Available online at www.sciencedirect.com
ScienceDirect
Relating sequence encoded information to form
and function of intrinsically disordered proteins
Rahul K Das, Kiersten M Ruff and Rohit V Pappu
Intrinsically disordered proteins (IDPs) showcase the of archetypal IDPs. CCRs enable the assignments of
importance of conformational plasticity and heterogeneity in conformational descriptors and inferences regarding the
protein function. We summarize recent advances that connect amplitudes of conformational fluctuations of IDPs. These
information encoded in IDP sequences to their conformational insights are relevant because amino acid compositions are
properties and functions. We focus on insights obtained often well conserved among orthologs of IDPs even if their
through a combination of atomistic simulations and biophysical sequences are poorly conserved [42,43].
measurements that are synthesized into a coherent framework
using polymer physics theories.
Compositional classes of IDPs
Address Amino acid compositions of IDPs are characterized by
Department of Biomedical Engineering and Center for Biological distinct biases [5]. They are deficient in canonical hydro-
Systems Engineering, Washington University in St. Louis, One Brookings phobic residues and enriched in polar and charged resi-
Drive, Campus Box 1097, St. Louis, MO 63130, USA
dues. Accordingly, IDPs fall into three distinct
compositional classes that reflect the fraction of charged
Corresponding author: Pappu, Rohit V ([email protected])
versus polar residues. The distinct classes are polar tracts,
polyampholytes, and polyelectrolytes [41] (see Figure 1). Polar
Current Opinion in Structural Biology 2015, 32:102–112 tracts are deficient in charged, hydrophobic, and proline
residues. They are enriched in polar amino acids such as
This review comes from a themed issue on Sequences and topology
Asn, Gly, Gln, His, Ser, and Thr. Polyampholytes and
Edited by M Madan Babu and Anna R Panchenko
polyelectrolytes can either be weak or strong depending
For a complete overview see the Issue and the Editorial
on the fraction of charged residues (FCR) that is quanti-
Available online 2nd April 2015 fied as the sum of f+ and f (see Figure 2). The latter two
http://dx.doi.org/10.1016/j.sbi.2015.03.008 parameters quantify the fraction of positive and negative-
ly charged residues in an IDP sequence. Polyelectrolytes
0959-440X/# 2015 Elsevier Ltd. All rights reserved.
have an excess of one type of charge, that is, f+ > f or vice
versa. Polyampholytes have roughly equivalent fractions
of opposite charges, that is, f+ f . The designation of
weak versus strong polyampholytes/polyelectrolytes is
governed by the value of FCR. In strong polyampho-
Introduction lytes/polyelectrolytes, the high FCR values encode an
intrinsic tendency for populating expanded coil-like con-
Protein domains are modular building blocks of macro-
formations because charged residues prefer to be solvated
molecular complexes and interaction networks [1]. The
in aqueous milieus.
concept of domains can be generalized to include se-
quence regions that fail to fold as autonomous units [2].
These intrinsically disordered regions/proteins, referred A formal language for describing
to collectively hereafter as IDPs, are distinct from struc- conformational preferences of IDPs
tured domains. Their sequences encode an intrinsic Ensembles of conformations as opposed to singular rep-
inability to fold into singular well-defined three-dimen- resentative structures are appropriate for describing IDPs.
sional structures [3 ,4 ,5–7] although some IDPs do fold The balance between solvent-mediated intra-chain
into well-ordered structures in the context of functional attractions versus repulsions determines the types of con-
complexes. IDPs are implicated in important cellular formations that make up the ensemble that is thermody-
processes that include cell division [8,9 ], cell signaling namically accessible to an IDP sequence. When attractions
[3 ,10], intracellular transport [11,12 ], bacterial translo- dominate, the conformations in the ensemble are, on aver-
cation [13 ], cell mechanics [14 ,15], protein degradation age, compact and spherical, that is, globular. Conversely, if
[16,17], posttranscriptional regulation [18], and cell cycle intra-chain repulsions dominate over attractions or, stated
control [19]. differently, chain solvation is preferred over desolvation,
then the conformations are, on average, expanded, prolate
IDPs can be classified into distinct conformational classes ellipsoidal, and coil-like. An intermediate scenario results if
based on their amino acid compositions [20–41]. We the strengths of intra-chain solvent mediated repulsions
summarize recent results that have identified composi- are counterbalanced by equivalent attractive interactions.
tion-to-conformation relationships (CCRs) through studies Under such circumstances, the ensembles are characterized
Current Opinion in Structural Biology 2015, 32:102–112 www.sciencedirect.com
Encoding form and function of IDPs Das, Ruff and Pappu 103
Figure 1
PolyQ: …QQQQQQQQQ…QQQQQQQQQQ … … … …
Sup35: …SNQGNNQQNYQQ YSQNGNQQ… … …
POLAR TRACTS
EcSSB: …QGGGAPA GGNIGGGQPQGGW… … …
Nup42: …TSPF GSLQQNASQNASSTSS… … …
WEAK
Nup60: …NAYKSENAPSA SSKEFNFTN… … …
PfSSB: …FM PLNSNDKIIEDKEFTDRL… … …
POLYAMPHOLYTES Nsp1: …AF SFGAKSDEKKDGDASKPA… … … PQBP1: …YDKVDRERERDRERDRDRG Y… … … STRONG
WEAK
PRM2: …ACYPVNIRARGLGKNMGMKS… … …
… …
POLYELECTROLYTES PDE6G: …DITVICPWEAFNHLELHELA…
NP1: …RARSRGRSV RRRRRGRSPGR… … …
RAG2: …SFDG DDEFDTYNEDDEDDES… … …
STRONG
Hydrophobic Polar Proline Positive Negative
Current Opinion in Structural Biology
Definitions of polar tracts, polyelectrolytes, and polyampholytes. Polar tracts shown here include polyQ (UniProt ID: P42858): Polyglutamine tracts
are found in at least ten proteins associated with human neurodegenerative disorders including Huntington’s disease; Sup35 (UniProt ID: P05453):
Residues 4–23 of S. cerevisiae Sup35 corresponding to a region of the N-terminal prion domain; EcSSB (UniProt ID: P0AGE0): Residues 117–136
of E. coli single stranded DNA binding protein corresponding to a region of the C-terminal tail; Nup42 (UniProt ID: P49686): Residues 181–200 of
S. cerevisiae nucleoporin Nup42 corresponding to a region of the FG domain, which modulates gating of the nuclear pore complex.
Polyampholytes shown here include: Nup60 (UniProt ID: P39705): Residues 412–431 of S. cerevisiae nucleoporin Nup60 corresponding to a region
of the FG domain which modulates gating of the nuclear pore complex; PfSSB (UniProt ID: Q8I415): Residues 232–251 of P. falciparum single
stranded DNA binding protein corresponding to a region of the C-terminal tail; Nsp1 (UniProt ID: P14907): Residues 359–378 of S. cerevisiae
nucleoporin Nsp1 corresponding to a region of the FG domain which modulates gating of the nuclear pore complex; PQBP1 (UniProt ID: O60828):
Residues 146–165 of H. sapiens polyglutamine-tract binding protein 1 corresponding to a region of the expanded linker, which connects the
N-terminal WW domain and the C-terminal U5 15 kDa binding region. Polyelectrolytes shown here include: PRM2 (UniProt ID: Q9EP54): Residues
2–21 of the C. griseus DNA packaging protein protamine 2, which is involved in the chromatin condensation process during spermatogenesis [6];
0 0
PDE6G (UniProt ID: P18545): Residues 63–82 of H. sapiens retinal rod rhodopsin-sensitive cGMP 3 ,5 -cyclic phosphodiesterase subunit gamma
protein, which is involved in processing visual signal; NP1 (UniProt ID: O13030): Residues 5–24 of C. pyrrhogaster protamine 1 which is involved in
the chromatin condensation process during spermatogenesis; RAG2 (UniProt ID: P21784): Residues 392–411 of C. griseus V(D)J recombination-
activating protein 2 corresponding to a region of the ‘acidic hinge’ which modulates DNA repair mechanisms.
by maximal conformational heterogeneity and compact, also classify the sequence-specific conformational prop-
semi-compact, expanded, and chimeric conformations be- erties by quantifying the amplitudes of conformational
come thermodynamically accessible [41]. Typical hetero- fluctuations [39]. All of these classifiers and descriptors
polymeric IDP sequences can sample conformations that rely on comparisons of measured or calculated values of
are chimeras of globules, coils, rods, and semi-compact conformational fluctuations to expectations from analyti-
hairpins. The preference is governed by the region-specific cal theories for flexible polymers in different types of
amino acid compositions along the linear sequence. solvents. Figure 3 summarizes the typical workflow that
leads from analysis of results from computer simulations
Polymer physics theories provide access to formal or in vitro experiments to quantitative inferences regard-
descriptors of conformational ensembles for heteroge- ing CCRs and/or sequence-to-conformation relationships
neous systems such as IDPs and these have been (SCRs).
reviewed recently [41,44]. Analytical relationships predict
the scaling of parameters such as radii of gyration, mean Distinct compositional classes can be
end-to-end distances, and hydrodynamic radii as func- mapped to distinct conformational classes
tions of chain length, amino acid composition, and intrin- Results from atomistic simulations obtained using explic-
sic stiffness. Analytical relations are also available to relate it representations of solvent molecules [45,46] and studies
the scaling of inter-residue distances to the linear se- based on fluorescence correlation spectroscopy [46,47]
quence separation between residues [41]. Finally, one can have shown that polyglycine chains, that is, polypeptide
www.sciencedirect.com Current Opinion in Structural Biology 2015, 32:102–112
104 Sequences and Topology
Figure 2
Charged sidechains can modulate the intrinsic tendency
of polypeptide backbones to form collapsed globules.
N: Number of residues in the sequence Essentially, the sidechains act as modulators of solvent
N+ , N− : Number of positive, negatively charged residues quality thus altering the sign and magnitude of the
N+ N− effective inter-residue interaction coefficient. As the
f+ = , f− =
N N FCR crosses a threshold value, the favorable solvation
FCR = ( f+ + f−) of charged sidechains combined with electrostatic repul-
NCPR = ( f+ − f−) sions in polyelectrolytes and/or the screening of electro-
2 static repulsions by attractions in certain categories of
( f+ − f )
Charge asymmetry σ = polyampholytes will result in a preference for either
( f+ + f−)
expanded conformations. Sequences with jNCPRj and
Current Opinion in Structural Biology
FCR values larger than a threshold value of 0.25 prefer
expanded coil-like structures [21 ,22,36,38 ,40]. These
Summary of readily calculated compositional parameters that help in
inferences have been obtained from a combination of
quantitative assessments of CCRs for IDP sequences.
atomistic simulations based on the ABSINTH implicit
solvation model and forcefield paradigm [24,54,55], fluo-
rescence correlation spectroscopy [40,47,51], time-resolved
backbones sans sidechains, form collapsed globules in
fluorescence measurements [53], single molecule Fo¨rster
aqueous solvents. Dipole–dipole interactions are favored
resonance energy transfer experiments [20–24], single
over the solvation of dipoles and this gives rise to the
molecule force spectroscopy [44], pulse field gradient
observed preference for globules [48]. In the language of
nuclear magnetic resonance experiments [36], measure-
polymer physics, the effective inter-residue interaction
ments of paramagnetic relaxation enhancements [56], and
coefficient quantifies the energetic balance of chain–
small-angle X-ray scattering measurements [57].
chain and chain–solvent interactions. For homopolymers,
this coefficient is negative in a poor solvent, zero in an
indifferent solvent, and positive in a good solvent [49,50]. Diagram-of-states summarizing composition-
The overall implication of the poor solubility and prefer- to-conformation relationships
ence of polypeptide backbones for globules is that water A diagram-of-states summarizes our current understand-
is a poor solvent for polypeptide backbones. The intrinsic ing of CCRs for IDPs. This diagram is shown in
preference of polypeptide backbones for globules and Figure 4. It depicts four distinct conformational classes
poor solubility in aqueous solvents is retained for other designated as R1, R2, R3, and R4, respectively. Polar
polyamides such as polyglutamine [51,52] and polar tracts tracts and weak polyampholytes/polyelectrolytes are
such as glycine-serine copolypeptides [45], and globule formers that make up region R1. Strong poly-
sequences that are enriched in Gln/Asn [53]. Collapsed ampholytes belong to region R3 and these form either
globules are also preferred for sequences for which coils or hairpins depending on the combination of FCR
FCR < 0.25 and the magnitude of net charge per residue values and charge patterning (see below). Sequences from
(NCPR, see Figure 3), is less than 0.25 [21 ,38 ,40]. region R2 have intermediate compositional biases and
Figure 3
PRIMARY GENERATION OF ANALYSIS OF GENERATION OF CCRs SEQUENCE ENSEMBLE ENSEMBLE AND / OR SCRs
Atomistic simulations Analyze ensemble Extract quantitative IDP sequence of using implicit or using the lens of rules regarding CCRs interest explicit representations polymer physics Rules and / or SCRs Theory of solvent and ions theories Simulations
In vitro spectroscopic and other biophysical measurements Experiments
Current Opinion in Structural Biology
Summary of the typical workflow used to extract quantitative CCRs and SCRs from computer simulations, in vitro biophysical experiments, or
synergy between the two modes of investigation.
Current Opinion in Structural Biology 2015, 32:102–112 www.sciencedirect.com
Encoding form and function of IDPs Das, Ruff and Pappu 105
Figure 4
R1 (25%): Globules, FCR < 0.25 & NCPR < 0.25
R2 (40%): Chimeras of globules & coils, 0.25 ≤ FCR ≤ 0.35 & NCPR ≤ 0.35
R3 (30%): Polyampholytic coils or hairpins, FCR > 0.35 & NCPR ≤ 0.35
R4 (5%): Polyelectrolytic semi-flexible rods or coils, FCR > 0.35 & NCPR > 0.35 1.0
0.8 R4 0.6 − f 0.4 R3
0.2 R2 R4 R1 0 0 0.2 0.4 0.6 0.8 1.0 f+
Current Opinion in Structural Biology
Diagram-of-states classification depicting the distinct conformational classes for IDP sequences. Statistics for different regions (percentages) are
from analysis of bona fide IDPs in DISPROT [61].
their conformations are likely to be chimeras of globules certain length range and proline contents that fall below
and coils. IDPs that undergo folding upon binding pre- a reasonably low threshold.
dominantly populate region R2. This highlights the role
played by context dependent interactions as determi- Statistics for different regions of the diagram-
nants of conformational transitions for sequences drawn of-states
from R2 [58]. It is worth emphasizing that the boundary The DISPROT database is an inventory of bona fide IDP
between R1 and R2 is rather ad hoc. The placement of this sequences [61]. Analysis of the compositional biases of
boundary reflects the limited ‘titration’ of CCRs for sequences from this database reveals that at least 70% of
sequences drawn from these two regions. Region R4 known IDP sequences belong to regions R2 and R3.
spans two areas, one each for acid versus base rich poly- These sequences are symmetric polyampholytes
electrolytes, respectively. For these sequences, the com- ( f+ f ), asymmetric polyampholytes ( f+ 6¼ f ), or weak
bination of electrostatic repulsions between charged polyelectrolytes. Based on their compositional biases,
sidechains and the favorable solvation free energies of sequences corresponding to regions R2 and R3 are
these sidechains gives rise to semi-flexible worm-like expected to adopt coil-like conformations, semi-compact
conformations. hairpins, or conformations that are chimeras of coils and
globules or coils and semi-compact hairpins. In addition,
The diagram-of-states classification shown in Figure 4 is their ensembles are expected to display significant con-
valid for IDP sequences that have at least thirty residues, formational heterogeneity [39] as characterized by spon-
low overall hydropathy, and low proline contents. The taneous conformational fluctuations whose amplitudes
physical principles underlying the conformational prop- are likely to be considerably larger than those of globular
erties of weak polyampholytes and polyelectrolytes sug- proteins. Regions R1, R2, and R3 together encompass at
gest that the conformational transitions are likely to be least 95% of the known sequences of IDPs.
continuous functions of FCR and NCPR [59,60]. If this
expectation is borne out for longer sequences with low Connecting CCRs to function
FCR and NCPR values or sequences with equivalent We present highlights from a growing body of data to
fractions of charged and polar residues, then the compo- demonstrate the functional implications of CCRs. The
sition range spanned by R2 will be larger than what is overall theme presented in this discussion is summa-
shown in Figure 4. Unpublished results suggest that the rized in Figure 5. Long disordered linkers that belong
classification of CCRs derived from the diagram-of-states, either to the R2 or R3 region of the diagram-of-states can
particularly the assignment of a sequence to region R1 or help localize proteins to the junction between the
R2, might only be valid for IDP sequences within a endoplasmic reticulum and plasma membrane [62].
www.sciencedirect.com Current Opinion in Structural Biology 2015, 32:102–112
106 Sequences and Topology
Figure 5
Connecting CCRs to Function Representative Sequence 1 Composition Function Conformation
…SKYFVEANWL WT KGSALQTSSA… Function
Wild-type (WT) WT: FCR & NCPR
Representative Sequence 2 Composition Function Conformation
WT …GTASWRAQNG Function
Class ETKYLSSTNA… Conserved Conserve
Compositional Similar FCR & NCPR
Representative Sequence 3 Composition Function Conformation
WT … EETADSLCET Function Alter Class ITEYDLSAKE… Modified
Compositional Alter FCR & NCPR
Current Opinion in Structural Biology
Illustrations of the impact of conserved versus altered CCRs on IDP functions.
C-terminal disordered tails of E. coli single stranded the open-ended polymerization of the corresponding SAM
DNA binding proteins belong to region R1 and these domain. With an FCR of 0.38 and NCPR of 0.07, the
tails engender positive cooperativity in single stranded disordered linker from PHC3 belongs to region R3 on the
DNA binding. Cooperativity in single stranded DNA diagram of states. This alternative linker promotes the open-
binding is abolished if the tails are eliminated or ended polymerization of PHC3. A chimera of the SAM
replaced with sequences drawn from the R3 region [63]. domain from Ph and the linker from the human ortholog
enhances transcriptional repression. Clearly, polymerization
Sterile alpha motifs (SAMs) are ubiquitous in eukaryotic requires that linkers tethered to the SAM domain be drawn
proteomes. SAMs are modular 70-residue alpha-helical from region R3 as opposed to R1 [64]. The results also
motifs that have an intrinsic ability to undergo open- demonstrate the connections between distinct CCRs and
ended polymerization and form left-handed helical su- different outcomes both in terms of SAM polymerization
pramolecular polymers. Among the many functions and the efficiency of transcription repression/derepression.
attributed to SAMs, their polymerization/depolymeriza-
tion reactions correlate with transcription repression/de- IDPs can function as entropic bristles and the conforma-
repression activities of gene silencing proteins. tional class that is encoded by the amino acid composition
Polyhomeotic (Ph) is a Drosophila protein that is a mem- of the IDP governs the properties of brushes or bristles.
ber of the polycomb group of proteins. These are chro- Investigations to assess the impact of entropic bristles as
matin-associated gene silencing proteins that solubilizing tags have established that sequences of dehy-
epigenetically regulate gene expression. The 88-residue drins, which belong to region R3, are more efficient than
intrinsically disordered linker that is directly N-terminal sequences drawn from region R1 at solubilizing reporter
to the SAM domain hinders open-ended polymerization proteins to which the bristles are tethered [65]. This
of Ph. With an FCR of 0.15 and NCPR of 0.08, this observation has been rationalized in terms of the in-
linker belongs to region R1 on the diagram-of-states creased FCR for optimal solubilizing tags.
[64]. The human ortholog of Ph is designated as Poly-
homeotic homolog 3 or PHC3. The N-terminal intrinsi- The importance of the magnitude of NCPR has been
cally disordered 84-residue linker of PHC3 also controls established in the recombination-activation gene
Current Opinion in Structural Biology 2015, 32:102–112 www.sciencedirect.com
Encoding form and function of IDPs Das, Ruff and Pappu 107
(RAG2). The sequence architecture of RAG2 is modular that are compatible with a given amino acid composition
and comprises a 60-residue ‘acidic hinge’ region that is astronomically large, do all conceivable sequences
connects the beta propeller core domain to a pleckstrin encode similar conformational properties and impact
homology domain [66]. The acidic hinge region is impor- function in similar ways? Of course, since IDPs serve
tant for the function of RAG2, which involves preventing as scaffolds for short linear motifs (SLiMs) [4,68–70], it
access to inappropriate repair mechanisms for DNA dou- stands to reason that conserving the identities and posi-
ble-stranded breaks such as alternative non-homologous tions of SLiMs will winnow down the number of func-
end joining. Key observations regarding the acidic hinge tionally relevant sequence alternatives for a given amino
highlight the importance of NCPR over details of the acid composition. Are there additional constraints that
primary sequence. Neutralization of charged residues could have a direct impact on global conformational
within the 31-residue N-terminal region of the acidic properties and hence on function?
hinge leads to increased alternative non-homologous
end joining whereas scrambling of the sequence that Quantitative studies of DNA binding proteins identified a
maintains NCPR maintains the functionality of the wild curious pattern of clustering of like-charged residues
type sequence. Similarly, human sequence variants of [71,72]. Recent systematic studies of charge patterning
RAG2 that lead to changes in NCPR cause increased have revealed the importance of the linear segregation
alternative non-homologous end joining and impaired versus mixing of oppositely charged residues as determi-
genome stability [66]. nants of conformational properties of polyampholytic
IDPs [38 ,73]. The patterning of oppositely charged
FG nucleoporins or FG-Nups can have distinct composi- residues is quantified in terms of a parameter designated
tional biases and these are distinguished by their FCR as k (see Figure 6). This parameter is bounded, 0 k 1,
values. FG-Nups with low FCR values belong to region and approaches zero if the oppositely charged residues are
R1 of the diagram-of-states and these are designated as well mixed in the linear sequence and approaches unity if
‘cohesive’ in contrast to sequences with higher FCR the oppositely charged residues are segregated [38 ].
values that belong to regions R2 and R3 and are desig- The number of sequences n(k) that are conceivable for
nated as being ‘repulsive’ [67]. The two categories of a given value of k is governed by the combination of FCR
sequences are proposed to play distinct roles as modula- and the constraints placed by the presence of conserved
tors of gating mechanisms in the nuclear pore complex. SLiMs. In general, n(k) is orders of magnitude higher for
low to intermediate k values when compared to high k
Going beyond CCRs: connecting sequence values. This high sequence entropy provides a default
patterns to conformational properties explanation for the observed preponderance of naturally
The diagram-of-states relies purely on the details of occurring sequences drawn from R2 and R3 for k values in
amino acid compositions and provides a zeroth order the range of 0.1–0.4 and a depletion of sequences with
classification of relationships between IDP sequences higher k values [38 ]. It is noteworthy that k also serves as
and conformational classes. The documented CCRs raise a single parameter surrogate for the strengths of intra-
an interesting question: Since the number of sequences chain electrostatic interactions that determine the overall
Figure 6
nw
2 ( σ σ) ∑ i δ
i=1 seq δ = ; κ = seq δ nw max
wt WPPDRGHDKSDRDRERGYDKVDRERERDRERDRDRGYDKADREEGKERRHHRREE κ = 0.02 sv1 WPPYDDRSRHERRHKYRRRRARKRHKGDREEGEEDVEDEDGDRRRRRKDDDDEGE κ = 0.43 sv2 WPPGGEDDEDDDDEEDDEGEDEDEDEAHYYKSHGRRRRKKRRKRRRHRRRRRRVR κ = 0.91
Current Opinion in Structural Biology
Calculation of k and using it to distinguish the sequences with different linear patterns of oppositely charged residues. The top row shows how k
is calculated. The overall charge asymmetry s is determined by the amino acid composition (see Figure 2). Each sequence is divided into nw
sliding windows and the mean squared deviation d helps quantify the deviation of the charge asymmetry across different sequence windows vis-a` -
vis the charge asymmetry encoded by the amino acid composition. The value of d is calculated for all sequence variants that are realizable for the
amino acid composition and this is used to evaluate the value of k, as shown, thus ensuring that k is bounded between 0 and 1. As an illustration
of the patterning that is quantified using k, we show the sequence of the ‘polar rich domain’ extracted from the sequence of the polyglutamine
tract binding protein PQB-P1. The bottom two rows show two de novo designed sequences designated as sv1 and sv2 for sequence variants
1 and 2. These two sequences were derived from alterations to the linear sequence distribution of oppositely charged residues [38 ]. On each
row, the values of k are shown to the right.
www.sciencedirect.com Current Opinion in Structural Biology 2015, 32:102–112
108 Sequences and Topology
conformational properties and the amplitudes of confor- changes to SCRs. Accordingly, the patterning concept
mational fluctuations. Specifically, in sequences with can be generalized to consider the patterns of charged
lower k values, intra-chain electrostatic repulsions are versus polar residues or charged versus aromatic residues.
screened by electrostatic attractions and these sequences The latter might be of particular relevance given growing
favor expanded, coil-like ensembles. In contrast, for interest in polycation–pi interactions [78].
sequences with higher k values, intra-chain electrostatic
attractions become dominant. In addition to global com- Direct impact of sequence patterns on IDP
paction, locally compact domains can form for sequences functions
with intermediate k values. Therefore, k serves as a PSC-CTR is the C-Terminal Region of the Posterior Sex
parameter to rationalize the boundaries between Combs subunit of the Polycomb Repressive Complex
sequences that conserve overall conformational proper- 1 system in Drosophila [79 ]. These proteins are involved
ties — and hence functions and phenotypes — versus in mediating heritable gene silencing and PSC-CTR is
sequences that yield altered conformational ensembles responsible for modulating non-covalent effects on chro-
and hence a loss or alteration of functions and phenotypes matin structure. Specifically, PSC-CTR is essential for
— see the summary in Figure 7. the inhibition of chromatin remodeling. The sequences
of PSC-CTRs are poorly conserved across orthologs.
Enabling de novo sequence design Systematic feature selection methods combined with
The connection between a parameter like k and confor- DNA binding studies and assays to quantify the repres-
mational properties enables the use of de novo design as a sion of chromatin remodeling helped identify sequence
tool for modulating SCRs. This should be helpful for patterns that distinguish repressive PSC-CTRs from non-
establishing the connections between changes to SCRs repressive ones. Non-repressive PSC-CTRs are distin-
and functions/phenotypes controlled by polyampholytic guishable by the ‘maximum contiguous negative charge’,
sequences drawn from regions R2 and R3. A range of which refers to the presence of contiguous stretches with
targets for such design efforts is readily available from the negative NCPR values. De novo sequence designs that
rich literature on IDPs with established functional roles redistribute the negative charge to lower the linear charge
for polyampholytic sequences [8,9,14 ,19,63,74–77]. Of density or eliminate the contiguous stretch of negative
course, the patterning of oppositely charged residues charges convert non-repressive PSC-CTRs to repressive
quantified by k is not the only way to conceive of ones. The study of Beh et al. [79 ] highlights the se-
modulating SCRs. Implicit in the work that uncovered quence encoding of the energy scales for electrostatics
the importance of k is the idea that changes to SCRs can interactions. It also highlights the need to go beyond
be realized by changes to sequence patterns that directly single value descriptors of sequence patterning such as
modulate the sequence-encoded balance between sol- k. Instead, the vectorial NCPR profile across the length of
vent mediated intra-chain repulsions and attractions. If the sequence (see Figure 7) is likely to be more informa-
the underlying energy scales cross some threshold vis-a`- tive for identifying local clusters of charge that are directly
vis thermal energy, then we can expect substantial relevant for controlling functions. There is also a case to
Figure 7
Connecting SCRs to Function Sequence 1 Representative Profile Function (WT) 1 Conformation
0.5
…VDRERERDRE 0 WT
NCPR
RDRDR GYDKA… –0.5 Function
–1 0 2 4 6 81012 14 16 Sequence Window (5 Residues)
Representative Sequence 2 Profile Function Conformation 1 0.5 WT Fixed Composition …DEDEDDEDGY 0 Function NCPR
(Sequences in R2 & R3) AVRRRRRKRR… –0.5 Modified
–1 0 2 4 6 81012 14 16 Sequence Window (5 Residues)
Current Opinion in Structural Biology
Illustrating the impact of sequence patterns and their conservation/alteration on IDP functions.
Current Opinion in Structural Biology 2015, 32:102–112 www.sciencedirect.com
Encoding form and function of IDPs Das, Ruff and Pappu 109
be made for going beyond the identification of conserved synergistic investigations must be brought to bear in order
SLiMs to include the presence of clusters of like charges to build on the insights that have been forthcoming with
in functional annotations of IDPs. Such clusters might regard to connecting information encoded in IDP
contribute either to attractive or repulsive long-range sequences to their form and function.
interactions that engender specificity of functions
through disordered regions. Conflict of interest
None declared.
Conclusions
We have summarized recent insights that help connect Acknowledgements
the information encoded in IDP sequences to conforma- We are grateful to M. Madan Babu, Martin Blackledge, Doug Barrick,
Ashok Deniz, Julie Forman-Kay, Tyler Harmon, Alex Holehouse, Richard
tional properties and functions. Efforts to uncover syner-
Kriwacki, Petra Levin, Timothy Lohman, Tanja Mittag, Anuradha Mittal,
gies among CCRs, SCRs, and SLiMs [69] as determinants Michael Rosen, Benjamin Schuler, and Andrea Soranno for many insightful
of conformational properties and functions of IDPs both discussions over the past two years. This work was supported by grants from
the US National Science Foundation (MCB 1121867) and US National
in vitro and in vivo are just burgeoning and several
Institutes of Health (5R01NS056114).
questions remain open for investigation especially with
regard to the in vivo implications of CCRs and SCRs. The
References and recommended reading
impact of chain length on CCRs and SCRs remains Papers of particular interest, published within the period of review have
been highlighted as:
unexplored. Many IDP sequences have high proline
contents and a systematic investigation of this feature
of special interest
is warranted. It is conceivable that different polar side- of outstanding interest
chains will have different effects on the conformational
1. Chothia C, Gough J, Vogel C, Teichmann SA: Evolution of the
properties and solubility profiles of IDPs, that is, there is
protein repertoire. Science 2003, 300:1701-1703.
good reason to conjecture that Ser-rich sequences might
2. Babu MM, Kriwacki RW, Pappu RV: Versatility from protein
behave differently than Gln-rich sequences and so on.
disorder. Science 2012, 337:1460-1461.
This conjecture has merits given published accounts of
3. Wright PE, Dyson HJ: Intrinsically disordered proteins in
differences between Gln versus Asn rich disordered cellular signalling and regulation. Nat Rev: Mol Cell Biol 2015,
16:18-29.
regions [80]. Targets for alternative splicing are enriched
An updated account of the importance of IDPs in cell signaling and the
in transcripts for IDPs [18]. This opens the door to the control of cellular decisions and fates.
possibility that posttranscriptional processing provides a
4. van der Lee R, Buljan M, Lang B, Weatheritt RJ, Daughdrill GW,
route to regulate CCRs and SCRs for tissue-specific Dunker AK, Fuxreiter M, Gough J, Gsponer J, Jones DT et al.:
Classification of intrinsically disordered regions and proteins.
control and rewiring of protein interaction networks.
Chem Rev 2014, 114:6589-6631.
Many of the common cellular posttranslational modifica- A comprehensive review of informatics and physical considerations that
have enabled the classification of motifs and IDPs.
tions involve either addition (Ser/Thr/Tyr phosphoryla-
tion, Gln/Asn deamidation, Tyr, Trp, or hydroxy amino 5. Uversky VN: Natively unfolded proteins: a point where biology
waits for physics. Protein Sci 2002, 11:739-756.
acid sulfonation, and Tyr nitration) or neutralization of
charges (Lys acetylation, Glu/Asp amidation, and Arg 6. Uversky VN: A decade and a half of protein intrinsic disorder:
biology still waits for physics. Protein Sci 2013, 22:693-724.
citrullination). N-linked and O-linked glycosylation can
7. Dunker AK, Brown CJ, Lawson JD, Iakoucheva LM, Obradovic´ Z:
either add or neutralize charge depending on the sugar
Intrinsic disorder and protein function. Biochemistry 2002,
being added. These post-translational modifications can 41:6573-6582.
lead to a change in conformational class. They can also
8. Buske PJ, Levin PA: Extreme C terminus of bacterial
influence the sequence patterning of oppositely charged cytoskeletal protein FtsZ plays fundamental role in assembly
independent of modulatory proteins. J Biol Chem 2012,
residues or the linear charge density within contiguous
287:10945-10957.
stretches of like charges. Therefore, altered sequence
9. Buske PJ, Levin PA: A flexible C-terminal linker is required for
patterns within IDPs and their functional consequences
proper FtsZ assembly in vitro and cytokinetic ring formation in
are likely to be an emergent property of posttranslational vivo. Mol Microbiol 2013, 89:249-263.
This paper demonstrates the central importance of the disordered
modifications. Finally, the connection between the time
C-terminal linker in forming Z-rings that mediate bacterial cell divi-
scales for inter-conversions between distinct conforma- sion. The linker is a polyampholyte and it connects the core domain
of FtsZ, which is a tubulin homolog, to the conserved C-terminal
tions and equilibrium descriptions of CCRs and SCRs
SLiM that mediates interactions with the network of FtsZ binding
remains under explored. Preliminary work has focused on proteins.
the impact of sequence-specific contributions to internal
10. Tantos A, Han KH, Tompa P: Intrinsic disorder in cell signaling
friction [20,81–84]. Advances in nuclear magnetic reso- and gene transcription. Mol Cell Endocrinol 2012, 348:457-465.
nance [85–89] and single molecule spectroscopies [90–92]
11. Meinema AC, Laba JK, Hapsari RA, Otten R, Mulder FAA, Kralt A,
combined with novel computational and theoretical van den Bogaart G, Lusk CP, Poolman B, Veenhoff LM: Long
unfolded linkers facilitate membrane protein import through
methodologies [93–95] should pave the way for compre-
the nuclear pore complex. Science 2011, 333:90-93.
hensive characterization of IDP dynamics and assessing
12. Meinema AC, Poolman B, Veenhoff LM: Quantitative analysis of
their impact on the dynamical regulation of cellular
membrane protein transport across the nuclear pore complex.
phenotypes [96,97]. Overall, it is clear that continued Traffic 2013, 14:487-501.
www.sciencedirect.com Current Opinion in Structural Biology 2015, 32:102–112
110 Sequences and Topology
An elegant study showing the importance of amino acid composition as a dimensions of disordered proteins. Proc Natl Acad Sci USA
determinant of IDP function. The authors demonstrate that composition 2014, 111:5213-5218.
controls the Stokes radius of disordered linkers that play a role in
25. Guerry P, Mollica L, Blackledge M: Mapping protein
facilitating nuclear import of substrates.
conformational energy landscapes using NMR and molecular
13. Housden NG, Hopper JTS, Lukoyanova N, Rodriguez-Larrea D, simulation. Chemphyschem 2013, 14:3046-3058.
Wojdyla JA, Klein A, Kaminska R, Bayley H, Saibil HR,
26. Jensen MR, Blackledge M: Testing the validity of ensemble
Robinson CV et al.: Intrinsically disordered protein threads
descriptions of intrinsically disordered proteins. Proc Natl
through the bacterial outer-membrane Porin OmpF. Science
Acad Sci USA 2014, 111:E1557-E1558.
2013, 340:1570-1574.
A multi-pronged investigation that highlights the role of the unstructured
27. Jensen MR, Ruigrok RWH, Blackledge M: Describing
N-terminal domain of colicin E9 in mediating the formation of bacterial
intrinsically disordered proteins at atomic resolution by NMR.
translocons. The IDR threads through two of the pores of the trimeric
Curr Opin Struct Biol 2013, 23:426-435.
OmpF porin and does so spontaneously in a manner that remains
unexplained. The sequence of the unstructured IDR belongs to the R1 28. Ozenne V, Schneider R, Yao M, Huang J-R, Salmon L,
region of the diagram-of-states raising intriguing questions about Zweckstetter M, Jensen MR, Blackledge M: Mapping the
mechanisms. potential energy landscape of intrinsically disordered proteins
at amino acid resolution. J Am Chem Soc 2012, 134:
14. Srinivasan N, Bhagawati M, Ananthanarayanan B, Kumar S: 15138-15148.
Stimuli-sensitive intrinsically disordered protein brushes. Nat
Commun 2014, 5:5145. 29. Parigi G, Rezaei-Ghaleh N, Giachetti A, Becker S, Fernandez C,
This study demonstrates the feasibility of using IDPs in engineering Blackledge M, Griesinger C, Zweckstetter M, Luchinat C: Long-
applications. The authors use sequences that mimic those of the poly- range correlated dynamics in intrinsically disordered proteins.
ampholytic heavy subunits of neurofilament sidearms and graft these to J Am Chem Soc 2014, 136:16201-16209.
surfaces to generate polymer brushes. They show that these well-mixed
polyampholytes characterized by low k values undergo dramatic con- 30. Schwalbe M, Ozenne V, Bibow S, Jaremko M, Jaremko L,
formational transitions in response to changes in pH and solution con- Gajda M, Jensen MR, Biernat J, Becker S, Mandelkow E et al.:
ditions. This clearly highlights the possibility that solution conditions Predictive atomic resolution descriptions of intrinsically
might have an impact that mimics the effect of increasing k. disordered hTau40 and alpha-synuclein in solution from NMR
and small angle scattering. Structure 2014, 22:238-249.
15. Guharoy M, Szabo B, Martos SC, Kosol S, Tompa P: Intrinsic
31. Jain N, Bhattacharya M, Mukhopadhyay S: Chain collapse of an
structural disorder in cytoskeletal proteins. Cytoskeleton 2013,
70:550-571. amyloidogenic intrinsically disordered protein. Biophys J 2011,
101:1720-1729.
16. van der Lee R, Lang B, Kruse K, Gsponer J, de Groot NS,
32. Forman-Kay JD, Mittag T: From sequence and forces to
Huynen MA, Matouschek A, Fuxreiter M, Babu MM: Intrinsically
structure function, and evolution of intrinsically disordered
disordered segments affect protein half-life in the cell and
proteins. Structure 2013, 21:1492-1499.
during evolution. Cell Rep 2014, 8:1832-1844.
33. Krzeminski M, Marsh JA, Neale C, Choy W-Y, Forman-Kay JD:
17. Gsponer J, Futschik ME, Teichmann SA, Babu MM: Tight
Characterization of disordered proteins with ENSEMBLE.
regulation of unstructured proteins: from transcript synthesis
Bioinformatics 2013, 29:398-399.
to protein degradation. Science 2008, 322:1365-1368.
34. Liu B, Chia D, Csizmok V, Farber P, Forman-Kay JD, Gradinaru CC:
18. Buljan M, Chalancon G, Eustermann S, Wagner GP, Fuxreiter M,
The effect of intrachain electrostatic repulsion on
Bateman A, Babu MM: Tissue-specific splicing of disordered
conformational disorder and dynamics of the Sic1 protein.
segments that embed binding motifs rewires protein
J Phys Chem B 2014, 118:4088-4097.
interaction networks. Mol Cell 2012, 46:871-883.
35. Marsh JA, Dancheck B, Ragusa MJ, Allaire M, Forman-Kay JD,
19. Wang YF, Fisher JC, Mathew R, Ou L, Otieno S, Sublet J, Xiao LM,
Peti W: Structural diversity in free and bound states of
Chen JH, Roussel MF, Kriwacki RW: Intrinsic disorder mediates
intrinsically disordered protein phosphatase 1 regulators.
the diverse regulatory functions of the Cdk inhibitor p21. Nat
Structure 2010, 18:1094-1103.
Chem Biol 2011, 7:214-221.
36. Marsh JA, Forman-Kay JD: Sequence determinants of
20. Borgia A, Wensley BG, Soranno A, Nettels D, Borgia MB, compaction in intrinsically disordered proteins. Biophys J
Localizing
Hoffmann A, Pfeil SH, Lipman EA, Clarke J, Schuler B: 2010, 98:2383-2390.
internal friction along the reaction coordinate of protein
folding by combining ensemble and single-molecule 37. Marsh JA, Forman-Kay JD: Ensemble modeling of protein
fluorescence spectroscopy. Nat Commun 2012, 3:1195. disordered states: experimental restraint contributions and
validation. Proteins – Struct Funct Bioinform 2012, 80:556-572.
21. Hofmann H, Soranno A, Borgia A, Gast K, Nettels D, Schuler B:
Polymer scaling laws of unfolded and intrinsically disordered 38. Das RK, Pappu RV: Conformations of intrinsically disordered
proteins quantified with single-molecule spectroscopy. Proc proteins are influenced by linear sequence distributions of
Natl Acad Sci USA 2012, 109:16155-16160. oppositely charged residues. Proc Natl Acad Sci USA 2013,
An important paper that quantifies the impact of charge on the dimen- 110:13392-13397.
sions of archetypal IDPs and unfolded proteins in aqueous solutions. This This paper introduces the importance of charge patterning as a determi-
work helps in identifying the connection between amino acid composition nant of IDP conformations. It also introduces the diagram-of-states
and the effective theta point for different protein sequences. The combi- classification that forms the focus of the current review.
nation of innovative single molecule measurements, its comprehensive
39. Lyle N, Das RK, Pappu RV: A quantitative measure for protein
nature, and the use of updated adaptations of polymer physics theories
conformational heterogeneity. J Chem Phys 2013, 139:121907.
make this a very important paper.
40. Mao AH, Crick SL, Vitalis A, Chicoine CL, Pappu RV: Net charge
22. Mueller-Spaeth S, Soranno A, Hirschfeld V, Hofmann H,
per residue modulates conformational ensembles of
Rueegger S, Reymond L, Nettels D, Schuler B: Charge
intrinsically disordered proteins. Proc Natl Acad Sci USA 2010,
interactions can dominate the dimensions of intrinsically
107:8183-8188.
disordered proteins. Proc Natl Acad Sci USA 2010, 107:
14609-14614.
41. Mao AH, Lyle N, Pappu RV: Describing sequence–ensemble
relationships for intrinsically disordered proteins. Biochem J
23. Soranno A, Koenig I, Borgia MB, Hofmann H, Zosel F, Nettels D,
2013, 449:307-318.
Schuler B: Single-molecule spectroscopy reveals polymer
effects of disordered proteins in crowded environments. Proc 42. Brown CJ, Johnson AK, Dunker AK, Daughdrill GW: Evolution and
Natl Acad Sci USA 2014, 111:4874-4879. disorder. Curr Opin Struct Biol 2011, 21:441-446.
24. Wuttke R, Hofmann H, Nettels D, Borgia MB, Mittal J, Best RB, 43. Moesa HA, Wakabayashi S, Nakai K, Patil A: Chemical
Schuler B: Temperature-dependent solvation modulates the composition is maintained in poorly conserved intrinsically
Current Opinion in Structural Biology 2015, 32:102–112 www.sciencedirect.com
Encoding form and function of IDPs Das, Ruff and Pappu 111
disordered regions and suggests a means for their membrane-binding motif sort Ist2 and Ssy1 to junctions.
classification. Mol BioSyst 2012, 8:3262-3273. Traffic 2015, 16:135-147.
44. Brucale M, Schuler B, Samori B: Single-molecule studies of 63. Kozlov AG, Weiland E, Mittal A, Waldman V, Antony E, Fazio N,
intrinsically disordered proteins. Chem Rev 2014, 114:3281- Pappu RV, Lohman TM: Intrinsically disordered C-terminal tails
3317. of E. coli single-stranded DNA binding protein regulate
cooperative binding to single-stranded DNA. J Mol Biol 2015,
45. Tran HT, Mao A, Pappu RV: Role of backbone – solvent 427:763-774.
interactions in determining conformational equilibria of
intrinsically disordered proteins. J Am Chem Soc 2008, 64. Robinson AK, Leal BZ, Nanyes DR, Kaur Y, Ilangovan U, Schirf V,
130:7380-7392. Hinck AP, Demeler B, Kim CA: Human polyhomeotic homolog 3
(PHC3) sterile alpha motif (SAM) linker allows open-ended
46. Holehouse AS, Garai K, Lyle N, Vitalis A, Pappu RV: Quantitative
polymerization of PHC3 SAM. Biochemistry 2012, 51:5379-5386.
assessments of the distinct contributions of polypeptide
backbone amides versus side chain groups to chain 65. Santner AA, Croy CH, Vasanwala FH, Uversky VN, Van Y-YJ,
expansion via chemical denaturation. J Am Chem Soc 2015, Dunker AK: Sweeping away protein aggregation with entropic
137:2984-2995. bristles: intrinsically disordered protein fusions enhance
soluble expression. Biochemistry 2012, 51:7250-7262.
47. Teufel DP, Johnson CM, Lum JK, Neuweiler H: Backbone-driven
collapse in unfolded protein chains. J Mol Biol 2011, 409: 66. Coussens MA, Wendland RL, Deriano L, Lindsay CR, Arnal SM,
250-262. Roth DB: RAG2’s acidic hinge restricts repair-pathway choice
and promotes genomic stability. Cell Rep 2013, 4:870-878.
48. Karandur D, Wong K-Y, Pettitt BM: Solubility and aggregation of
Gly5 in water. J Phys Chem B 2014, 118:9565-9572. 67. Yamada J, Phillips JL, Patel S, Goldfien G, Calestagne-Morelli A,
Huang H, Reza R, Acheson J, Krishnan VV, Newsam S et al.: A
49. Rubinstein M, Colby RH: Polymer Physics.. Oxford/New York:
bimodal distribution of two distinct categories of intrinsically
Oxford University Press; 2003.
disordered structures with separate functions in FG
nucleoporins. Mol Cell Proteomics 2010, 9:2205-2224.
50. Sanchez IC: Phase transition behavior of the isolated polymer
chain. Macromolecules 1979, 12:980-988.
68. Davey NE, Van Roey K, Weatheritt RJ, Toedt G, Uyar B,
Altenberg B, Budd A, Diella F, Dinkel H, Gibson TJ: Attributes of
51. Crick SL, Jayaraman M, Frieden C, Wetzel R, Pappu RV:
short linear motifs. Mol BioSyst 2012, 8:268-281.
Fluorescence correlation spectroscopy shows that
monomeric polyglutamine molecules form collapsed
69. Tompa P, Davey NE, Gibson TJ, Babu MM: A million peptide
structures in aqueous solutions. Proc Natl Acad Sci USA 2006,
motifs for the molecular biologist. Mol Cell 2014, 55:161-169.
103:16764-16769.
70. Ba ANN, Yeh BJ, van Dyk D, Davidson AR, Andrews BJ, Weiss EL,
52. Crick SL, Ruff KM, Garai K, Frieden C, Pappu RV: Unmasking the
Moses AM: Proteome-wide discovery of evolutionary
roles of N- and C-terminal flanking sequences from exon 1 of
conserved sequences in disordered regions. Sci Signal 2012:5.
huntingtin as modulators of polyglutamine aggregation. Proc
Natl Acad Sci USA 2013, 110:20075-20080.
71. Potoyan DA, Papoian GA: Energy landscape analyses of
disordered histone tails reveal special organization of their
53. Mukhopadhyay S, Krishnan R, Lemke EA, Lindquist S, Deniz AA: A
conformational dynamics. J Am Chem Soc 2011, 133:
natively unfolded yeast prion monomer adopts an ensemble of
7405-7415.
collapsed and rapidly fluctuating structures. Proc Natl Acad Sci
USA 2007, 104:2649-2654.
72. Vuzman D, Levy Y: DNA search efficiency is modulated by
charge composition and distribution in the intrinsically
54. Vitalis A, Pappu RV: ABSINTH: a new continuum solvation
disordered tail. Proc Natl Acad Sci USA 2010, 107:21004-21009.
model for simulations of polypeptides in aqueous solutions.
J Comput Chem 2009, 30:673-699.
73. Srivastava D, Muthukumar M: Sequence dependence of
conformations of polyampholytes. Macromolecules 1996,
55. Radhakrishnan A, Vitalis A, Mao AH, Steffen AT, Pappu RV:
29:2324-2326.
Improved atomistic Monte Carlo simulations demonstrate
that poly-L-proline adopts heterogeneous ensembles of
74. Mitrea DM, Yoon MK, Ou L, Kriwacki RW: Disorder-function
conformations of semi-rigid segments interrupted by kinks.
relationships for the cell cycle regulatory proteins p21 and
J Phys Chem B 2012, 116:6862-6871.
p27. Biol Chem 2012, 393:259-274.
56. Xue Y, Skrynnikov NR: Motion of a disordered polypeptide
75. Bertagna A, Toptygin D, Brand L, Barrick D: The effects of
chain as studied by paramagnetic relaxation enhancements,
conformational heterogeneity on the binding of the Notch
15N relaxation, and molecular dynamics simulations: how fast
intracellular domain to effector proteins: a case of biologically
is segmental diffusion in denatured ubiquitin? J Am Chem Soc
tuned disorder. Biochem Soc Trans 2008, 36:157-166.
2011, 133:14614-14628.
76. Johnson SE, Barrick D: Dissecting and circumventing the
57. Bernado P, Svergun DI: Structural analysis of intrinsically
requirement for RAM in CSL-dependent notch signaling. PLoS
disordered proteins by small-angle X-ray scattering. Mol
ONE 2012, 7:e39093.
BioSyst 2012, 8:151-167.
77. Lai J, Koh CH, Tjota M, Pieuchot L, Raman V, Chandrababu KB,
58. Mittal A, Lyle N, Harmon TS, Pappu RV: Hamiltonian Switch
Yang D, Wong L, Jedd G: Intrinsically disordered proteins
Metropolis Monte Carlo Simulations for improved
aggregate at fungal cell-to-cell channels and regulate
conformational sampling of intrinsically disordered regions
intercellular connectivity. Proc Natl Acad Sci USA 2012,
tethered to ordered domains of proteins. J Chem Theory
109:15781-15786.
Comput 2014, 10:3550-3562.
78. Song J, Ng SC, Tompa P, Lee KAW, Chan HS: Polycation–pi
59. Dobrynin AV, Colby RH, Rubinstein M: Scaling theory of
interactions are a driving force for molecular recognition by an
polyelectrolyte solutions. Macromolecules 1995, 28:1859-1871.
intrinsically disordered oncoprotein family. PLoS Comput Biol
2013, 9:e1003239.
60. Dobrynin AV, Rubinstein M: Flory theory of a polyampholyte
chain. J Phys II 1995, 5:677-695.
79. Beh LY, Colwell LJ, Francis NJ: A core subunit of Polycomb
61. Sickmeier M, Hamilton JA, LeGall T, Vacic V, Cortese MS, repressive complex 1 is broadly conserved in function but not
Tantos A, Szabo B, Tompa P, Chen J, Uversky VN et al.: DisProt: primary sequence. Proc Natl Acad Sci USA 2012, 109:
the database of disordered proteins. Nucleic Acids Res 2007, E1063-E1071.
35:D786-D793. This paper captures the essence of the connections between sequence
patterning and IDP functions. The focus on the evolution of coarse grain
62. Kralt A, Carretta M, Mari M, Reggiori F, Steen A, Poolman B, sequence patterns that defy ready recognition by naı¨ve sequence com-
Veenhoff LM: Intrinsically disordered linker and plasma parisons makes this a very appealing read.
www.sciencedirect.com Current Opinion in Structural Biology 2015, 32:102–112
112 Sequences and Topology
80. Halfmann R, Alberti S, Krishnan R, Lyle N, O’Donnell CW, King OD, 89. Andresen C, Helander S, Lemak A, Fares C, Csizmok V,
Berger B, Pappu RV, Lindquist S: Opposing effects of glutamine Carlsson J, Penn LZ, Forman-Kay JD, Arrowsmith CH,
and asparagine govern prion formation by intrinsically Lundstrom P et al.: Transient structure and dynamics in the
disordered proteins. Mol Cell 2011, 43:72-84. disordered c-Myc transactivation domain affect Bin1 binding.
Nucleic Acids Res 2012, 40:6353-6366.
81. Schulz JCF, Schmidt L, Best RB, Dzubiella J, Netz RR: Peptide
chain dynamics in light and heavy water: zooming in on 90. Polinkovsky ME, Gambin Y, Banerjee PR, Erickstad MJ,
internal friction. J Am Chem Soc 2012, 134:6273-6279. Groisman A, Deniz AA: Ultrafast cooling reveals microsecond-
scale biomolecular dynamics. Nat Commun 2014, 5:5737.
82. Soranno A, Buchli B, Nettels D, Cheng RR, Mueller-Spaeth S,
Pfeil SH, Hoffmann A, Lipman EA, Makarov DE, Schuler B:
91. Kalinin S, Peulen T, Sindbert S, Rothwell PJ, Berger S, Restle T,
Quantifying internal friction in unfolded and intrinsically
Goody RS, Gohlke H, Seidel CAM: A toolkit and benchmark
disordered proteins with single-molecule spectroscopy. Proc
study for FRET-restrained high-precision structural modeling.
Natl Acad Sci USA 2012, 109:17800-17806.
Nat Methods 2012, 9:U1129-U1218.
83. de Sancho D, Sirur A, Best RB: Molecular origins of internal
92. Olofsson L, Felekyan S, Doumazane E, Scholler P, Fabre L,
friction effects on protein-folding rates. Nat Commun 2014,
Zwier JM, Rondard P, Seidel CAM, Pin J-P, Margeat E: Fine
5:4307.
tuning of sub-millisecond conformational dynamics controls
metabotropic glutamate receptors agonist efficacy. Nat
84. Echeverria I, Makarov DE, Papoian GA: Concerted dihedral
Commun 2014, 5:5206.
rotations give rise to internal friction in unfolded proteins. J Am
Chem Soc 2014, 136:8708-8713.
93. Bolhuis PG, Chandler D, Dellago C, Geissler PL: Transition path
sampling: throwing ropes over rough mountain passes, in the
85. Silvers R, Sziegat F, Tachibana H, Segawa S-I, Whittaker S,
dark. Annu Rev Phys Chem 2002, 53:291-318.
Guenther UL, Gabel F, Huang J-R, Blackledge M, Wirmer-
Bartoschek J et al.: Modulation of structure and dynamics by
94. Borrero EE, Dellago C: Overcoming barriers in trajectory space:
disulfide bond formation in unfolded states. J Am Chem Soc
mechanism and kinetics of rare events via Wang–Landau
2012, 134:6846-6854.
enhanced transition path sampling. J Chem Phys 2010,
86. Guerry P, Schneider R, Huang JR, Delaforge E, Maurin D, 133:134112.
Ozenne V, Communie G, Mollica L, Jensen M, Blackledge M:
95. Juraszek J, Vreede J, Bolhuis PG: Transition path sampling
Protein conformational dynamics and molecular recognition
of protein conformational changes. Chem Phys 2012,
in folded and unfolded proteins by NMR. Eur Biophys J Biophys
396:30-44.
Lett 2013, 42:S61.
87. Markwick PRL, Bouvignies G, Salmon L, McCammon JA, 96. Borcherds W, Theillet F-X, Katzer A, Finzel A, Mishall KM,
Nilges M, Blackledge M: Toward a unified representation of Powell AT, Wu H, Manieri W, Dieterich C, Selenko P et al.: Disorder
protein structural dynamics in solution. J Am Chem Soc 2009, and residual helicity alter p53-Mdm2 binding affinity and
131:16968-16975. signaling in cells. Nat Chem Biol 2014, 10:1000-1002.
88. Mittag T, Kay LE, Forman-Kay JD: Protein dynamics and 97. Ferreon ACM, Ferreon JC, Wright PE, Deniz AA: Modulation
conformational disorder in molecular recognition. J Mol of allostery by protein intrinsic disorder. Nature 2013, 498:
Recognit 2010, 23:105-116. 390-394.
Current Opinion in Structural Biology 2015, 32:102–112 www.sciencedirect.com