ordered by by CDF CH [92-plot]. Figure but ordered7 presents by the CDF results [92]. ofFigure this analysis 7 presents for the 166 results human of TPR this proteins analysis and for shows166 human that 12 TPR of themproteins are highlyand shows disordered, that 12 52of havethem aare molten highly globular disordered, or hybrid 52 have structure, a molten and globular 100 are or mostly hybrid ordered.structure, In and other 100 words, are mostly based ordered. on these In analyses,other words, ~38.6% based of human on these TPR analyses, proteins ~38.6% are expected of human to be TPR globally proteins disordered, are expected which to is closebe globally to the numberdisordered, generated which byis close per-residue to the number predictors generated (35.5%, by see per above).-residue predictors (35.5%, see above).

0.19

0.09

-0.01

-0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 CH CH

D -0.11

-0.21

-0.31

DCDF FigureFigure 7.7. CH-CDFCH-CDF plotplot analysisanalysis ofof 166166 humanhuman TPRTPR proteins.proteins. QuadrantsQuadrants areare numberednumbered inin aa clockwiseclockwise directiondirection startingstarting withwith Q1Q1 inin thethe lowerlower rightright andand endingending withwith Q4Q4 inin thethe upperupper right.right. TheThe followingfollowing characterizecharacterize proteins proteins within within each each quadrant: quadrant: Q1 Q1 (lower-right (lower-right quadrant) quadrant) –– proteinsproteins predicted predicted to to be be orderedordered byby bothboth predictors,predictors, Q2Q2 (lower-left(lower-left quadrant)quadrant) –– proteinsproteins predictedpredicted toto bebe orderedordered byby CHCH butbut disordereddisordered byby CDF,CDF, Q3Q3 (upper-left(upper-leftquadrant) quadrant)– – proteinsproteins predictedpredicted toto bebe disordereddisordered byby both predictors, andand Q4Q4 (upper-right(upper-right quadrant)quadrant)– –proteins proteins predicted predicted to to be be disordered disordered by by CH CH and and ordered ordered by by CDF. CDF. 2.3. Analysis of the Intrinsic Disorder-Based Functionality of Human TPR Proteins 2.3. Analysis of the Intrinsic Disorder-Based Functionality of Human TPR Proteins It is known that there is an intricate correlation between protein intrinsic disorder and alternative It is known that there is an intricate correlation between protein intrinsic disorder and alternative splicing, where alternatively spliced exons in mRNA are overall more likely to encode IDPRs rather splicing, where alternatively spliced exons in mRNA are overall more likely to encode IDPRs rather than ordered protein segments [31,94–96]. This tendency is even more pronounced in alternative exons, than ordered protein segments [31,94–96]. This tendency is even more pronounced in alternative whose inclusion or exclusion is regulated in a tissue-speciﬁc manner [97]. Therefore, we analyzed the exons, whose inclusion or exclusion is regulated in a tissue-specific manner [97]. Therefore, we correlation between the number of alternative isoforms reported for human TPR proteins and their analyzed the correlation between the number of alternative isoforms reported for human TPR proteins and their disorder status. Results of this analysis are summarized in Figure 8, which shows that although vast majority of human TPR proteins can exist in more than one alternative isoform, there is no obvious correlation between their disorder level and the number of isoforms. An important feature of IDPs and IDPRs is their remarkable binding promiscuity [5,11,21,23,41,42]. In fact, these binding “professionals” are always complexed, invariably interacting with various partners via multiple binding modes [5,11,21,41], and forming static, semi-static, dynamic, or fuzzy complexes [23,42]. They are also capable of semi-static and dynamic polyvalent interactions [98], where multiple binding sites of one protein are simultaneously bound to multiple receptors on another protein [99]. Many IDPs/IDPRs bind partners with both high specificity and low affinity [100], and can fold at binding to their partners [15,16,101]. The degree of such binding- induced folding can be different in various systems, thereby forming complexes with broad structural and functional heterogeneity [23,42]. Furthermore, some IDPs/IDPRs serve as morphing shape- changers that are able to adopt alternate folds as a result of binding to different partners [101–106].

Int. J. Mol. Sci. 2020, 21, 3709 12 of 35 disorder status. Results of this analysis are summarized in Figure8, which shows that although vast majority of human TPR proteins can exist in more than one alternative isoform, there is no obvious correlation between their disorder level and the number of isoforms. An important feature of IDPs and IDPRs is their remarkable binding promiscuity [5,11,21,23,41,42]. In fact, these binding “professionals” are always complexed, invariably interacting with various partners via multiple binding modes [5,11,21,41], and forming static, semi-static, dynamic, or fuzzy complexes [23,42]. They are also capable of semi-static and dynamic polyvalent interactions [98], where multiple binding sites of one protein are simultaneously bound to multiple receptors on another protein [99]. Many IDPs/IDPRs bind partners with both high specificity and low affinity [100], and can fold at binding to their partners [15,16,101]. The degree of such binding-induced folding can be different in various systems, thereby forming complexes with broad structural and functional heterogeneity [23,42]. Furthermore, some IDPs/IDPRs serve as morphing shape-changers that are able Int.to adoptJ. Mol. Sci. alternate 2020, 21, x folds FOR PEER as a resultREVIEW of binding to different partners [101–106]. The binding region12 of 35 of such a morphing IDP can assume completely different structures in the rigidified assemblies formed The binding region of such a morphing IDP can assume completely different structures in the by binding to divergent partners [18,41,107–109]. Many other IDPs/IDPRs are known to form fuzzy rigidified assemblies formed by binding to divergent partners [18,41,107–109]. Many other complexes, where significant disorder is retained, at least outside the binding interface [110–117]. IDPs/IDPRs are known to form fuzzy complexes, where significant disorder is retained, at least Therefore, it is not surprising that many IDPs/IDPRs serve as hub proteins – nodes in complex outside the binding interface [110–117]. Therefore, it is not surprising that many IDPs/IDPRs serve as protein-protein interaction (PPI) networks that have a very large number of connections to other hub proteins – nodes in complex protein-protein interaction (PPI) networks that have a very large nodes [106,118–123]. number of connections to other nodes [106,118–123]. 100 90 80 70 60

based % disorder % based - 40 30 20

PONDR VSL2 PONDR 10 0 0 1 2 3 4 5 6 7 8 Number of isoforms

Figure 8. The number of protein isoforms listed in UniProt against the PONDR® VSL2 percent Figuredisorder 8. score.The number of protein isoforms listed in UniProt against the PONDR® VSL2 percent disorder score. It seems that the aforementioned concept of “morphing shape-changers” is not directly applicable to theIt TPR seems repeats, that the which aforem areentioned structured concept peptide-binding of “morphing motifs shape that- deﬁnechangers” the multivalency is not directly of applicablecorresponding to the TPR TPR proteins. repeats, However, which one are should structured keep peptide in mind-binding that in addition motifs thatto these define ordered the multivalencyrepeats, many of TPR corresponding proteins contain TPR otherproteins. domains, However, and, one most should importantly, keep in functional mind that IDPRsin addition that can to thesebe involved ordered in repeats, protein-protein many TPR interactions, proteins contain and which, other therefore, domains, serve and, asmost the importantly, illustrative examples functional of IDPRsthe disorder-based that can be “morphing involved in shape-changers.” protein-protein Obviously, interactions, while and considering which, therefore, TPR proteins, serve it as would the illustrativebe clearly a examples mistake to of focus the exclusively disorder-based on ordered “morphing TPR repeats. shape-changers. Instead, these” Obviously, proteins should while consideringconsidered inTPR their proteins, entirety. it would be clearly a mistake to focus exclusively on ordered TPR repeats. Instead,Based these on proteins all these considerationsshould considered we decided in their toentirety. check interactability of human TPR proteins using SearchBased Tool on for all the these Retrieval considerations of Interacting we decided Genes; STRING, to check http: interactability//string-db.org of human/. Figure TPR9 represents proteins usingthe inter-TPR Search PPITool network for the generated Retrieval by of STRING Interacting for 161Genes; human STRING, TPR proteins http://string (no STRING-db.org/ information. Figure 9 representswas available the inter for 5- TPR proteins,PPI network UniProt generated IDs: O14607,by STRING Q86TZ1, for 161 Q6P2S7, human Q8IZP2,TPR proteins and Q8NFI4)(no STRING and informationshows that most was ofavailable these proteins for 5 TPR are proteins, involved UniProt in the formation IDs: O14607, of a rather Q86TZ1, dense Q6P2S7, PPI network. Q8IZP2, In and fact, Q8NFI4) and shows that most of these proteins are involved in the formation of a rather dense PPI network. In fact, only two of the remaining 161 TPR proteins (UniProt IDs: Q5W5X9 and Q7Z3J3) are not included in this network. As a result, this network contains 159 nodes (TPR proteins) connected by 1,392 edges (PPIs). In this network, the average node degree is 17.3, and its average local clustering coefficient (which defines how close its neighbors are to being a complete clique; the local clustering coefficient is equal to 1 if every neighbor connected to a given node Ni is also connected to every other node within the neighborhood, and it is equal to 0 if no node that is connected to a given node Ni connects to any other node that is connected to Ni) is 0.499. Since the expected number of interactions among proteins in a similar size set of proteins randomly selected from human proteome is equal to 708, this TPR internal PPI network has significantly more interactions than expected, being characterized by a PPI enrichment p-value of < 10−16. Therefore, these data indicate that the majority of human TPR proteins can interact with each other (although the confidence of this inter-family PPI network is low). Increasing STRING confidence level to 0.4 (moderate confidence, which is a default minimum required interaction score) results in reduction of the reliably interacting proteins from 159 to 124. In the resulting PPI network (see Supplementary Figure S1), 124 nodes are linked by 301 edges,

Int. J. Mol. Sci. 2020, 21, 3709 13 of 35 only two of the remaining 161 TPR proteins (UniProt IDs: Q5W5X9 and Q7Z3J3) are not included in this network. As a result, this network contains 159 nodes (TPR proteins) connected by 1,392 edges (PPIs). In this network, the average node degree is 17.3, and its average local clustering coefficient (which defines how close its neighbors are to being a complete clique; the local clustering coefficient is equal to 1 if every neighbor connected to a given node Ni is also connected to every other node within the neighborhood, and it is equal to 0 if no node that is connected to a given node Ni connects to any other node that is connected to Ni) is 0.499. Since the expected number of interactions among proteins in a similar size set of proteins randomly selected from human proteome is equal to 708, this TPR internal PPI network has significantly more interactions than expected, being characterized 16 by a PPI enrichment p-value of < 10− . Therefore, these data indicate that the majority of human TPR proteins can interact with each other (although the confidence of this inter-family PPI network is low). Increasing STRING confidence level to 0.4 (moderate confidence, which is a default minimum required interaction score) results in reduction of the reliably interacting proteins from 159 to 124. In the resulting PPI network (see Supplementary Figure S1), 124 nodes are linked by 301 edges, giving the average node degree of 3.74, average local clustering coefficient of 0.422, expected number of 16 edges of 89 and PPI enrichment p-value of < 10− . Further increase in confidence level results in the breakage of the network into a few small clusters and a multitude of non-interacting proteins (see Supplementary Figure S2 for a network with high confidence of 0.7). Next, we looked at the global interactivity of the whole set of human TPR proteins by including a first shell interactors (i.e., proteins interacting with TPR proteins). The resulting PPI network generated by STRING is shown in Figure 10. Note that the number of interactors in STRING is limited to 500. In this analysis, the highest confidence level of 0.9 was used. The resulting interactome includes 661 nodes connected by 7655 edges. Therefore, this interactome is characterized by an average node degree of 23.2 and it shows an average local clustering coefficient of 0.67. The expected number of interactions for the set of proteins of its size is 3838, indicating this human TRP-centered PPI network 16 has significantly more interactions than expected (PPI enrichment p-value is < 10− ). Decreasing STRING confidence level to 0.15 (this low confidence level ensures inclusion of the maximal number of TRP proteins into the inter-TPR PPI network) generated a dense network of 661 proteins connected by 35,582 interactions with the average node degree of 108, average local clustering coefficient of 16 0.464, expected number of edges of 23,094, and PPI enrichment p-value of < 10− (see Supplementary Figure S3). We also looked at the correlation between the interactability of individual TRP proteins evaluated by STRING at different confidence levels and their level of intrinsic disorder. Results of this analysis are shown in Figure 11 illustrating that no relationship was observed between the PONDR-FIT percent disorder score and the number of protein interactions. Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 13 of 35

giving the average node degree of 3.74, average local clustering coefficient of 0.422, expected number of edges of 89 and PPI enrichment p-value of < 10−16. Further increase in confidence level results in

Int.the J. Mol. breakage Sci. 2020 of, 21the, 3709 network into a few small clusters and a multitude of non-interacting proteins (see14 of 35 Supplementary Figure S2 for a network with high confidence of 0.7).

Figure 9. Figure 9.STRING-based STRING-based analysisanalysis of the inter inter-set-set interactivity interactivity of of 166 166 human human TPR TPR proteins proteins using using the the lowlow confidence confidence level level of of 0.15. 0.15. ThisThis confidenceconfidence level level was was selected selected to to ensure ensure maximal maximal inclusion inclusion of TPR of TPR proteinsproteins in inthe the resulting resulting PPI. PPI. STRING STRING generates generates a network a network of predicted of predicted associations associations based onbased predicted on andpredicted experimentally-validated and experimentally- informationvalidated information on the interaction on the interaction partners partners of a protein of a protein of interest of interest [124]. In the[124] corresponding. In the corresponding network, the network, nodes thecorrespond nodes correspond to proteins, to whereas proteins, the whereas edges the show edges predicted show or knownpredicted functional or known associations. functional Seven associations. types of evidence Seven types are used of evidenceto build the are corresponding used to build network, the andcorresponding are indicated network, by the di andfferently are indicated colored lines:by the a greendifferently line representscolored lines: neighborhood a green line evidence; represents a red lineneighborhood – the presence evidence; of fusion a evidence;red line – athe purple presence line –of experimental fusion evidence; evidence; a purple a blue line line – experimental – co-occurrence evidence;evidence; a a light blue blue line line– co –-occurrence database evidence;evidence; aa yellowlight blue line line – text – database mining evidence; a and yellow a black line line– – co-expressiontext mining evidence; evidence and [124 a]. black line – co-expression evidence [124].

Int. J. Mol. Sci. 2020, 21, 3709 15 of 35 Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 14 of 35

FigureFigure 10. 10.STRING-based STRING-based analysis analysis of the of whole the whole set of set human of human TPR proteins TPR proteins using the using highest the conﬁdence highest level of 0.9. This conﬁdence level was selected to ensure maximal inclusion of TPR proteins in the Int. J. Mol.confidence Sci. 2020, 2 level1, x FOR of 0.9. PEER This REVIEW confidence level was selected to ensure maximal inclusion of TPR proteins 15 of 35 resultingin the resulting PPI. PPI.

50000 Next, we looked at the global interactivity of the whole set of human TPR proteins by including 45000 R² = 0.0004 a first shell interactors (i.e., proteins interacting with TPR proteins).0.4 The resulting PPI network generated by STRING40000 is shown in Figure 10. Note that the number of interactors in STRING is limited 0.7R² = 7E-05 to 500. In this analysis,35000 the highest confidence level of 0.9 was used. The resulting interactome 30000 R² = 9E-05 includes 661 nodes connected by 7655 edges. Therefore, this interactome0.9 is characterized by an average node degree25000 of 23.2 and it shows an average local clustering coefficient of 0.67. The expected number of interactions20000 for the set of proteins of its size is 3838, indicating this human TRP-centered PPI network hasInteractions 15000significantly more interactions than expected (PPI enrichment p-value is < 10−16). Decreasing STRING10000 confidence level to 0.15 (this low confidence level ensures inclusion of the maximal number of5000 TRP proteins into the inter-TPR PPI network) generated a dense network of 661 proteins connected by0 35,582 interactions with the average node degree of 108, average local clustering coefficient of0% 0.464, 10%expected20% number30% of edges40% of 23,094,50% and60% PPI70% enrichment80% p-value of < 10−16 (see Supplementary Figure S3). PONDR-FIT % disorder We also looked at the correlation between the interactability of individual TRP proteins Figure 11. The quantity of protein interactions given by STRING at medium (0.4), high (0.7), and evaluated by STRING at different confidence levels and their level of intrinsic disorder. Results of highest (0.9) conﬁdence by the PONDR-FIT percent disorder score. Figurethis analysis11. The quantity are shown of protein in Figure interactions 11 illustrating given that by nSTRINGo relationship at medium was observed(0.4), high between (0.7), and the highestPONDR (0.9)-FIT confidence percent disorder by the PONDRscore and-FIT the percentnumber disorderof protein score. interactions.

2.4. Structural Properties of Human TPR Proteins

To shed some light on the structural repertoire (or structural mosaic) of human TPR proteins, we collected available information on structures of different members of this family from PDB. Results of this analysis are summarized in Figure 12, which shows structures of 56 TPR proteins and illustrates that the vast majority of human TPR proteins with known structures are mostly α-helical. However, although it was known a priori that TPR repeats are helical, Figure 12 indicates than not all human TPR proteins are α-helical. This is because of the fact that many structures shown in Figure 12 are not representing the entire TPR proteins, but rather their crystalizable domains or regions amenable to NMR- or cryo-electron microscopy-based structural characterization. This fact is further illustrated by Figure 13, showing the fractions of these proteins represented by the experimentally validated ordered domains. This analysis reveals that there is a week anti- correlation between the structural coverage of 56 human TPR proteins evaluated for each protein as percent of its sequence that is mapped to all the known structures and intrinsic disorder predisposition calculated as corresponding PONDR® FIT-based PPDR values. Figure 13 shows that no structure is currently available for any TPR protein with disorder content exceeding 55%. Furthermore, one can see there an expected trend, where more disordered proteins show less structural coverage. Furthermore, some of the structures shown in Figure 12 are not the TPR motifs of the corresponding proteins but rather represent other functional domains. For example, structures with the PDB IDs 1RL1, 5U9J, and 3B7X that contain noticeable levels of β-structure correspond to the bipartite CS domain (which is a ~100-residue protein-protein interaction module named after CHORD-containing proteins and SGT1) of human protein SGT1 homolog (PDB ID 1RL1), PPIase FKBP-type domain of aryl-hydrocarbon-interacting protein-like 1 (AIPL1; PDB ID: 5U9J), and another PPIase FKBP-type domain of the inactive peptidyl-prolyl cis-trans isomerase FKBP6 (PDB ID: 3B7X). Furthermore, some of the structures shown in Figure 12 contain noticeable disordered regions.

Int. J. Mol. Sci. 2020, 21, 3709 16 of 35

2.4. Structural Properties of Human TPR Proteins To shed some light on the structural repertoire (or structural mosaic) of human TPR proteins, we collected available information on structures of diﬀerent members of this family from PDB. Results of

Int.this J. Mol. analysis Sci. 2020, are21, x summarized FOR PEER REVIEW in Figure 12, which shows structures of 56 TPR proteins and16 of illustrates 35 that the vast majority of human TPR proteins with known structures are mostly α-helical.

Figure 12. Cont. Figure 12. Cont.

Int. J. Mol. Sci. 2020, 21, 3709 17 of 35 Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 17 of 35

Figure 12. A portrait gallery of 56 human TPR proteins with structure available in PDB. If multiple structures were available for a given protein, the structure with the greatest number of residues was selected, otherwise, the X-ray crystallographic structure with the best resolution was selected. For proteins with NMR structures, only one model is shown. Int. J. Mol. Sci. 2020, 21, 3709 18 of 35

However, although it was known a priori that TPR repeats are helical, Figure 12 indicates than not all human TPR proteins are α-helical. This is because of the fact that many structures shown in Figure 12 are not representing the entire TPR proteins, but rather their crystalizable domains or regions amenable to NMR- or cryo-electron microscopy-based structural characterization. This fact is further illustrated by Figure 13, showing the fractions of these proteins represented by the experimentally validated ordered domains. This analysis reveals that there is a week anti-correlation between the structural coverage of 56 human TPR proteins evaluated for each protein as percent of its sequence that is mapped to all the known structures and intrinsic disorder predisposition calculated as corresponding PONDR® FIT-based PPDR values. Figure 13 shows that no structure is currently available for any TPR protein with disorder content exceeding 55%. Furthermore, one can see there an expected trend, where more disordered proteins show less structural coverage. Furthermore, some of the structures shown in Figure 12 are not the TPR motifs of the corresponding proteins but rather represent other functional domains. For example, structures with the PDB IDs 1RL1, 5U9J, and 3B7X that contain noticeable levels of β-structure correspond to the bipartite CS Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 18 of 35 domain (which is a ~100-residue protein-protein interaction module named after CHORD-containing proteinsFigure and 12. SGT1) A portrait of human gallery protein of 56 human SGT1 TPR homolog proteins (PDB with IDstructure 1RL1), available PPIase FKBP-typein PDB. If multiple domain of aryl-hydrocarbon-interactingstructures were available for protein-like a given protein, 1 (AIPL1; the structure PDB ID:with 5U9J), the greatest and another number PPIaseof residues FKBP-type was domainselected, of the otherwise, inactive peptidyl-prolyl the X-ray crystallographic cis-trans isomerase structure with FKBP6 the (PDBbest resolution ID: 3B7X). was Furthermore, selected. For some of theproteins structures with shown NMR struc in Figuretures, only12 contain one model noticeable is shown. disordered regions.

FigureFigure 13.13. CorrelationCorrelation ofof thethe structuralstructural coveragecoverage (percent(percent ofof proteinprotein sequencesequence thatthat mapmap toto knownknown structures)structures) ofof 56 human human TPR TPR proteins proteins with with their their intrinsic intrinsic disorder disorder content content evaluated evaluated as PONDR as PONDR® FIT®- FIT-basedbased PPDR PPDR values. values.

2.5.2.5. FunctionalFunctional AnalysisAnalysis ofof MostMost DisorderedDisordered HumanHuman TPRTPR ProteinsProteins Finally,Finally, wewe conductedconducted functionalfunctional disorderdisorder analysisanalysis forfor 1010 mostmost disordereddisordered TPRTPR proteins.proteins. ResultsResults ofof thisthis analysisanalysis areare outlinedoutlined below.below. Figure 14 presents the corresponding data for the most disordered TPR protein, human tetratricopeptide repeat protein 1 (TTC1), which is characterized by the percent of predicted disordered residues (PPDR) of 73.3 15.4% and the average disorder score (ADS) of 0.65 0.11. The N-terminal ± ± half of this 292-residue long protein, which is involved in unfolded protein binding, is highly disordered (Figure 14A). TTC1 contains three TPRs, residues 116–149, 155–188, and 189–222 with the ADS values of

Figure 14. Functional disorder analysis of human tetratricopeptide repeat protein 1 (TTC1; UniProt ID: Q99614). (A) Intrinsic disorder profile generated by DiSpi web crawler. (B) Functional disorder profile generated by D2P2 platform. (C) Interactability of human TTC1 protein analyzed by STRING.

Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 18 of 35

Int. J. Mol. Sci. 2020, 21, 3709 19 of 35

0.61 0.18, 0.55 0.21, and 0.49 0.17, respectively, and has multiple sites of different posttranslational ± ± ± modificationsFigure and 7 13. molecular Correlation recognition of the structural features coverage (MoRFs), (percent of disorder-based protein sequence protein-proteinthat map to known interaction ® sites where disorderedstructures) of 56 regions human TPR can proteins fold at with interaction their intrinsic with disorder binding content evaluated partners as (FigurePONDR FIT14B).- Finally, based PPDR values. Figure 14C presents the TTC1-centered PPI network generated by STRING with the medium confidence level of 0.4.2.5. ThereFunctional are Analysis 72 nodes of Most in thisDisordered network, Human which TPR Proteins are connected by 280 edges. This network is characterizedFinally, by the we average conducted node functional degree ofdisorder 7.78, averageanalysis for local 10 most clustering disordered coeffi TPRcient proteins. of 0.785, Results expected 16 number ofof edgesthis analysis of 115, are and outlined PPI enrichmentbelow. p-value of <10− .

Figure 14.FigureFunctional 14. Functional disorder disorder analysis analysis of human of human tetratricopeptide tetratricopeptide repeat repeat proteinprotein 1 1 (TTC1; (TTC1; UniProt UniProt ID: Q99614).ID: (A) Q99614). Intrinsic (A disorder) Intrinsic proﬁle disorder generated profile generated by DiSpi by webDiSpi crawler. web crawler. (B) Functional(B) Functional disorder disorder proﬁle generatedprofile by D 2generatedP2 platform. by D2P (C2 platform.) Interactability (C) Interactability of human of human TTC1 proteinTTC1 protein analyzed analyzed by by STRING. STRING.

Figure 15 presents the results of functional disorder analysis of human tetratricopeptide repeat protein 36 (TTC36; PPDR = 66.1 13.6%; ADS = 0.593 0.063). This 189-residue-long protein related to ± ± cilium assembly has disordered N- and C-tails, and there are two long IDPRs (see Figure 15A). TTC36 contains three TPRs, residues 51-84, 86-118, and 123-156, with the ADS values of 0.51 0.18, 0.56 0.13, ± ± and 0.72 0.10, and is predicted to have two MoRFs, residues 7-28 and 73-82 (see Figure 15B). The ± mostly disordered N-terminal region is missing in isoform 2, where the residues 1-59 were removed as a result of alternative splicing. Although the first MoRF is located outside the TPR-containing region, the second MoRF is positioned at the C-terminal half of this TPR (Figure 15B). Therefore, alternative splicing is removing one of the MoRFs, potentially affecting disorder-based interactability of this protein. TTC36-centered PPI network generated by STRING with the medium confidence level of 0.4 includes 27 proteins connected by 127 edges (see Figure 15C). This network is characterized by the average node degree of 9.41, average local clustering coefficient of 0.889, expected number of edges of 16 28, and PPI enrichment p-value of < 10− . Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 19 of 35

Figure 14 presents the corresponding data for the most disordered TPR protein, human tetratricopeptide repeat protein 1 (TTC1), which is characterized by the percent of predicted disordered residues (PPDR) of 73.3 ± 15.4% and the average disorder score (ADS) of 0.65 ± 0.11. The N-terminal half of this 292-residue long protein, which is involved in unfolded protein binding, is highly disordered (Figure 14A). TTC1 contains three TPRs, residues 116–149, 155–188, and 189–222 with the ADS values of 0.61 ± 0.18, 0.55 ± 0.21, and 0.49 ± 0.17, respectively, and has multiple sites of different posttranslational modifications and 7 molecular recognition features (MoRFs), disorder- based protein-protein interaction sites where disordered regions can fold at interaction with binding partners (Figure14B). Finally, Figure 14C presents the TTC1-centered PPI network generated by STRING with the medium confidence level of 0.4. There are 72 nodes in this network, which are connected by 280 edges. This network is characterized by the average node degree of 7.78, average local clustering coefficient of 0.785, expected number of edges of 115, and PPI enrichment p-value of <10−16. Figure 15 presents the results of functional disorder analysis of human tetratricopeptide repeat protein 36 (TTC36; PPDR = 66.1 ± 13.6%; ADS = 0.593 ± 0.063). This 189-residue-long protein related to cilium assembly has disordered N- and C-tails, and there are two long IDPRs (see Figure 15A). TTC36 contains three TPRs, residues 51-84, 86-118, and 123-156, with the ADS values of 0.51 ± 0.18, 0.56 ± 0.13, and 0.72 ± 0.10, and is predicted to have two MoRFs, residues 7-28 and 73-82 (see Figure 15B). The mostly disordered N-terminal region is missing in isoform 2, where the residues 1-59 were removed as a result of alternative splicing. Although the first MoRF is located outside the TPR- containing region, the second MoRF is positioned at the C-terminal half of this TPR (Figure 15B). Therefore, alternative splicing is removing one of the MoRFs, potentially affecting disorder-based interactability of this protein. TTC36-centered PPI network generated by STRING with the medium Int.confidence J. Mol. Sci. 2020level, 21of ,0.4 3709 includes 27 proteins connected by 127 edges (see Figure 15C). This network is 20 of 35 characterized by the average node degree of 9.41, average local clustering coefficient of 0.889, expected number of edges of 28, and PPI enrichment p-value of < 10−16.

Figure 15. Functional disorder analysis of human tetratricopeptide repeat protein 36 (TTC36; UniProt ID:Figure A6NLP5). 15. Functional (A) Intrinsic disorder disorderanalysis of profile human generatedtetratricopeptide by DiSpi repeat web protein crawler. 36 (TTC36; (B) U FunctionalniProt disorder profileID: A6NLP5). generated (A) Intrinsic by D2P 2disorderplatform. profile (C )generated Interactability by DiSpi of web human crawler. TTC36 (B) Functional protein analyzed disorder by STRING. profile generated by D2P2 platform. (C) Interactability of human TTC36 protein analyzed by STRING. Figure 16 reflects functional disorder analysis of human nuclear autoantigenic sperm protein Figure 16 reflects functional disorder analysis of human nuclear autoantigenic sperm protein (NASP; PPDR = 76.1 3.6%; ADS = 0.711 0.071). NASP is needed for cell proliferation, DNA (NASP; PPDR = 76.1 ±± 3.6%; ADS = 0.711 ± 0.071).± NASP is needed for cell proliferation, DNA replication,replication, and and normalnormal cell cycle cycle progression. progression. This This 788- 788-residue-longresidue-long protein protein interacts interacts with HSP90 with HSP90 and H1 linker histones (via the histone-binding regions at residues 116-127, 211-244, and 469-512 [125]) and stimulates HSP90 ATPase activity. NASP has three TPRs, residues 43-76, 542-575, and 584-617 with the ADS values of 0.21 0.08, 0.37 0.10, and 0.28 0.18, and four coiled-coil regions (residues 136–164, ± ± ± 460–487, 597–665, and 753–778). There are three alternatively spliced isoform of NASP. In the isoform 2, region 138–476 is missing; isoform 3 has MAMESTATAAVAAELVSADKIEDVPAPSTSADKVES MFLLLLHLQIKWRATINLLSVTED GLHFVEYYLNRIIH substitution at 1–36 region, and isoform → 4 misses the 36–99 region. Figure 16A,B show that more than 400-residue-long region (residues 100–516) located in the middle of NASP is predicted to be highly disordered. This long IDPR includes all histone-binding regions and two coiled-coil regions and is predicted to contain 11 MoRFs. Supplementary Figure S4 shows how alternative splicing affects disorder predisposition of human NASP. It is clearly seen that due to the removal of a long central IDPR, isoform 2 is essentially more ordered than the canonical form. Similarly, alternative splicing induced changes in disorder of the N-tail, making isoform 3 more ordered than the canonical form, and isoform 4 more disordered than the canonical NASP. Figure 16B shows that the entire NASP is heavily decorated with numerous phosphorylation, acetylation and ubiquitylation sites and contains 18 MoRFs, which incorporate more than half of the residues of this protein. Therefore, it is not surprising that NASP serves as a hub of very dense PPI network (Figure 16C) generated by STRING with the medium confidence level of 0.4. This network includes 207 proteins linked by 6969 interactions and is characterized by the average node degree of 67.3, average local clustering coefficient of 0.738, expected number of edges of 1161, 16 and PPI enrichment p-value of < 10− . Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 20 of 35

and H1 linker histones (via the histone-binding regions at residues 116-127, 211-244, and 469-512 [125]) and stimulates HSP90 ATPase activity. NASP has three TPRs, residues 43-76, 542-575, and 584- 617 with the ADS values of 0.21 ± 0.08, 0.37 ± 0.10, and 0.28 ± 0.18, and four coiled-coil regions (residues 136–164, 460–487, 597–665, and 753–778). There are three alternatively spliced isoform of NASP. In the isoform 2, region 138–476 is missing; isoform 3 has MAMESTATAAVAAELVSADKIEDVPAPSTSADKVES → MFLLLLHLQIKWRATINLLSVTED GLHFVEYYLNRIIH substitution at 1–36 region, and isoform 4 misses the 36–99 region. Figures 16A and 16B show that more than 400-residue-long region (residues 100–516) located in the middle of NASP is predicted to be highly disordered. This long IDPR includes all histone-binding regions and two coiled-coil regions and is predicted to contain 11 MoRFs. Supplementary Figure S4 shows how alternative splicing affects disorder predisposition of human NASP. It is clearly seen that due to the removal of a long central IDPR, isoform 2 is essentially more ordered than the canonical form. Similarly, alternative splicing induced changes in disorder of the N-tail, making isoform 3 more ordered than the canonical form, and isoform 4 more disordered than the canonical NASP. Figure 16B shows that the entire NASP is heavily decorated with numerous phosphorylation, acetylation and ubiquitylation sites and contains 18 MoRFs, which incorporate more than half of the residues of this protein. Therefore, it is not surprising that NASP serves as a hub of very dense PPI network (Figure 16C) generated by STRING with the medium confidence level of 0.4. This network includes Int.207 J. Mol.proteins Sci. 2020 linked, 21, 3709by 6969 interactions and is characterized by the average node degree of 67.3, 21 of 35 average local clustering coefficient of 0.738, expected number of edges of 1161, and PPI enrichment p-value of < 10−16.

FigureFigure 16. 16. FunctionalFunctional disorder disorder analysis analysis of ofhuman human nuclear nuclear autoantigenic autoantigenic sperm sperm protein protein (NASP; (NASP; UniProt ID:UniProt P49321). ID: P49321) (A) Intrinsic. (A) Intrinsic disorder disorder proﬁle profile generated generated by by DiSpiDiSpi web web crawler. crawler. (B)( BFunctional) Functional disorder proﬁledisorder generated profile generated by D2P by2 platform.D2P2 platform. (C )(C Interactability) Interactability of of human human NASP NASP analyzed analyzed by STRING. by STRING.

FigureFigure 17 showsshows functional functional disorder disorder profiles profiles and interaction and interaction network of network human tetratricopeptide of human tetratricopeptide repeat protein 31 (TTC31; PPDR = 62.2 ± 11.2%; ADS = 0.591 ± 0.097). This 519-residue-long protein repeat protein 31 (TTC31; PPDR = 62.2 11.2%; ADS = 0.591 0.097). This 519-residue-long protein contains a coiled-coil region (residues 147–197)± and three TPRs, residues± 305–338, 339–372, and 373– contains406 with a the coiled-coil ADS values region of 0.1 (residues7 ± 0.12, 0.1 147–197)5 ± 0.06, and and 0.3 three0 ± 0.11. TPRs, TTC31 residues has an alternatively 305–338, 339–372, spliced and 373–406 withisoform, the ADSwhere values the 281 of-285 0.17 region0.12, underwent 0.15 REERP0.06, and→ ATSPC, 0.30 and0.11. where TTC31 the entire has an C- alternativelyterminal spliced ± ± ± isoform,half (residues where 286 the-519) 281-285 is missing. region underwent Disorder profile REERP of TTC31ATSPC, (see Figuresand where 17A the and entire 17B) C-terminal is half → (residuescharacterized 286-519) by the ispresence missing. of two Disorder long IDPRs profile (residues of TTC31 82–310 and (see 399 Figure–519) that17A,B) cover is coiled characterized-coil by the region and C-terminal region of last TPR. Because of the removal of the mostly ordered C-terminal presence of two long IDPRs (residues 82–310 and 399–519) that cover coiled-coil region and C-terminal region of last TPR. Because of the removal of the mostly ordered C-terminal region containing all TPRs by alternative splicing, the resulting isoform is highly disordered (see Supplementary Figure S5). Several PTM sites and 12 MoRFs are spread over this protein (Figure 17B). TTC31-centered PPI network generated by STRING includes 69 proteins connected by 689 interactions (see Figure 17C). This network is characterized by the average node degree of 20, average local clustering coefficient of 16 0.813, expected number of edges of 115, and PPI enrichment p-value of < 10− . Figure 18 presents the results of functional disorder analysis of human Hsc70-interacting protein (HIP, or protein FAM10A1; PPDR = 62.4 10.5%; ADS = 0.616 0.072). This 369-residue-long ± ± protein forms homotetramers and is engaged in interaction with heat shock proteins, where one HIP homotetramer binds the ATPase domains of at least two HSC70 molecules. HIP has three TPRs, residues 114–147, 148–181, and 182–215 with the ADS values of 0.35 0.23, ± 0.28 0.14, and 0.26 0.12, and a heat shock chaperonin-binding motif, STI1 domain (residues ± ± 319–358). According to Figure 18A,B, long regions at both N- and C-termini of HIP are predicted to be disordered (residues 1–122 and 213–369), suggesting that STI1 domain is a disorder-based binding region. In agreement with this hypothesis, Figure 18B shows that HIP contains multiple PTMs sites and 9 MoRFs, one of which (residues 306–337) overlaps with STI1 domain. In the HIP-centered PPI network (Figure 18C), there are 78 nodes linked by 783 interactions. This STRING-generated network is characterized by the average node degree of 20.1, average local clustering coefficient of 0.793, expected 16 number of edges of 180, and PPI enrichment p-value of < 10− . Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 21 of 35

region containing all TPRs by alternative splicing, the resulting isoform is highly disordered (see Supplementary Figure S5). Several PTM sites and 12 MoRFs are spread over this protein (Figure 17B). TTC31-centered PPI network generated by STRING includes 69 proteins connected by 689 interactionsInt. J. Mol. Sci. 20(see20, 2Figure1, x FOR 17C). PEER ThisREVIEW network is characterized by the average node degree of 20, average21 of 35 local clustering coefficient of 0.813, expected number of edges of 115, and PPI enrichment p-value of region containing all TPRs by alternative splicing, the resulting isoform is highly disordered (see < 10−16. Supplementary Figure S5). Several PTM sites and 12 MoRFs are spread over this protein (Figure 17B). TTC31-centered PPI network generated by STRING includes 69 proteins connected by 689 interactions (see Figure 17C). This network is characterized by the average node degree of 20, average Int.local J. Mol. clustering Sci. 2020 coefficient, 21, 3709 of 0.813, expected number of edges of 115, and PPI enrichment p-value of 22 of 35 < 10−16.

Figure 17. Functional disorder analysis of human tetratricopeptide repeat protein 31 (TTC31; UniProt ID: Q49AM3). (A) Intrinsic disorder profile generated by DiSpi web crawler. (B) Functional disorder profile generated by D2P2 platform. (C) Interactability of human TTC31 protein analyzed by STRING using the medium confidence level of 0.4.

FigureFigure 17. 17.18 FunctionalpresentsFunctional the disorder disorderresults analysis of analysisfunctional of human of disorder human tetratricopeptide tetratricopeptideanalysis ofrepeat human protein repeatHsc70 31 (TTC31;- proteininteracting UniProt 31 (TTC31;protein UniProt (HIP,ID:I D:or Q49AM3). Q49AM3)protein FAM10A1;. (A (A) Intrinsic) Intrinsic PPD disorderR disorder = 6 2.profile4 ± profile10.5%; generated AD generatedS by = 0DiSpi.616 by ±web 0 DiSpi.072). crawler. This web ( B369 crawler.) Functional-residue (B- )disorderlong Functional protein disorder 2 2 formsprofileprofile homotetramers generatedgenerated by by andD DP2 Pplatform. is2 platform. engaged (C) Interactability in (C interaction) Interactability of withhuman of heat TTC31 human shock protein TTC31 pro analyzedteins, protein where by analyzedSTRING one HIP by STRING using the medium confidence level of 0.4. homotetramerusing the medium binds the confidence ATPase domains level of of 0.4. at least two HSC70 molecules. Figure 18 presents the results of functional disorder analysis of human Hsc70-interacting protein (HIP, or protein FAM10A1; PPDR = 62.4 ± 10.5%; ADS = 0.616 ± 0.072). This 369-residue-long protein forms homotetramers and is engaged in interaction with heat shock proteins, where one HIP homotetramer binds the ATPase domains of at least two HSC70 molecules.

FigureFigure 18. 18. FunctionalFunctional disorder disorder analysis of of human Hsc70 Hsc70-interacting-interacting protein protein (HIP, (HIP, or or protein protein FAM10A1; UniProtFAM10A1; ID: UniProt P50502). ID: (P50502)A) Intrinsic. (A) Intrinsic disorder disorder proﬁle profile generated generated by by DiSpi DiSpi webweb crawler. (B ()B ) Functional disorder proﬁle generated by D2P2 platform. (C) Interactability of human HIP analyzed by STRING.

Results of intrinsic disorder analysis in 770-residue-long human tetratricopeptide repeat protein Figure 18. Functional disorder analysis of human Hsc70-interacting protein (HIP, or protein 14 (TTC14; PPDR = 56.1 15.0%; ADS = 0.545 0.114) are shown in Figure 19. This protein can interact FAM10A1; UniProt ID:± P50502). (A) Intrinsic disorder± profile generated by DiSpi web crawler. (B) with DNA and contains a conserved S1 motif with unknown function (residues 126–208), four TPRs (residues 210–243, 307–340, 342–374, and 382–415 with the ADS values of 0.59 0.08, 0.21 0.14, 0.29 ± ± 0.09, and 0.39 0.18), as well as ﬁve regions with compositional bias, such as Poly-Glu (residues ± ± 393–396), Ser-rich (residues 475–525), and three Poly-Ser regions (residues 475–483, 487–497, and 580–583). In addition to the canonical form, TTC14 has two alternatively spliced isoforms. In isoform 2, the 592–653 region is changed to VYSYLFKKLTIKQPQAGPSGDIPEEGIVIIDDSSIHVTDPEDLQVGQ DMEVEDSGIDDPDHG and residues 654–770 are missing. In isoform 3, the 340-residue-long C-terminal region 431–770 is shortened to the VIPYFLLEI peptide. Figure 19A indicates that TTC14 has a highly disordered C-terminal region (residues 389–770) that incorporates all regions with compositional bias. Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 22 of 35

Functional disorder profile generated by D2P2 platform. (C) Interactability of human HIP analyzed by STRING.

HIP has three TPRs, residues 114–147, 148–181, and 182–215 with the ADS values of 0.35 ± 0.23, 0.28 ± 0.14, and 0.26 ± 0.12, and a heat shock chaperonin-binding motif, STI1 domain (residues 319– 358). According to Figures 18A and 18B, long regions at both N- and C-termini of HIP are predicted to be disordered (residues 1–122 and 213–369), suggesting that STI1 domain is a disorder-based binding region. In agreement with this hypothesis, Figure 18B shows that HIP contains multiple PTMs sites and 9 MoRFs, one of which (residues 306–337) overlaps with STI1 domain. In the HIP- centered PPI network (Figure 18C), there are 78 nodes linked by 783 interactions. This STRING- generated network is characterized by the average node degree of 20.1, average local clustering coefficient of 0.793, expected number of edges of 180, and PPI enrichment p-value of < 10−16. Results of intrinsic disorder analysis in 770-residue-long human tetratricopeptide repeat protein 14 (TTC14; PPDR = 56.1 ± 15.0%; ADS = 0.545 ± 0.114) are shown in Figure 19. This protein can interact with DNA and contains a conserved S1 motif with unknown function (residues 126–208), four TPRs (residues 210–243, 307–340, 342–374, and 382–415 with the ADS values of 0.59 ± 0.08, 0.21 ± 0.14, 0.29 ± 0.09, and 0.39 ± 0.18), as well as five regions with compositional bias, such as Poly-Glu (residues 393–396), Ser-rich (residues 475–525), and three Poly-Ser regions (residues 475–483, 487–497, and 580– 583). In addition to the canonical form, TTC14 has two alternatively spliced isoforms. In isoform 2, the 592–653 region is changed to VYSYLFKKLTIKQPQAGPSGDIPEEGIVIIDDSSIHVTDPEDLQVGQ DMEVEDSGIDDPDHG and residues 654–770 are missing. In isoform 3, the 340-residue-long C-terminal region 431–770 is shortened to the VIPYFLLEI peptide. Figure 19A indicates that TTC14 has a highly disordered C- terminal region (residues 389–770) that incorporates all regions with compositional bias. Int. J. Mol. Sci. 2020, 21, 3709 23 of 35

FigureFigure 19. 19. FunctionalFunctional disorder disorder analysis analysis of human of human tetratricopeptide tetratricopeptide repeat protein repeat 14 (TTC14; protein UniProt 14 (TTC14; UniProt ID:ID: Q96N46). Q96N46). ( A)) Intrinsic Intrinsic disorder disorder profile profile generated generated by DiSpi by web DiSpi crawler. web ( crawler.B) Functional (B) disorder Functional disorder profileprofile generated generated by D D2P22P platform.2 platform. (C) Interactability (C) Interactability of human of TTC14 human protein TTC14 analyzed protein by analyzed STRING by STRING usingusing medium medium confidence confidence level level of 0.4. of 0.4.

Furthermore,Furthermore, all all alternative alternative splicing splicing-induced-induced changes changes take take place place within within this long this Clong-terminal C-terminal IDPR. IDPR. Figure 19B shows that this protein has multiple PTMs and MoRFs, which are mostly Figure 19B shows that this protein has multiple PTMs and MoRFs, which are mostly concentrated concentrated within the disordered C-terminal region. According to STRING analysis (see Figure within19C), theTTC14 disordered is engaged C-terminal in interaction region. with 40 According partners. In tothe STRING resulting PPI analysis network, (see there Figure are 13319C), TTC14 is engaged in interaction with 40 partners. In the resulting PPI network, there are 133 edges, and it is characterized by the average node degree of 6.65, average local clustering coefficient of 0.762, expected 16 number of edges of 44, and PPI enrichment p-value of < 10− . Figure 20 shows functional disorder profiles and interaction network of human tetratricopeptide repeat protein 9B (TTC9B; PPDR = 60.4 15.0%; ADS = 0.590 0.053). This 239-residue-long protein ± ± has a Pro-rich segment (residues 17–50) and contains two TPRs, residues 65–99 and 171–204 (ADS values of 0.63 0.14 and 0.21 0.16). TTV9B has an alternative splicing-generated isoform, in which ± ± the C-terminal region 143–239 is changed to a shorter sequence GTPSGGGGMGHEGRGQSGELGD LGAR GPGAEGSRAVGFSGSLQSLIKERD. Disorder is concentrated within the N-terminal half of this protein (see Figure 20A,B), which can be approximated as one long IDPR (residues 1–140). Alternative splicing-induced changes in TTC9B sequence convert this protein to a completely disordered form characterized by PPDR = 93.0 6.0% and ADS = 0.787 0.010 (see Supplementary Figure S6). The ± ± first TPR of TTC9B overlaps with longest of three MoRFs found in this IDPR (residues 1-16, 52-98, and 140-146) and contains majority of phosphorylation sites (Figure 20B). Based on STRING analysis (Figure 20C), TTC9B interacts with 40 partners, and is located in the middle of a PPI network containing 149 edges and characterized by the average node degree of 7.27, average local clustering coefficient of 16 0.824, expected number of edges of 42, and PPI enrichment p-value of < 10− . Figure 21 shows functional disorder profiles and interaction network of human protein SMG7 (PPDR = 56.6 11.7%; ADS = 0.543 0.096). SMG7 is a 1137-residue-long protein that plays a role ± ± in the nonsense-mediated mRNA decay (NMD), a process by which aberrant mRNAs containing nonsense mutations and premature termination codons (PTCs) are degraded [126,127]. SMG7 recruits regulator of nonsense transcripts 1 (a.k.a. up-frame-shift suppressor 1 homolog, UPF1) to cytoplasmic mRNA decay bodies, where they interact with each other and SMG5 via their N-terminal domains to from a complex [127]. SMG7 contains two TRPs (residues 152–185 and 187–219 with the ADS values of 0.39 0.26 and 0.24 0.21), and Gln/Pro-rich and Ser-rich regions (residues 648–843 and ± ± 922–1015, respectively). In addition to the canonical form, SMG7 has several isoforms generated by alternative splicing. Residues 569-614 are missing in both isoform 2 and isoform 4. Also, in isoform 4, residue Glu914 is changed to the residue sequence EDPKSSPLLPPDLLKSLAALEEEEELIFSNPPD LYPALLGPLASLPGRSLF, and the 38-residue-long C-terminal region (residues 1101–1137) is Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 23 of 35

edges, and it is characterized by the average node degree of 6.65, average local clustering coefficient of 0.762, expected number of edges of 44, and PPI enrichment p-value of < 10−16. Figure 20 shows functional disorder profiles and interaction network of human tetratricopeptide repeat protein 9B (TTC9B; PPDR = 60.4 ± 15.0%; ADS = 0.590 ± 0.053). This 239-residue-long protein has a Pro-rich segment (residues 17–50) and contains two TPRs, residues 65–99 and 171–204 (ADS values of 0.63 ± 0.14 and 0.21 ± 0.16). TTV9B has an alternative splicing-generated isoform, in which the C-terminal region 143–239 is changed to a shorter sequence GTPSGGGGMGHEGRGQSGELGD LGAR GPGAEGSRAVGFSGSLQSLIKERD. Disorder is concentrated within the N-terminal half of this protein (see Figures 20A and 20B), which can be approximated as one long IDPR (residues 1– 140). Alternative splicing-induced changes in TTC9B sequence convert this protein to a completely Int. J. Mol. Sci. 2020, 21, 3709 24 of 35 disordered form characterized by PPDR = 93.0 ± 6.0% and ADS = 0.787 ± 0.010 (see Supplementary Figure S6). The first TPR of TTC9B overlaps with longest of three MoRFs found in this IDPR (residues 1-16, 52-98, and 140-146) and contains majority of phosphorylation sites (Figure 20B). Based on changed to a longer tail KQQHGVQQLGPKRQSEEEGSSSICVAHRGPRPLPSCSLPASTFRVKFKA STRING analysis (Figure 20C), TTC9B interacts with 40 partners, and is located in the middle of a PPI ARTCAHQAQKKTRRRPFWKRRKKGK. Isoform 5 is missing 42 N-terminal residues and has an E network containing 149 edges and characterized by the average node degree of 7.27, average local → EDPKSSPLLPPDclustering coefficient LLKSLAALEEEEELIFSNPPDLYPALLGPLASLPGRSLF of 0.824, expected number of edges of 42, and PPI enrichment p substitution-value of < 10− at16. position 914.

Int. J. Mol. Sci. 2020, 21, x FOR PEER REVIEW 24 of 35

FigureFigurechanged 20.20. FunctionalFunctional to a longer disorder disorder tail analysis KQQHGVQQLGPK analysis of human of human tetratricopeptideRQSEEEGSSSICVAHRGPRPLPSCSLPASTFRVKFKA tetratricopeptide repeat protein repeat 9B (TTC9B; protein UniProt 9B (TTC9B; UniProt ID:ID:ARTCAHQAQKKTRRRPFWKRRKKGK. Q8N6N2). Q8N6N2). (A (A) Intrinsic) Intrinsic disorder disorder profile profile generated Isoform generated by DiSpi 5 is by missingweb DiSpi crawler. 42 web N (B- crawler.terminal) Functional residues (B )disorder Functional and has disorder an E profileprofile→ EDPKSSPLLPPD generatedgenerated by by D D2P2 PLLKSLAALEEEEELIFSNPPDLYPALLGPLASLPGRSLFplatform.2 platform. (C) Interactability (C) Interactability of human of TTC9B human protein TTC9B analyzed protein substitution by analyzedSTRING at by position STRING usingusing914. thethe medium confidence confidence level level of 0.4 of. 0.4.

Figure 21 shows functional disorder profiles and interaction network of human protein SMG7 (PPDR = 56.6 ± 11.7%; ADS = 0.543 ± 0.096). SMG7 is a 1137-residue-long protein that plays a role in the nonsense-mediated mRNA decay (NMD), a process by which aberrant mRNAs containing nonsense mutations and premature termination codons (PTCs) are degraded [126,127]. SMG7 recruits regulator of nonsense transcripts 1 (a.k.a. up-frame-shift suppressor 1 homolog, UPF1) to cytoplasmic mRNA decay bodies, where they interact with each other and SMG5 via their N-terminal domains to from a complex [127]. SMG7 contains two TRPs (residues 152–185 and 187–219 with the ADS values of 0.39 ± 0.26 and 0.24 ± 0.21), and Gln/Pro-rich and Ser-rich regions (residues 648–843 and 922–1015, respectively). In addition to the canonical form, SMG7 has several isoforms generated by alternative splicing. Residues 569-614 are missing in both isoform 2 and isoform 4. Also, in isoform 4, residue Glu914 is changed to the residue sequence EDPKSSPLLPPDLLKSLAALEEEEELIFSNPPD LYPALLGPLASLPGRSLF, and the 38-residue-long C-terminal region (residues 1101–1137) is

Figure 21.FigureFunctional 21. Functional disorder disorder analysis analysis of of human human proteinprotein SMG7 SMG7 (UniProt (UniProt ID: ID:Q92540) Q92540).. (A) Intrinsic (A) Intrinsic disorderdisorder profile profile generated generated by DiSpi by DiSpi web web crawler. crawler. (B(B)) FunctionalFunctional disorder disorder profile profile generated generated by D2P by2 D2P2 platform. (C) Interactability of human SMG7 protein analyzed by STRING using the high confidence platform. (C) Interactability of human SMG7 protein analyzed by STRING using the high confidence level of 0.7. level of 0.7. Although X-ray crystal structure is available for the N-terminal domain of SMG7 (residues 1– Although497; PDB X-ray ID: 1YA0 crystal [126] structure), Figure 21A is, availableB show that for C-terminal the N-terminal half of this domain protein ofis highly SMG7 disordered. (residues 1–497; PDB ID:All 1YA0 sequence [126]), changes Figure introduced21A,B show by that the alternativC-terminale splicing half of take this place protein within is highly this long disordered. IDPR. All Supplementary Figure S7 shows how alternative splicing affects disorder predisposition of human SNG7. Figure 21B indicates that the highly disordered C-terminal IDPR of this protein contains multiple sites of different PTMs (phosphorylation, methylation, acetylation, and ubiquitylation) and includes 16 MoRFs, suggesting that SNG7 can exhibit high binding promiscuity. This hypothesis is supported by Figure 21C representing STRING-generated PPI network centered at SNG7. This protein can interact with 120 partners, and its network includes 6379 edges and characterized by an average node degree of 106, average local clustering coefficient of 0.988, expected number of edges of 835, and PPI enrichment p-value of < 10−16. Results of functional disorder analysis of human FK506-binding protein-like (FKBPL; PPDR = 53.9 ± 14.6%; ADS = 0.525 ± 0.088) are summarized in Figure 22. FKBPL, also known as WAF-1/CIP1 stabilizing protein 39 (WISp39) is 349-residue-long protein involved in regulation of the stability of p21WAF1/CIP1 protein, which is a cyclin-dependent kinase inhibitor and a critical regulator of cell cycle, via interaction with Hsp90 and p21WAF1/CIP1 [128]. FKBPL contains FKPD-like domain (residues 95– 181), and three TPRs (residues 210–243, 252–285, and 286–316; the corresponding ADS values of 0.65 ± 0.15, 0.45 ± 0.13, and 0.41 ± 0.12). This protein contains high levels of intrinsic disorder, with the N-

Int. J. Mol. Sci. 2020, 21, 3709 25 of 35 sequence changes introduced by the alternative splicing take place within this long IDPR. Supplementary Figure S7 shows how alternative splicing affects disorder predisposition of human SNG7. Figure 21B indicates that the highly disordered C-terminal IDPR of this protein contains multiple sites of different PTMs (phosphorylation, methylation, acetylation, and ubiquitylation) and includes 16 MoRFs, suggesting that SNG7 can exhibit high binding promiscuity. This hypothesis is supported by Figure 21C representing STRING-generated PPI network centered at SNG7. This protein can interact with 120 partners, and its network includes 6379 edges and characterized by an average node degree of 106, average local clustering coefficient of 0.988, expected number of edges of 835, and PPI enrichment 16 p-value of < 10− . Results of functional disorder analysis of human FK506-binding protein-like (FKBPL; PPDR = 53.9 14.6%; ADS = 0.525 0.088) are summarized in Figure 22. FKBPL, also known as WAF-1/CIP1 ± ± stabilizing protein 39 (WISp39) is 349-residue-long protein involved in regulation of the stability of p21WAF1/CIP1 protein, which is a cyclin-dependent kinase inhibitor and a critical regulator of cell cycle, via interaction with Hsp90 and p21WAF1/CIP1 [128]. FKBPL contains FKPD-like domain (residues 95–181), and three TPRs (residues 210–243, 252–285, and 286–316; the corresponding ADS values of 0.65Int. J. 0.15,Mol. Sci. 0.45 2020, 210.13,, x FORand PEER0.41 REVIEW0.12). This protein contains high levels of intrinsic25 disorder, of 35 with the ± ± ± N-terminalterminal region region (residues (residues 1–95) 1–95) predicted predicted to be completely to be completely disordered disordered by all predictors by all utilized predictors in utilized in thisthis study, study, while while thethe C C-terminal-terminal region region (residues (residues 152-349) 152-349) is mostly is mostlydisordered disordered (Figure 22A (Figure,B). 22A,B).

FigureFigure 22. 22. FunctionalFunctional disorder disorder analysis analysis of human of human FK506- FK506-bindingbinding protein-like protein-like (FKBPL; UniProt (FKBPL; ID: UniProt ID: Q9UIM3).Q9UIM3).( A(A)) IntrinsicIntrinsic disorder profile profile generated generated by byDiSpi DiSpi web web crawler. crawler. (B) Functional (B) Functional disorder disorder profile generatedprofile generated by D2P by2 platform. D2P2 platform. (C) ( InteractabilityC) Interactability ofof human FKBPL FKBPL protein protein analyzed analyzed by STRING by STRING using theusing medium the medium confidence confidence level level of 0.4.of 0.4.

Curiously,Curiously, thethe FKPD FKPD-like-like domain domain constitutes constitutes the most the ordered most ordered part of this part protein, of this whereas protein, all whereas all three TPRs are located within the mostly disordered C-terminal domain. Figure 22B shows that there three TPRs are located within the mostly disordered C-terminal domain. Figure 22B shows that there are 9 MoRFs in this protein, suggesting high interactability. In line with this indication, Figure 22C arerepresents 9 MoRFs STRING in this- protein,generated suggesting PPI network high centered interactability. at FKBPL and In shows line with that this this indication,protein can Figure 22C representsinteract with STRING-generated 42 partners. This PPI PPI network network includes centered 120 atedges FKBPL and andis characterized shows that by this an average protein can interact withnode 42 degree partners. of 5.71, This average PPI network local clustering includes coefficient 120 edges of 0.787, and expected is characterized number of byedges an of average 63, and node degree of 5.71,PPI enrichment average local p-value clustering of < 10−16.coe ﬃcient of 0.787, expected number of edges of 63, and PPI enrichment Figure 23 reports16 results of the functional disorder analysis of human kinesin light chain 3 p-value of < 10− . (KLC3; PPDR = 57.2 ± 11.4%; ADS = 0.547 ± 0.070). Kinesin is an oligomer composed of two heavy Figure 23 reports results of the functional disorder analysis of human kinesin light chain 3 (KLC3; chains and two light chains that associates with microtubulin in an ATP-dependent manner and PPDR = 57.2 11.4%; ADS = 0.547 0.070). Kinesin is an oligomer composed of two heavy chains serves as a force± -producing microtubule± -associated protein that may be responsible for organelle andtransport. two light The chains 504-residue that- associateslong KLC3 withcontains microtubulin a Rab5-binding in andomain ATP-dependent (residues 79–248) manner and five and serves as a force-producingTPRs (residues 207 microtubule-associated–240, 249–282, 291–324, 333 protein–366, and that 375 may–408; be the responsible corresponding for ADS organelle values transport.of The 0.30 ± 0.15, 0.25 ± 0.20, 0.44 ± 0.12, 0.25 ± 0.11, and 0.34 ± 0.09). In the N-terminal half of this protein, there is a coiled-coil domain (residues 90–150), as well as Poly-Glu and Poly-Ala regions with compositional bias (residues 181–184 and 190–196, respectively). Figures 23A and 23B show that 200 N-terminal residues and 118 C-terminal residues (387–504) are predicted to be mostly disordered, and most of the Rab5-binding domain is immerged within the long N-terminal IDPR. Central TPR-containing domain is characterized by the “wavy” disorder profile, possessing several short IDPRs connecting more ordered regions that mostly correspond to TPRs. Both disordered tails of KLC3 have multiple MoRFs and phosphorylation sites (see Figure 23B). In addition to the canonical form, KLC3 has an alternatively spliced isoform with the methionine at position 1 substituted to MIPQTPHHCSPGAAM.

Int. J. Mol. Sci. 2020, 21, 3709 26 of 35

504-residue-long KLC3 contains a Rab5-binding domain (residues 79–248) and ﬁve TPRs (residues 207–240, 249–282, 291–324, 333–366, and 375–408; the corresponding ADS values of 0.30 0.15, 0.25 ± 0.20, 0.44 0.12, 0.25 0.11, and 0.34 0.09). In the N-terminal half of this protein, there is a ± ± ± ± coiled-coil domain (residues 90–150), as well as Poly-Glu and Poly-Ala regions with compositional bias (residues 181–184 and 190–196, respectively). Figure 23A,B show that 200 N-terminal residues and 118 C-terminal residues (387–504) are predicted to be mostly disordered, and most of the Rab5-binding domainInt. J. Mol. is Sci. immerged 2020, 21, x FOR within PEER REVIEW the long N-terminal IDPR. 26 of 35

FigureFigure 23.23. Functional disorder disorder analysis analysis of human of human kinesin kinesin light chain light 3 chain (KLC3; 3 (KLC3;UniProt ID: UniProt Q6P597) ID:. Q6P597). (A) Intrinsic(A) Intrinsic disorder disorder profile profile generated generated by byDiSpi DiSpi web web crawler. crawler. (B ()B Functional) Functional disorder disorder profile profile generated by 2 2 Dgenerated2P2 platform. by D (PC )platform. Interactability (C) Interactability of human KLC3of human analyzed KLC3 analyzed by STRING by STRING using the using medium the confidence medium confidence level of 0.4. level of 0.4. This addition extends the N-terminal IDPR by 14 residues and extends N-terminal MoRF from 6 toCentral 25 residues. TPR-containing Based on the STRING domain analysis, is characterized KLC3 interacts by with the 165 “wavy” proteins, disorder and is located profile, at possessing severalthe center short of IDPRsa dense connecting PPI network more (see Figure ordered 23C). regions This PPI that network mostly includes correspond 5,380to edges TPRs. and Both is disordered tailscharacterized of KLC3 have by the multiple average node MoRFs degree and of phosphorylation 64.8, average local sites clustering (see Figure coefficient 23B). of In 0.875, addition to the canonicalexpected form,number KLC3 of edges has of an 456, alternatively and PPI enrichment spliced p isoform-value of with< 10−16 the. methionine at position 1 substituted to MIPQTPHHCSPGAAM. 3. Materials and Methods This addition extends the N-terminal IDPR by 14 residues and extends N-terminal MoRF from 6 to3.1. 25 Datasets residues. Based on the STRING analysis, KLC3 interacts with 165 proteins, and is located at the centerOn 1 of October a dense 2019, PPI network all human (see TPR Figure repeat 23C).-containing This PPI proteins network listed includes in UniProt 5,380 edges and is characterized(https://www.uniprot.org/ by the average) were node identified degree using of 64.8, the average search criteria: local clusteringtetratricopeptide coe ffi repeatcient protein of 0.875, expected 16 numberannotation:(type:repeat of edges of 456, tpr) AND and PPIreviewed:yes enrichment AND organism:p-value” ofHomo< 10 sapiens− . (Human) 9606”. This search yielded 166 different human proteins, which were used to perform computational analysis for 3.abundance Materials of and intrinsic Methods disorder. Sequences of these proteins in FASTA format and some functional information was extracted from UniProt [129]. UniProt IDs and some related information of the 3.1.analyzed Datasets proteins are shown in the Supplementary Materials. The available protein structures were obtained from the Protein Data Bank (PDB; https://www.rcsb.org/) [130]. On 1 October 2019, all human TPR repeat-containing proteins listed in UniProt (https://www. uniprot.org3.2. Computational/) were Characterization identified using of Intrinsic the search Disorder criteria: in Humantetratricopeptide TPR Proteins repeat protein annotation:(type:repeat tpr) ANDInitially, reviewed:yes human TPR AND proteins organism:”Homo were analyzed sapiens by five (Human) per-residue [9606]” predictors,. This such search as PONDR yielded® 166 different humanVLXT proteins,[131], PONDR which® VSL2 were [132] used, and to perform PONDR® computationalVL3 [132] available analysis on the for PONDR abundance site of intrinsic disorder.(http://www.pondr.com Sequences of these), and the proteins IUPred in computational FASTA format platform and somethat allows functional identification information of either was extracted fromshort UniProt or long [ regions129]. UniProt of intrinsic IDs disorder, and some IUPred related-L and information IUPred-S [133] of the. We analyzed utilized DiSp proteinsi web are shown in crawler that was designed for the rapid prediction and comparison of protein disorder profiles. It the Supplementary Materials. The available protein structures were obtained from the Protein Data aggregates the results from a number of well-known disorder predictors: PONDR® VLXT [131], BankPONDR (PDB;® VL3 https: [134]//,www.rcsb.org PONDR® VLS2B/)[ [132]130,]. PONDR® FIT [89], IUPred2 (Short) and IUPred2 (Long) [133,135]. The outputs of the evaluation of the per-residue disorder propensity by these tools are represented as real numbers between 1 (ideal prediction of disorder) and 0 (ideal prediction of order).

Int. J. Mol. Sci. 2020, 21, 3709 27 of 35

3.2. Computational Characterization of Intrinsic Disorder in Human TPR Proteins Initially, human TPR proteins were analyzed by five per-residue predictors, such as PONDR® VLXT [131], PONDR® VSL2 [132], and PONDR® VL3 [132] available on the PONDR site (http: //www.pondr.com), and the IUPred computational platform that allows identification of either short or long regions of intrinsic disorder, IUPred-L and IUPred-S [133]. We utilized DiSpi web crawler that was designed for the rapid prediction and comparison of protein disorder profiles. It aggregates the results from a number of well-known disorder predictors: PONDR® VLXT [131], PONDR® VL3 [134], PONDR® VLS2B [132], PONDR® FIT [89], IUPred2 (Short) and IUPred2 (Long) [133,135]. The outputs of the evaluation of the per-residue disorder propensity by these tools are represented as real numbers between 1 (ideal prediction of disorder) and 0 (ideal prediction of order). A threshold of 0.5 was ≥ used to identify disordered residues and regions in query proteins. For each query protein in this study, the predicted percentage of intrinsic disorder (PPID) was calculated based on the outputs of per-residue disorder predictors. Here, PPID in a query protein represents a percent of residues with disorder scores exceeding 0.5. Next, the outputs of two binary predictors, the charge-hydropathy (CH) plot [4,14] and the cumulative distribution function (CDF) plot [14,90,136] were combined to conduct a CH-CDF analysis [90–93] that allows classification of proteins based on their position within the CH-CDF phase space as ordered (proteins predicted to be ordered by both binary predictors), putative native “molten globules” or hybrid proteins (proteins determined to be ordered/compact by CH, but disordered by CDF), putative native coils and native pre-molten globules (proteins predicted to be disordered by both methods), and proteins predicted to be disordered by CH-plot, but ordered by CDF. Complementary disorder evaluations together with important disorder-related functional information were retrieved from the D2P2 database (http://d2p2.pro/)[137], which is a database of predicted disorder for a large library of proteins from completely sequenced genomes [137]. D2P2 database uses outputs of IUPred [133], PONDR® VLXT [131], PrDOS [138], PONDR® VSL2B [134,139], PV2 [137], and ESpritz [140]. The visual console of D2P2 displays 9 colored bars representing the location of disordered regions as predicted by these different disorder predictors. In the middle of the D2P2 plots, the blue-green-white bar shows the predicted disorder agreement between nine disorder predictors (IUPred, PONDR® VLXT, PONDR® VSL2, PrDOS, PV2, and ESpritz), with blue and green parts corresponding to disordered regions by consensus. Above the disorder consensus bar are two lines with colored and numbered bars that show the positions of the predicted (mostly structured) SCOP domains [141,142] using the SUPERFAMILY predictor [143]. Yellow zigzagged bar shows the location of the predicted disorder-based binding sites (MoRF regions) identified by the ANCHOR algorithm [144], whereas differently colored circles at the bottom of the plot show location of various PTMs assigned using the outputs of the PhosphoSitePlus platform [145], which is a comprehensive resource of the experimentally determined post-translational modifications.

3.3. Computational Evaluation of Interactability of the Human TPR Proteins Information on the interactability of human TPR proteins was retrieved using Search Tool for the Retrieval of Interacting Genes; STRING, http://string-db.org/. STRING generates a network of protein-protein interactions based on predicted and experimentally-validated information on the interaction partners of a protein of interest [124]. In the corresponding network, the nodes correspond to proteins, whereas the edges show predicted or known functional associations. Seven types of evidence are used to build the corresponding network, where they are indicated by the diﬀerently colored lines: a green line represents neighborhood evidence; a red line – the presence of fusion evidence; a purple line – experimental evidence; a blue line – co-occurrence evidence; a light blue line – database evidence; a yellow line – text mining evidence; and a black line – co-expression evidence [124]. In this study, STRING was utilized in three diﬀerent modes: to generate the inter-TPR network PPI interactions, to produce the TRP set-centered PPI network, and to create PPI networks centered at individual human TPR protein. Protein interaction networks were obtained from STRING (https: Int. J. Mol. Sci. 2020, 21, 3709 28 of 35

//string-db.org/) for each protein using a custom value of 500 maximum first-shell interactions at medium, high, and highest confidence levels (minimum required interaction score of 0.4, 0.7, and 0.9 respectively). Resulting PPI networks were further analyzed using STRING-embedded routines in order to retrieve the network-related statistics, such as: the number of nodes (proteins); the number of edges (interactions); average node degree (average number of interactions per protein); average local clustering coefficient (which defines how close the neighbors are to being a complete clique – if a local clustering coefficient is equal to 1, then every neighbor connected to a given node Ni is also connected to every other node within the neighborhood, and if it is equal to 0, then no node that is connected to a given node Ni connects to any other node that is connected to Ni); expected number of edges (which is a number of interactions among the proteins in a random set of proteins of similar size); and a PPI enrichment p-value (which is a reflection of the fact that query proteins in the analyzed PPI network have more interactions among themselves than what would be expected for a random set of proteins of similar size, drawn from the genome. It was pointed out that such an enrichment indicates that the proteins are at least partially biologically connected, as a group).

4. Conclusions This article summarizes the results of comprehensive bioinformatics and computational analysis of the intrinsic disorder predisposition of human proteins possessing Tetratricopeptide Repeats (TPRs). This analysis revealed that human TPR proteins, ranging in length from 151 to 4471 residues, contain variable levels of intrinsic disorder (1.9% to 74.9%), with disordered residues assembled into functionally important IDPRs. Disorder in these proteins is used for protein-protein interactions and serves as a signal for a variety of posttranslational modifications. Results of our analysis add a new perspective for better understanding of the functionality of TPR proteins, many of which have high disorder content. They are characterized by the presence of multiple PTM sites, disorder-based protein interaction sites that can undergo binding induced folding at interaction with specific partners, and numerous isoforms generated by alternative splicing. These features (intrinsic disorder, capability to undergo disorder-to-order transitions, PTMs, and alternative splicing) are known to serve as a basis of the proteoform concept, where proteoforms constitute a set of structurally and functionally distinct protein molecules encoded by a single gene [146,147]. They are also a cornerstone of the “protein structure-function continuum” model, where any protein represents a dynamic conformational ensemble, and where multiple proteoforms have different structural features with various functions [146,148,149]. Such disorder-based structural and functional heterogeneity of human TPR proteins can be used to better understanding of the engagement of these proteins in the pathogenesis of various human diseases. This is also in agreement with the observation that IDPs or hybrid proteins containing ordered domains and functional IDPRs are common among disease-associated proteins [45,46]. This is because multi-level harm can be induced by the deregulation, misfolding, misidentification, mis-interactions, and mis-signaling of IDPs/IDPRs, which are commonly found in various proteomes and are involved in recognition, regulation, and cell signaling [45,52,150–153].

Supplementary Materials: The following are available online at http://www.mdpi.com/1422-0067/21/10/3709/s1. Figure S1. STRING-generated TPR internal PPI network generated with medium confidence level of 0.4. Figure S2. STRING-generated TPR internal PPI network generated with high confidence of 0.7. Figure S3. STRING-generated PPI network of 161 human TPR proteins with included first shell interactors using the low confidence level of 0.15. This dense network of 661 proteins connected by 35,582 interactions with the average node degree of 108, average local clustering coefficient of 0.464, expected number of edges of 23,094, and PPI enrichment p-value of < 16 10− . Figure S4. Intrinsic disorder analysis of alternatively spliced isoforms of human NASP. Figure S5. Intrinsic disorder analysis of alternatively spliced isoforms of human TTC31. Figure S6. Intrinsic disorder analysis of alternatively spliced isoforms of human TTC9B. Figure S7. Intrinsic disorder analysis of alternatively spliced isoforms of human SNG7. Int. J. Mol. Sci. 2020, 21, 3709 29 of 35

Author Contributions: N.W.V.B., C.H., and R.K. – conducted research, collected and analyzed literature data and helped with the manuscript preparation; B.X. – conducted research and helped with the manuscript preparation; V.N.U. – conceived the idea, collected and analyzed literature data, conducted research, and wrote the manuscript. All authors have read and agreed to the published version of the manuscript. Acknowledgments: We would like to thank Guy Dayhoff for the development of the DiSpi web crawler. Conflicts of Interest: The authors declare no conflict of interest.

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