DOCSLIB.ORG

Databases & Structural Classes of Proteins

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Databases & Structural Classes of Proteins Databases & Structural Classes of Proteins Marjolein Thunnissen Lund September 2009 Classification of protein structures: Why needed? ! Plays a central role in understanding the principles of protein structure, function and evolution. ! Class assignment can provide unknown functional details. This is of special importance in structural genomics projects. Databases : PDB The Protein Data Bank (PDB) was established at Brookhaven National Laboratory in 1971 as an archive for biological macromolecular crystal structures. In the beginning it held seven structures. (http:// www.rcsb.org/) Currently it holds around 60046 structures. PDB Content Growth PDB Growth in New Folds: Proportion of "new folds" (light blue) and "old folds" (orange) for a given year as a number of protein PDB search results: The PDBsum database (at www.ebi.ac.uk) contains summary information and derived data on entries in the Protein Data Bank. PDBsum Additional features: secondary structure Includes analysis of ligand binding to proteins. Databases : MMDB Uses a file format diferent from that used by the PDB. Integrated into the Entrez system - very useful when you need to find a 3D structure of a homologous protein. Provides an alignment to related structures. Contains about 18000 domains against which a search with a structure can be performed using the VAST algorithm. MMDB: A result of a search for similar structures Databases : NDB The Nucleic Acid Database Project (NDB) assembles and distributes structural information about nucleic acids. http:// ndbserver.rutgers.edu/ The logic of classification: Assignment of independent folding units --> domains. Assignment. of secondary structure. Assignment of structural class (all !, all ", !/" and !+"). Assignment of domains Spatially separated units of protein structure. May. have sequence and/or structural resemblance to another protein structure/domain Example: The globin domain. One protein - one domain Fold: Globin-like, Superfamily: globin-like Example: The structure of one domain of a bacterial muramidase. 450 amino acid residues build up 27 helices arranged in a two- layered ring. The ring has a large central hole with a diameter of about 30 Å. Scop fold: alpha-alpha superhelix, superfamily: bacterial muramidases Example Pyruvate kinase folds into several domains, one of which is an a/b barrel (red). One of the loop regions in this barrel domain is extended and comprises about 100 amino acid residues that fold into a separate domain (blue) built up from antiparallel b strands. The C-terminal region of about 140 residues forms a third domain (green), which is an open twisted a/b structure. Assignment of fold The number, type connectivity and arrangement of secondary structures define the fold of the protein. Databases may disagree in the definition of a certain fold, therefore diferent databases should be checked. The name is given to a fold often on the bases of the first protein/protein function, where the fold was observed. oligonucleotide/ oligosaccharide binding folds The coenzyme-binding domain of some dehydrogenases: the Rossmann fold Examples of folds: Class: alpha & beta, fold:TIM barrel Subform of Rossmann fold: flavodoxin fold Superfolds: Folds found within many diferent superfamilies: Rossmann fold, TIM-barrels, ferredoxin-like, four-helical bundles, Ig-like b-sandwich, OB-binding fold, etc. These folds are adopted by groups of seemingly non- homologous proteins with diferent functions. They tend to bind ligand at similar structural sites-supersites. Assignment of superfamily For many proteins with similar folds, sequence, structure or function suggest divergence from a common ancestor. Superfamily refers to group of proteins that appear to be homologous, even in absence of significant sequence similarity. Unrelated protein with the same fold are called analogues. Some members of the IGSF (Immunoglobulin superfamily How can we distinguish analogues from homologues? A high level of structure similarity most probably means homology. Conservation of unusual structural features outside the core structure (turn conformations, left-handed b-a-b units, p-helices, etc.). Low, but convincing sequence identity (>12%) calculated after structural superposition. The presence of key active site residues even in the absence of global sequence similarity. Sequence similarity bridges-if A is similar to B and B is similar to C, than A is similar to C. Clusters proteins at four major levels, Class (C), Architecture (A), Topology (T) and Homologous superfamily (H). http://cathwww.biochem.ucl.ac.uk/latest/index.html Assignment of structural class After assignment of secondary structure and domains, structural class can be assigned to each domain. Structural classes divide proteins according to secondary structure content and organisation. Databases: SCOP Structural Classification of Proteins. Created by manual inspection and automated methods, aims to provide a detailed and comprehensive description of the structural and evolutionary relationships between all proteins whose structure is known. http://scop.mrc- lmb.cam.ac. Structure classification at SCOP: Proteins are divided into functional domains, which are grouped into a hierarchy: Class - Fold - Superfamily - Family -Protein. Proteins in the same superfamily have probable common evolutionary origin. Proteins in the same family have clear evolutionary relationship. Proteins in the same fold but diferent superfamily do not have a clear common ancestor. Scop classification statistics Class Number of folds Number of superfamilies Number of families All alpha proteins 284 507 871 All beta proteins 174 354 742 Alpha and beta proteins (a/b) 147 244 803 Alpha and beta proteins (a+b) 376 552 1055 Multi-domain proteins 66 66 89 Membrane /cell surface proteins 58 110 123 Small proteins 90 129 219 Total 1195 1962 3902 Classification at CATH: Class - Architecture - Topology - Homology (SCOP: class-fold-superfamily-family-protein) ! " barrel !" " ribbon Tiamin- like T cell endotoxin " antigen " sandwich Ig-like transthyretin " etc. etc plastocyanin . etc . Class assignment may be funny! Which class this protein belongs to ? Staphylococcal nuclease Search results from CATH Search results from SCOP Class assignment in this case follows the fact that the core of the protein comprises an oligonucleotide/olygosac- charide (OB) binding fold b barrel.Thus, structural similarity/function may afect fold assignment. Databases: FSSP Based on exhaustive all- against-all comparison of protein 3D structures currently in the PDB. Multiple alignment views: structure neighbours sequence neighbours structures superimposed in 3D http:// ekhidna.biocenter.helsinki.fi/ dali/start FSSP search result:.
Load more

Recommended publications
  • The Janus-Like Role of Proline Metabolism in Cancer Lynsey Burke1,Innaguterman1, Raquel Palacios Gallego1, Robert G
    Burke et al. Cell Death Discovery (2020) 6:104 https://doi.org/10.1038/s41420-020-00341-8 Cell Death Discovery REVIEW ARTICLE Open Access The Janus-like role of proline metabolism in cancer Lynsey Burke1,InnaGuterman1, Raquel Palacios Gallego1, Robert G. Britton1, Daniel Burschowsky2, Cristina Tufarelli1 and Alessandro Rufini1 Abstract The metabolism of the non-essential amino acid L-proline is emerging as a key pathway in the metabolic rewiring that sustains cancer cells proliferation, survival and metastatic spread. Pyrroline-5-carboxylate reductase (PYCR) and proline dehydrogenase (PRODH) enzymes, which catalyze the last step in proline biosynthesis and the first step of its catabolism, respectively, have been extensively associated with the progression of several malignancies, and have been exposed as potential targets for anticancer drug development. As investigations into the links between proline metabolism and cancer accumulate, the complexity, and sometimes contradictory nature of this interaction emerge. It is clear that the role of proline metabolism enzymes in cancer depends on tumor type, with different cancers and cancer-related phenotypes displaying different dependencies on these enzymes. Unexpectedly, the outcome of rewiring proline metabolism also differs between conditions of nutrient and oxygen limitation. Here, we provide a comprehensive review of proline metabolism in cancer; we collate the experimental evidence that links proline metabolism with the different aspects of cancer progression and critically discuss the potential mechanisms involved. ● How is the rewiring of proline metabolism regulated Facts depending on cancer type and cancer subtype? 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; ● Is it possible to develop successful pharmacological ● Proline metabolism is widely rewired during cancer inhibitor of proline metabolism enzymes for development.
    [Show full text]
  • A Structural Perspective on the Enzyme with Two Rossmann-Fold Domains
    biomolecules Review S-adenosyl-l-homocysteine Hydrolase: A Structural Perspective on the Enzyme with Two Rossmann-Fold Domains Krzysztof Brzezinski Laboratory of Structural Microbiology, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland; [email protected] Received: 16 November 2020; Accepted: 15 December 2020; Published: 16 December 2020 Abstract: S-adenosyl-l-homocysteine hydrolase (SAHase) is a major regulator of cellular methylation reactions that occur in eukaryotic and prokaryotic organisms. SAHase activity is also a significant source of l-homocysteine and adenosine, two compounds involved in numerous vital, as well as pathological processes. Therefore, apart from cellular methylation, the enzyme may also influence other processes important for the physiology of particular organisms. Herein, presented is the structural characterization and comparison of SAHases of eukaryotic and prokaryotic origin, with an emphasis on the two principal domains of SAHase subunit based on the Rossmann motif. The first domain is involved in the binding of a substrate, e.g., S-adenosyl-l-homocysteine or adenosine and the second domain binds the NAD+ cofactor. Despite their structural similarity, the molecular interactions between an adenosine-based ligand molecule and macromolecular environment are different in each domain. As a consequence, significant differences in the conformation of d-ribofuranose rings of nucleoside and nucleotide ligands, especially those attached to adenosine moiety, are observed. On the other hand, the chemical nature of adenine ring recognition, as well as an orientation of the adenine ring around the N-glycosidic bond are of high similarity for the ligands bound in the substrate- and cofactor-binding domains.
    [Show full text]
  • 02 Whole.Pdf (8.685Mb)
    Copyright is owned by the Author of the thesis. Permission is given for a copy to be downloaded by an individual for the purpose of research and private study only. The thesis may not be reproduced elsewhere without the permission of the Author. X-RAY CRYSTALLOGRAPHIC INVESTIGATIONS OF THE STRUCTURES OF ENZYMES OF MEDICAL AND BIOTECHNOLOGICA L IMPORTANCE by Richard Lawrence Kingston A dissertation submitted in partial satisfaction of the requirements fo r the degree of Doctor of Philosophy in the Department of Biochemistry at MASSEY UNIVERSITY, NEW ZEALAND November, 1996 ABSTRACT This thesis is broadly in three parts. In the first, the problem of identifying conditions under which a protein will crystallize is considered. Then structural studies on two enzymes are reported, glucose-fructose oxidoreductase from the bacterium Zymomonas mobilis, and the human bile salt dependent lipase (carboxyl ester hydrolase). The ability of protein crystals to diffract X-rays provides the experimental data required to determine their three dimensional structures at atomic resolution. However the crystalliza­ tion of proteins is not always straightforward. A systematic procedure to search for protein crystallization conditions has been developed. This procedure is based on the use of orthog­ onal arrays (matrices whose columns possess certain balancing properties). The theoretical and practical background to the problem is discussed, and the relationship of the presented procedure to other published search methods is considered. The anaerobic Gram-negative bacterium Zymomonas mobilis occurs naturally in sugar-rich growth media, and has attracted much interest because of its potential for industrial ethanol production. In this organism the periplasmic enzyme glucose-fructose oxidoreductase (GFOR) is involved in a protective mechanism to counter osmotic stress.
    [Show full text]
  • PREDICTION REPORTS Successful Recognition of Protein Folds Using Threading Methods Biased by Sequence Similari
    PROTEINS: Structure, Function, and Genetics Suppl 3:104–111 (1999) FOLD RECOGNITION: PREDICTION REPORTS Successful Recognition of Protein Folds Using Threading Methods Biased by Sequence Similarity and Predicted Secondary Structure David T. Jones,* Michael Tress, Kevin Bryson, and Caroline Hadley Department of Biological Sciences, University of Warwick, Coventry, United Kingdom ABSTRACT Analysis of our fold recognition sequence families includes a member of known 3D struc- results in the 3rd Critical Assessment in Structure ture. Sensitive sequence profile methods can extend the Prediction (CASP3) experiment, using the programs range of comparative modeling to the point where around THREADER 2 and GenTHREADER, shows an en- 12% of the families can be assigned to a known 3D couraging level of overall success. Of the 23 submit- structural superfamily, but in contrast to this, it is esti- ted predictions, 20 targets showed no clear se- mated that the probability of a novel protein having a quence similarity to proteins of known 3D structure. similar fold to a known structure is currently as high as These 20 targets can be divided into 22 domains, of 60–70%. There is, therefore, a great deal to be gained from which, 20 domains either entirely match a previ- attempting to solve the problem of building models for very ously known fold, or partially match a substantial remotely related proteins, and for proteins which have region of a known fold. Of these 20 domains, we merely analogous folds, and so are beyond the scope of correctly assigned the folds in 10 cases. Proteins normal comparative modeling strategies. To date the most Suppl 1999:3:104–111.
    [Show full text]
  • That Is the Question
    polymers Review To Tie or Not to Tie? That Is the Question Pawel Dabrowski-Tumanski 1,2 and Joanna I. Sulkowska 1,2,* 1 Centre of New Technologies, University of Warsaw, Warsaw 02-097, Poland; [email protected] 2 Faculty of Chemistry, University of Warsaw, Warsaw 02-093, Poland * Correspondence: [email protected]; Tel.: +48-22-55-43678 Received: 26 August 2017; Accepted: 12 September 2017; Published: 16 September 2017 Abstract: In this review, we provide an overview of entangled proteins. Around 6% of protein structures deposited in the PBD are entangled, forming knots, slipknots, lassos and links. We present theoretical methods and tools that enabled discovering and classifying such structures. We discuss the advantages and disadvantages of the non-trivial topology in proteins, based on available data about folding, stability, biological properties and evolutionary conservation. We also formulate intriguing and challenging questions on the border of biophysics, bioinformatics, biology and mathematics, which arise from the discovery of an entanglement in proteins. Finally, we discuss possible applications of entangled proteins in medicine and nanotechnology, such as the chance to design super stable proteins, whose stability could be controlled by chemical potential. Keywords: knots; link; lasso; topology; polymer; disulfide 1. Introduction Self-tying of proteins was long considered as impossible, as it requires the threading of a chain through a twisted loop, which in principle is an entropically unfavorable event. However, similar structures have been known to exist in other biopolymers (such as DNA) for many years [1,2], and their self-tying was attributed to, e.g., better packing [3].
    [Show full text]
  • Α+Β 31 37 28 18 16 12 40 3
    class Fold# EC SC HI SS HP MJ MP MG total Fam. PDB Rep. Struc. Name α/β 18 60 46 23 40 19 743 202 16 183 1xel - NAD(P)-binding Rossmann Fold α/β 24 20 69 17 19 17 16 10 11 179 13 132 1gky - P-loop Containing NTP Hydrolases α+β 31 37 28 18 16 12 40 33 157 23 160 1fxd - like Ferrodoxin α/β 01 45 36 13 22 11 10 54 146 37 399 1byb - TIM-barrel α/β 23 18 17 794822 67 5 36 1pyd a:2-181 Thiamin-binding α/β 04 15 11 7 10 1955 63 13 132 2tmd a:490-645 FAD/NAD(P)-binding α+β 55 89789366 56 4 23 1sry a:111-421 Class-II-aaRS/Biotin Synthetases β 27 7 10 884433 47 5 19 1fnb 19-154 Reductase/Elongation Factor Domain β 24 13 7433333 39 18 177 1snc - OB-fold α+β 11 10 8482221 37 11 48 1igd - beta-Grasp β 55 9 10 552222 37 7 19 1bdo - Barrel-sandwich hybrid α/β 15 55445633 35 3 22 2ts1 1-217 ATP pyrophoshatases α/β 05 10 4242223 29 4 35 1zym a: The "swivelling" beta/beta/alpha domain α/β 60 57463211 29 3 18 3pmg a:1-190 Phosphoglucomutase, first 3 domains α+β 68 42364243 28 2 3 1mat - Creatinase/methionine aminopeptidase α+β 39 64344111 24 3 42 1gad o:149-312 like G3P dehydrogenase, Ct-dom α+β 18 54412212 21 3 23 1fkd - FKBP-like α/β 41 33331311 18 3 16 1opr - Phosphoribosyltransferases (PRTases) α 78 19121111 17 1 23 1oel a:(*) GroEL, the ATPase domain α+β 10 22242122 17 2 5 1dar 477-599 Ribosomal protein S5 domain 2-like α+β 43 43221122 17 4 50 3grs 364-478 FAD/NAD-linked reductases, dimer-dom.
    [Show full text]
  • Arabidopsis Transcriptome Analysis Reveals Key Roles of Melatonin in Plant Defense Systems
    Arabidopsis Transcriptome Analysis Reveals Key Roles of Melatonin in Plant Defense Systems Sarah Weeda1, Na Zhang2, Xiaolei Zhao3, Grace Ndip4, Yangdong Guo2*, Gregory A. Buck5, Conggui Fu3, Shuxin Ren1* 1 Agriculture Research Station, Virginia State University, Petersburg, Virginia, United States of America, 2 College of Agriculture and Biotechnology, China Agricultural University, Beijing, P. R. China, 3 Tianjin Crop Science Institute, Tianjin Academy of Agricultural Science, Tianjin, P. R. China, 4 Department of Chemistry, Virginia State University, Petersburg, Virginia, United States of America, 5 Center of the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, United States of America Abstract Melatonin is a ubiquitous molecule and exists across kingdoms including plant species. Studies on melatonin in plants have mainly focused on its physiological influence on growth and development, and on its biosynthesis. Much less attention has been drawn to its affect on genome-wide gene expression. To comprehensively investigate the role(s) of melatonin at the genomics level, we utilized mRNA-seq technology to analyze Arabidopsis plants subjected to a 16-hour 100 pM (low) and 1 mM (high) melatonin treatment. The expression profiles were analyzed to identify differentially expressed genes. 100 pM melatonin treatment significantly affected the expression of only 81 genes with 51 down-regulated and 30 up-regulated. However, 1 mM melatonin significantly altered 1308 genes with 566 up-regulated and 742 down-regulated. Not all genes altered by low melatonin were affected by high melatonin, indicating different roles of melatonin in regulation of plant growth and development under low and high concentrations. Furthermore, a large number of genes altered by melatonin were involved in plant stress defense.
    [Show full text]
  • Supporting Information
    Supporting Information Rackovsky 10.1073/pnas.0903433106 Table S1. The 10 property factors 1. Alpha-helix/bend preference 2. Side-chain size 3. Extended structure preference 4. Hydrophobicity 5. Double-bend preference 6. Amino acid composition 7. Flat extended preference 8. Occurrence in ␣ region 9. pK 10. Surrounding hydrophobicity The first 4 property factors correspond essentially to single amino acid physical properties. The remaining 6 factors are superpositions of several physical properties and for convenience are identified by the property making the greatest contribution to the factor. Rackovsky www.pnas.org/cgi/content/short/0903433106 1of4 Table S2. The 59 CAT groups C A T Number of sequences CATH group name 1 20 5 39 Single alpha-helices involved in coiled coils or other helix–helix interfaces 1 50 10 31 Glycosyltransferase 1 20 58 38 Methane monooxygenase Hydroxylase, chain G, domain 1 1 10 238 67 Recoverin, domain 1 1 10 490 32 Globin-like 1 10 287 53 Helix hairpins 1 10 8 40 Helicase, ruva protein, domain 3 1 20 1,050 29 Glutathione S-transferase Yfyf (class Pi), chain A, domain 2 1 20 1,250 27 Growth hormone, chain A 1 10 472 20 Cyclin A, domain 1 1 10 760 33 Cytochrome Bc1 complex, chain D, domain 2 1 20 120 54 Four-helix bundle [hemerythrin (Met), subunit A] 1 10 10 150 Arc repressor mutant, subunit A 1 10 150 54 DNA polymerase, domain 1 1 25 40 67 Serine threonine protein phosphatase 5, tetratricopeptide repeat 1 10 510 28 Transferase (phosphotransferase), domain 1 2 40 50 125 OB fold (dihydrolipoamide acetyltransferase,
    [Show full text]
  • Deep Evolutionary Analysis Reveals the Design Principles of Fold A
    RESEARCH ARTICLE Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases Rahil Taujale1,2, Aarya Venkat3, Liang-Chin Huang1, Zhongliang Zhou4, Wayland Yeung1, Khaled M Rasheed4, Sheng Li4, Arthur S Edison1,2,3, Kelley W Moremen2,3, Natarajan Kannan1,3* 1Institute of Bioinformatics, University of Georgia, Athens, Georgia; 2Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia; 3Department of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia; 4Department of Computer Science, University of Georgia, Athens, Georgia Abstract Glycosyltransferases (GTs) are prevalent across the tree of life and regulate nearly all aspects of cellular functions. The evolutionary basis for their complex and diverse modes of catalytic functions remain enigmatic. Here, based on deep mining of over half million GT-A fold sequences, we define a minimal core component shared among functionally diverse enzymes. We find that variations in the common core and emergence of hypervariable loops extending from the core contributed to GT-A diversity. We provide a phylogenetic framework relating diverse GT-A fold families for the first time and show that inverting and retaining mechanisms emerged multiple times independently during evolution. Using evolutionary information encoded in primary sequences, we trained a machine learning classifier to predict donor specificity with nearly 90% accuracy and deployed it for the annotation of understudied GTs. Our studies provide an evolutionary framework for investigating complex relationships connecting GT-A fold sequence, structure, function and regulation. *For correspondence: [email protected] Introduction Competing interests: The Complex carbohydrates make up a large bulk of the biomass of any living cell and play essential authors declare that no roles in biological processes ranging from cellular interactions, pathogenesis, immunity, quality con- competing interests exist.
    [Show full text]
  • IDH1 Targeting As a New Potential Option for Intrahepatic Cholangiocarcinoma Treatment—Current State and Future Perspectives
    molecules Review IDH1 Targeting as a New Potential Option for Intrahepatic Cholangiocarcinoma Treatment—Current State and Future Perspectives 1, 1, 1 1 Fabiana Crispo y , Michele Pietrafesa y , Valentina Condelli , Francesca Maddalena , Giuseppina Bruno 2, Annamaria Piscazzi 2, Alessandro Sgambato 1, Franca Esposito 3,* and Matteo Landriscina 1,2,* 1 Laboratory of Pre-Clinical and Translational Research, IRCCS, Referral Cancer Center of Basilicata, 85028 Rionero in Vulture (PZ), Italy; [email protected] (F.C.); [email protected] (M.P.); [email protected] (V.C.); [email protected] (F.M.); [email protected] (A.S.) 2 Medical Oncology Unit, Department of Medical and Surgical Sciences, University of Foggia, 71100 Foggia, Italy; [email protected] (G.B.); [email protected] (A.P.) 3 Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, 80131 Naples, Italy * Correspondence: [email protected] (F.E.); [email protected] (M.L.); Tel.: +39-081-746-3145 (F.E.); +39-088-173-6426 (M.L.) These authors have contributed equally to this work. y Received: 29 July 2020; Accepted: 17 August 2020; Published: 18 August 2020 Abstract: Cholangiocarcinoma is a primary malignancy of the biliary tract characterized by late and unspecific symptoms, unfavorable prognosis, and few treatment options. The advent of next-generation sequencing has revealed potential targetable or actionable molecular alterations in biliary tumors. Among several identified genetic alterations, the IDH1 mutation is arousing interest due to its role in epigenetic and metabolic remodeling. Indeed, some IDH1 point mutations induce widespread epigenetic alterations by means of a gain-of-function of the enzyme, which becomes able to produce the oncometabolite 2-hydroxyglutarate, with inhibitory activity on α-ketoglutarate-dependent enzymes, such as DNA and histone demethylases.
    [Show full text]
  • Significance of Knotted Structures for Function of Proteins and Nucleic Acids SEPTEMBER 17–21, 2014 | WARSAW, POLAND
    Biophysical Society Thematic Meeting | PROGRAM AND ABSTRACTS Significance of Knotted Structures for Function of Proteins and Nucleic Acids SEPTEMBER 17–21, 2014 | WARSAW, POLAND Ministry of Science and Higher Education Republic of Poland Thank You to the Programming Committee and Local Organizers Program Committee Wilma Olson, Rutgers University, USA Jose Onuchic, Rice University, USA Matthias Rief, Technical University of Munich, Germany Joanna Sulkowska, University of Warsaw, Poland Sarah Woodson, Johns Hopkins University, USA Local Organizers Krsysztof Bryl, University of Warmia and Mazury, Poland Sebastian Kmiecik, University of Warsaw, Poland Andrzej Kolinski, University of Warsaw, Poland Alicja Kurcinska, Secretary, University of Warsaw, Poland Monika Pietrzak, University of Warmia and Mazury, Poland Joanna Sulkowska, University of Warsaw, Poland Mariusz Szabelski, University of Warmia and Mazury, Poland Zbigniew Wieczorek, University of Warmia and Mazury, Poland - 1 - This meeting is financially supported by Ministry of Science and Higher Education University of Warsaw, Center for New Technology (CeNT), Foundation for Polish Science (Inter) and National Science Center Poland (Sonata BIS) Additional support provided by European Molecular Biology Organization (EMBO) Centrum Nowych Technologii - 2 - Significance of Knotted Structures for Function of Proteins and Nucleic Acids Welcome Letter September 2014 Dear Colleagues, We would like to welcome you to the conference on the “Significance of Knotted Structures for Function of Proteins and Nucleic Acids”. During this meeting we will focus on recent progress in identifying a biological role of knots in proteins and nucleic acids. This is a new, interdisciplinary field, which has recently been extensively explored by many groups. One important motivation to study these topics is an increasing number of proteins with knots being discovered.
    [Show full text]
  • Proteins Eugene Shakhnovich Harvard University Boulder, CO July 25-27 2012 Outline
    Proteins Eugene Shakhnovich Harvard University Boulder, CO July 25-27 2012 Outline Lecture 1. Introduction: Principles of structural organization of proteins and Protein Universe. Concepts of convergent and divergent molecular evolution. Lecture 2. Protein folding – Experiment and Theory and Simulations Lecture 3: Bridging scales: From Protein Biophysics to Population Genetics (‘’From Crick to Darwin and back’’) Marriage made in heaven: genomics and protein folding/evolution Proteins are folded on various scales As of now we know hundreds of thousands of sequences (Swissprot) and a few thousand of Structures (protein data bank) Proteins are tightly packed Structural organization of globular proteins Fold, Folding Pattern and Packing Simplified models of protein structures. a), A detailed fold describing positions of secondary structures in the protein hain and in space (see also Fig. 13-1e). (b), The folding pattern of the protein chain with omitted details of loop pathways, the size and exact orientation of α-helices (shown as cylinders) and β-strands (shown as arrows). (c), Packing: a stack of structural segments with no loop shown and omitted details of size, orientation and direction of α-helices and β-strands (which are therefore presented as ribbons rather than as arrows). Similarities at the fold level, differences at the detailed structural level Two close relatives: horse hemoglobin α and horse hemoglobin β (both possessing a heme shown as a wire model with iron in the center). Find similarities and differences. (For tips: they are highly similar although have some differences in details of loop conformations, in details of orientation of some helices, and in one additional helical turn available in the β globin, on the right).
    [Show full text]