101
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Wilson D, Madera M, Vogel C, Chothia C, Gough J. The SUPERFAMILY database in 2007: families and functions. Nucleic Acids Res 2006; 35:D308-13. [PMID: 17098927 PMCID: PMC1669749 DOI: 10.1093/nar/gkl910] [Citation(s) in RCA: 169] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The SUPERFAMILY database provides protein domain assignments, at the SCOP 'superfamily' level, for the predicted protein sequences in over 400 completed genomes. A superfamily groups together domains of different families which have a common evolutionary ancestor based on structural, functional and sequence data. SUPERFAMILY domain assignments are generated using an expert curated set of profile hidden Markov models. All models and structural assignments are available for browsing and download from http://supfam.org. The web interface includes services such as domain architectures and alignment details for all protein assignments, searchable domain combinations, domain occurrence network visualization, detection of over- or under-represented superfamilies for a given genome by comparison with other genomes, assignment of manually submitted sequences and keyword searches. In this update we describe the SUPERFAMILY database and outline two major developments: (i) incorporation of family level assignments and (ii) a superfamily-level functional annotation. The SUPERFAMILY database can be used for general protein evolution and superfamily-specific studies, genomic annotation, and structural genomics target suggestion and assessment.
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Affiliation(s)
- Derek Wilson
- MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 2QH, UK.
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102
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Shiozawa K, Goda N, Shimizu T, Mizuguchi K, Kondo N, Shimozawa N, Shirakawa M, Hiroaki H. The common phospholipid-binding activity of the N-terminal domains of PEX1 and VCP/p97. FEBS J 2006; 273:4959-71. [PMID: 17018057 DOI: 10.1111/j.1742-4658.2006.05494.x] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
PEX1 is a type II AAA-ATPase that is indispensable for biogenesis and maintenance of the peroxisome, an organelle responsible for the primary metabolism of lipids, such as beta-oxidation and lipid biosynthesis. Recently, we demonstrated a striking structural similarity between its N-terminal domain and those of other membrane-related AAA-ATPases, such as valosine-containing protein (p97). The N-terminal domain of valosine-containing protein serves as an interface to its adaptor proteins p47 and Ufd1, whereas the physiologic interaction partner of the N-terminal domain of PEX1 remains unknown. Here we found that N-terminal domains isolated from valosine-containing protein, as well as from PEX1, bind phosphoinositides. The N-terminal domain of PEX1 appears to preferentially bind phosphatidylinositol 3-monophosphate and phosphatidylinositol 4-monophosphate, whereas the N-terminal domain of valosine-containing protein displays broad and nonspecific lipid binding. Although N-ethylmaleimide-sensitive fusion protein, CDC48 and Ufd1 have structures similar to that of valosine-containing protein, they displayed lipid specificity similar to that of the N-terminal domain of PEX1 in the assays. By mutational analysis, we demonstrate that a conserved arginine surrounded by hydrophobic residues is essential for lipid binding, despite very low sequence similarity between PEX1 and valosine-containing protein.
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Affiliation(s)
- Kumiko Shiozawa
- International Graduate School of Arts and Sciences, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
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103
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Hollunder J, Friedel M, Beyer A, Workman CT, Wilhelm T. DASS: efficient discovery and p-value calculation of substructures in unordered data. ACTA ACUST UNITED AC 2006; 23:77-83. [PMID: 17032678 DOI: 10.1093/bioinformatics/btl511] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
MOTIVATION Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. RESULTS We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. AVAILABILITY The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS
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Affiliation(s)
- Jens Hollunder
- Department of Theoretical Systems Biology, Leibniz Institute for Age Research--Fritz-Lipmann-Institute e. V. (former IMB Jena) Beutenbergstrasse 11, D-07745 Jena, Germany
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104
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Korkin D, Davis FP, Alber F, Luong T, Shen MY, Lucic V, Kennedy MB, Sali A. Structural modeling of protein interactions by analogy: application to PSD-95. PLoS Comput Biol 2006; 2:e153. [PMID: 17096593 PMCID: PMC1635541 DOI: 10.1371/journal.pcbi.0020153] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2006] [Accepted: 10/04/2006] [Indexed: 11/18/2022] Open
Abstract
We describe comparative patch analysis for modeling the structures of multidomain proteins and protein complexes, and apply it to the PSD-95 protein. Comparative patch analysis is a hybrid of comparative modeling based on a template complex and protein docking, with a greater applicability than comparative modeling and a higher accuracy than docking. It relies on structurally defined interactions of each of the complex components, or their homologs, with any other protein, irrespective of its fold. For each component, its known binding modes with other proteins of any fold are collected and expanded by the known binding modes of its homologs. These modes are then used to restrain conventional molecular docking, resulting in a set of binary domain complexes that are subsequently ranked by geometric complementarity and a statistical potential. The method is evaluated by predicting 20 binary complexes of known structure. It is able to correctly identify the binding mode in 70% of the benchmark complexes compared with 30% for protein docking. We applied comparative patch analysis to model the complex of the third PSD-95, DLG, and ZO-1 (PDZ) domain and the SH3-GK domains in the PSD-95 protein, whose structure is unknown. In the first predicted configuration of the domains, PDZ interacts with SH3, leaving both the GMP-binding site of guanylate kinase (GK) and the C-terminus binding cleft of PDZ accessible, while in the second configuration PDZ interacts with GK, burying both binding sites. We suggest that the two alternate configurations correspond to the different functional forms of PSD-95 and provide a possible structural description for the experimentally observed cooperative folding transitions in PSD-95 and its homologs. More generally, we expect that comparative patch analysis will provide useful spatial restraints for the structural characterization of an increasing number of binary and higher-order protein complexes.
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Affiliation(s)
- Dmitry Korkin
- Department of Biopharmaceutical Sciences, University of California San Francisco, San Francisco, California, United States of America
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America
- California Institute for Quantitative Biomedical Research, University of California San Francisco, San Francisco, California, United States of America
| | - Fred P Davis
- Department of Biopharmaceutical Sciences, University of California San Francisco, San Francisco, California, United States of America
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America
- California Institute for Quantitative Biomedical Research, University of California San Francisco, San Francisco, California, United States of America
| | - Frank Alber
- Department of Biopharmaceutical Sciences, University of California San Francisco, San Francisco, California, United States of America
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America
- California Institute for Quantitative Biomedical Research, University of California San Francisco, San Francisco, California, United States of America
| | - Tinh Luong
- Division of Biology, California Institute of Technology, Pasadena, California, United States of America
| | - Min-Yi Shen
- Department of Biopharmaceutical Sciences, University of California San Francisco, San Francisco, California, United States of America
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America
- California Institute for Quantitative Biomedical Research, University of California San Francisco, San Francisco, California, United States of America
| | - Vladan Lucic
- Department of Structural Biology, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Mary B Kennedy
- Division of Biology, California Institute of Technology, Pasadena, California, United States of America
| | - Andrej Sali
- Department of Biopharmaceutical Sciences, University of California San Francisco, San Francisco, California, United States of America
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, United States of America
- California Institute for Quantitative Biomedical Research, University of California San Francisco, San Francisco, California, United States of America
- * To whom correspondence should be addressed. E-mail:
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105
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Abstract
Many classification schemes for proteins and domains are either hierarchical or semi-hierarchical yet most databases, especially those offering genome-wide analysis, only provide assignments to sequences at one level of their hierarchy. Given an established hierarchy, the problem of assigning new sequences to lower levels of that existing hierarchy is less hard (but no less important) than the initial top level assignment which requires the detection of the most distant relationships. A solution to this problem is described here in the form of a new procedure which can be thought of as a hybrid between pairwise and profile methods. The hybrid method is a general procedure that can be applied to any pre-defined hierarchy, at any level, including in principle multiple sub-levels. It has been tested on the SCOP classification via the SUPERFAMILY database and performs significantly better than either pairwise or profile methods alone. Perhaps the greatest advantage of the hybrid method over other possible approaches to the problem is that within the framework of an existing profile library, the assignments are fully automatic and come at almost no additional computational cost. Hence it has already been applied at the SCOP family level to all genomes in the SUPERFAMILY database, providing a wealth of new data to the biological and bioinformatics communities.
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Affiliation(s)
- Julian Gough
- Unite de Bioinformatique Structurale, Institut Pasteur, 25-28 Rue du Docteur Roux, 75724 Paris Cedex 15, Paris, France.
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106
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Lin K, Zhu L, Zhang DY. An initial strategy for comparing proteins at the domain architecture level. Bioinformatics 2006; 22:2081-6. [PMID: 16837531 DOI: 10.1093/bioinformatics/btl366] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Ideally, only proteins that exhibit highly similar domain architectures should be compared with one another as homologues or be classified into a single family. By combining three different indices, the Jaccard index, the Goodman-Kruskal gamma function and the domain duplicate index, into a single similarity measure, we propose a method for comparing proteins based on their domain architectures. RESULTS Evaluation of the method using the eukaryotic orthologous groups of proteins (KOGs) database indicated that it allows the automatic and efficient comparison of multiple-domain proteins, which are usually refractory to classic approaches based on sequence similarity measures. As a case study, the PDZ and LRR_1 domains are used to demonstrate how proteins containing promiscuous domains can be clearly compared using our method. For the convenience of users, a web server was set up where three different query interfaces were implemented to compare different domain architectures or proteins with domain(s), and to identify the relationships among domain architectures within a given KOG from the Clusters of Orthologous Groups of Proteins database. CONCLUSION The approach we propose is suitable for estimating the similarity of domain architectures of proteins, especially those of multidomain proteins. AVAILABILITY http://cmb.bnu.edu.cn/pdart/.
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Affiliation(s)
- Kui Lin
- MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China.
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107
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Weiner J, Beaussart F, Bornberg-Bauer E. Domain deletions and substitutions in the modular protein evolution. FEBS J 2006; 273:2037-47. [PMID: 16640566 DOI: 10.1111/j.1742-4658.2006.05220.x] [Citation(s) in RCA: 96] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The main mechanisms shaping the modular evolution of proteins are gene duplication, fusion and fission, recombination and loss of fragments. While a large body of research has focused on duplications and fusions, we concentrated, in this study, on how domains are lost. We investigated motif databases and introduced a measure of protein similarity that is based on domain arrangements. Proteins are represented as strings of domains and comparison was based on the classic dynamic alignment scheme. We found that domain losses and duplications were more frequent at the ends of proteins. We showed that losses can be explained by the introduction of start and stop codons which render the terminal domains nonfunctional, such that further shortening, until the whole domain is lost, is not evolutionarily selected against. We demonstrated that domains which also occur as single-domain proteins are less likely to be lost at the N terminus and in the middle, than at the C terminus. We conclude that fission/fusion events with single-domain proteins occur mostly at the C terminus. We found that domain substitutions are rare, in particular in the middle of proteins. We also showed that many cases of substitutions or losses result from erroneous annotations, but we were also able to find courses of evolutionary events where domains vanish over time. This is explained by a case study on the bacterial formate dehydrogenases.
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Affiliation(s)
- January Weiner
- Division of Bioinformatics, School of Biological Sciences, The Westfalian Wilhelms University of Münster, Germany
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108
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Vogel C, Chothia C. Protein family expansions and biological complexity. PLoS Comput Biol 2006; 2:e48. [PMID: 16733546 PMCID: PMC1464810 DOI: 10.1371/journal.pcbi.0020048] [Citation(s) in RCA: 161] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2005] [Accepted: 03/27/2006] [Indexed: 11/19/2022] Open
Abstract
During the course of evolution, new proteins are produced very largely as the result of gene duplication, divergence and, in many cases, combination. This means that proteins or protein domains belong to families or, in cases where their relationships can only be recognised on the basis of structure, superfamilies whose members descended from a common ancestor. The size of superfamilies can vary greatly. Also, during the course of evolution organisms of increasing complexity have arisen. In this paper we determine the identity of those superfamilies whose relative sizes in different organisms are highly correlated to the complexity of the organisms. As a measure of the complexity of 38 uni- and multicellular eukaryotes we took the number of different cell types of which they are composed. Of 1,219 superfamilies, there are 194 whose sizes in the 38 organisms are strongly correlated with the number of cell types in the organisms. We give outline descriptions of these superfamilies. Half are involved in extracellular processes or regulation and smaller proportions in other types of activity. Half of all superfamilies have no significant correlation with complexity. We also determined whether the expansions of large superfamilies correlate with each other. We found three large clusters of correlated expansions: one involves expansions in both vertebrates and plants, one just in vertebrates, and one just in plants. Our work identifies important protein families and provides one explanation of the discrepancy between the total number of genes and the apparent physiological complexity of eukaryotic organisms. One of the main goals in biology is to understand how complex organisms have evolved. Much of an organism's physiology, and hence complexity, is determined by its protein repertoire. The repertoire has been largely formed by the duplication, divergence, and combination of genes. This means that proteins can be grouped into families whose members are descended from a common ancestor. The authors have examined the sizes of 1,219 protein families in 38 eukaryotes of different complexity. Only a small fraction of protein families have expansions that are correlated with the number of cell types in the organisms. Half of these families are involved in regulation or extracellular processes. Other families do have expansions but in a lineage-specific manner. Thus, certain protein family expansions are “progressive” in that they lead to increases in biological complexity; other expansions are “conservative” in that they help an organism to adapt better to its environment, but do not increase its complexity. This means that there is no simple correlation between an organism's complexity and the number of its genes.
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Affiliation(s)
- Christine Vogel
- Medical Research Council Laboratory of Molecular Biology, Cambridge, United Kingdom.
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109
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Marsden RL, Ranea JAG, Sillero A, Redfern O, Yeats C, Maibaum M, Lee D, Addou S, Reeves GA, Dallman TJ, Orengo CA. Exploiting protein structure data to explore the evolution of protein function and biological complexity. Philos Trans R Soc Lond B Biol Sci 2006; 361:425-40. [PMID: 16524831 PMCID: PMC1609337 DOI: 10.1098/rstb.2005.1801] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
New directions in biology are being driven by the complete sequencing of genomes, which has given us the protein repertoires of diverse organisms from all kingdoms of life. In tandem with this accumulation of sequence data, worldwide structural genomics initiatives, advanced by the development of improved technologies in X-ray crystallography and NMR, are expanding our knowledge of structural families and increasing our fold libraries. Methods for detecting remote sequence similarities have also been made more sensitive and this means that we can map domains from these structural families onto genome sequences to understand how these families are distributed throughout the genomes and reveal how they might influence the functional repertoires and biological complexities of the organisms. We have used robust protocols to assign sequences from completed genomes to domain structures in the CATH database, allowing up to 60% of domain sequences in these genomes, depending on the organism, to be assigned to a domain family of known structure. Analysis of the distribution of these families throughout bacterial genomes identified more than 300 universal families, some of which had expanded significantly in proportion to genome size. These highly expanded families are primarily involved in metabolism and regulation and appear to make major contributions to the functional repertoire and complexity of bacterial organisms. When comparisons are made across all kingdoms of life, we find a smaller set of universal domain families (approx. 140), of which families involved in protein biosynthesis are the largest conserved component. Analysis of the behaviour of other families reveals that some (e.g. those involved in metabolism, regulation) have remained highly innovative during evolution, making it harder to trace their evolutionary ancestry. Structural analyses of metabolic families provide some insights into the mechanisms of functional innovation, which include changes in domain partnerships and significant structural embellishments leading to modulation of active sites and protein interactions.
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Affiliation(s)
- Russell L Marsden
- Department of Biochemistry, University College London Gower Street, London WC1E 6BT, UK.
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110
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Pasek S, Risler JL, Brézellec P. Gene fusion/fission is a major contributor to evolution of multi-domain bacterial proteins. Bioinformatics 2006; 22:1418-23. [PMID: 16601004 DOI: 10.1093/bioinformatics/btl135] [Citation(s) in RCA: 110] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Most proteins comprise one or several domains. New domain architectures can be created by combining previously existing domains. The elementary events that create new domain architectures may be categorized into three classes, namely domain(s) insertion or deletion (indel), exchange and repetition. Using 'DomainTeam', a tool dedicated to the search for microsyntenies of domains, we quantified the relative contribution of these events. This tool allowed us to collect homologous bacterial genes encoding proteins that have obviously evolved by modular assembly of domains. We show that indels are the most frequent elementary events and that they occur in most cases at either the N- or C-terminus of the proteins. As revealed by the genomic neighbourhood/context of the corresponding genes, we show that a substantial number of these terminal indels are the consequence of gene fusions/fissions. We provide evidence showing that the contribution of gene fusion/fission to the evolution of multi-domain bacterial proteins is lower-bounded by 27% and upper-bounded by 64%. We conclude that gene fusion/fission is a major contributor to the evolution of multi-domain bacterial proteins.
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Affiliation(s)
- Sophie Pasek
- Laboratoire Statistique et Génome 523 Place des Terrasses, 91034 Evry cedex, France.
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111
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Chandonia JM, Kim SH. Structural proteomics of minimal organisms: conservation of protein fold usage and evolutionary implications. BMC STRUCTURAL BIOLOGY 2006; 6:7. [PMID: 16566839 PMCID: PMC1488858 DOI: 10.1186/1472-6807-6-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2005] [Accepted: 03/28/2006] [Indexed: 11/10/2022]
Abstract
BACKGROUND Determining the complete repertoire of protein structures for all soluble, globular proteins in a single organism has been one of the major goals of several structural genomics projects in recent years. RESULTS We report that this goal has nearly been reached for several "minimal organisms"--parasites or symbionts with reduced genomes--for which over 95% of the soluble, globular proteins may now be assigned folds, overall 3-D backbone structures. We analyze the structures of these proteins as they relate to cellular functions, and compare conservation of fold usage between functional categories. We also compare patterns in the conservation of folds among minimal organisms and those observed between minimal organisms and other bacteria. CONCLUSION We find that proteins performing essential cellular functions closely related to transcription and translation exhibit a higher degree of conservation in fold usage than proteins in other functional categories. Folds related to transcription and translation functional categories were also overrepresented in minimal organisms compared to other bacteria.
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Affiliation(s)
- John-Marc Chandonia
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Sung-Hou Kim
- Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- Department of Chemistry, University of California, Berkeley, CA 94720, USA
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112
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Abstract
Considering the limited success of the most sophisticated docking methods available and the amount of computation required for systematic docking, cataloging all the known interfaces may be an alternative basis for the prediction of protein tertiary and quaternary structures. We classify domain interfaces according to the geometry of domain-domain association. By applying a simple and efficient method called "interface tag clustering," more than 4,000 distinct types of domain interfaces are collected from Protein Quaternary Structure Server and Protein Data Bank. Given a pair of interacting domains, we define "face" as the set of interacting residues in each single domain and the pair of interacting faces as an "interface." We investigate how the geometry of interfaces relates to a network of interacting protein families, such as how many different binding orientations are possible between two families or whether a family uses distinct surfaces or the same surface when the family has diverse interaction partners from various families. We show there are, on average, 1.2-1.9 different types of interfaces between interacting domains and a significant number of family pairs associate in multiple orientations. In general, a family tends to use distinct faces for each partner when the family has diverse interaction partners. Each face is highly specific to its interaction partner and the binding orientation. The relative positions of interface residues are generally well conserved within the same type of interface even between remote homologs. The classification result is available at http://www.biotec.tu-dresden.de/~wkim/supplement.
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Affiliation(s)
- Wan Kyu Kim
- Biotechnological Centre, TU Dresden, Germany
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113
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Wriggers W, Chakravarty S, Jennings PA. Control of protein functional dynamics by peptide linkers. Biopolymers 2006; 80:736-46. [PMID: 15880774 DOI: 10.1002/bip.20291] [Citation(s) in RCA: 145] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Control of structural flexibility is essential for the proper functioning of a large number of proteins and multiprotein complexes. At the residue level, such flexibility occurs due to local relaxation of peptide bond angles whose cumulative effect may result in large changes in the secondary, tertiary or quaternary structures of protein molecules. Such flexibility, and its absence, most often depends on the nature of interdomain linkages formed by oligopeptides. Both flexible and relatively rigid peptide linkers are found in many multidomain proteins. Linkers are thought to control favorable and unfavorable interactions between adjacent domains by means of variable softness furnished by their primary sequence. Large-scale structural heterogeneity of multidomain proteins and their complexes, facilitated by soft peptide linkers, is now seen as the norm rather than the exception. Biophysical discoveries as well as computational algorithms and databases have reshaped our understanding of the often spectacular biomolecular dynamics enabled by soft linkers. Absence of such motion, as in so-called molecular rulers, also has desirable functional effects in protein architecture. We review here the historic discovery and current understanding of the nature of domains and their linkers from a structural, computational, and biophysical point of view. A number of emerging applications, based on the current understanding of the structural properties of peptides, are presented in the context of domain fusion of synthetic multifunctional chimeric proteins.
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Affiliation(s)
- Willy Wriggers
- School of Health Information Sciences and Institute of Molecular Medicine University of Texas, Health Science Center Houston, Houston, TX 77030, USA.
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114
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Lucas JI, Arnau V, Marín I. Comparative genomics and protein domain graph analyses link ubiquitination and RNA metabolism. J Mol Biol 2006; 357:9-17. [PMID: 16426638 DOI: 10.1016/j.jmb.2005.12.068] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2005] [Revised: 12/18/2005] [Accepted: 12/20/2005] [Indexed: 10/25/2022]
Abstract
The human gene parkin, known to cause familial Parkinson disease, as well as several other genes, likely involved in other neurodegenerative diseases or in cancer, encode proteins of the RBR family of ubiquitin ligases. Here, we describe the structural diversity of the RBR family in order to infer their functional roles. Of particular interest is a relationship detected between RBR-mediated ubiquitination and RNA metabolism: a few RBR proteins contain RNA binding domains and DEAH-box RNA helicase domains. Global protein domain graph analyses demonstrate that this connection is not RBR-specific, but instead many other proteins contain both ubiquitination and RNA-related domains. These proteins are present in animals, plants and fungi, suggesting that the link between these two cellular processes is ancient. Our results show that global bioinformatic approaches, involving comparative genomics and domain network analyses, may unearth novel functional relationships involving well-known and thoroughly studied groups of proteins.
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Affiliation(s)
- J Ignasi Lucas
- Departamento de Genética, Universidad de Valencia, Burjassot, Spain
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115
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Novinec M, Kordis D, Turk V, Lenarcic B. Diversity and Evolution of the Thyroglobulin Type-1 Domain Superfamily. Mol Biol Evol 2005; 23:744-55. [PMID: 16368776 DOI: 10.1093/molbev/msj082] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Multidomain proteins are gaining increasing consideration for their puzzling, flexible utilization in nature. The presence of the characteristic thyroglobulin type-1 (Tg1) domain as a protein module in a variety of multicellular organisms suggests pivotal roles for this building block. To gain insight into the evolution of Tg1 domains, we performed searches of protein, expressed sequence tag, and genome databases. Tg1 domains were found to be Metazoa specific, and we retrieved a total of 170 Tg1 domain-containing protein sequences. Their architectures revealed a wide taxonomic distribution of proteins containing Tg1 domains followed or preceded by secreted protein, acidic, rich in cysteines (SPARC)-type extracellular calcium-binding domains. Other proteins contained lineage-specific domain combinations of peptidase inhibitory modules or domains with different biological functions. Phylogenetic analysis showed that Tg1 domains are highly conserved within protein structures, whereas insertion into novel proteins is followed by rapid diversification. Seven different basic types of protein architecture containing the Tg1 domain were identified in vertebrates. We examined the evolution of these protein groups by combining Tg1 domain phylogeny with additional analyses based on other characteristic domains. Testicans and secreted modular calcium binding protein (SMOCs) evolved from invertebrate homologs by introduction of vertebrate-specific domains, nidogen evolved by insertion of a Tg1 domain into a preexisting architecture, and the remaining four have unique architectures. Thyroglobulin, Trops, and the major histocompatibility complex class II-associated invariant chain are vertebrate specific, while an insulin-like growth factor-binding protein and nidogen were also identified in urochordates. Among vertebrates, we observed differences in protein repertoires, which result from gene duplication and domain duplication. Members of five groups have been characterized at the molecular level. All exhibit subtle differences in their specificities and function either as peptidase inhibitors (thyropins), substrates, or both. As far as the sequence is concerned, only a few conserved residues were identified. In combination with structural data, our analysis shows that the Tg1 domain fold is highly adaptive and comprises a relatively well-conserved core surrounded by highly variable loops that account for its multipurpose function in the animal kingdom.
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Affiliation(s)
- Marko Novinec
- Department of Biochemistry and Molecular Biology, JoZef Stefan Institute, Jamova 39, Ljubljana, Slovenia
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116
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Björklund AK, Ekman D, Light S, Frey-Skött J, Elofsson A. Domain Rearrangements in Protein Evolution. J Mol Biol 2005; 353:911-23. [PMID: 16198373 DOI: 10.1016/j.jmb.2005.08.067] [Citation(s) in RCA: 138] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2005] [Revised: 08/19/2005] [Accepted: 08/26/2005] [Indexed: 10/25/2022]
Abstract
Most eukaryotic proteins are multi-domain proteins that are created from fusions of genes, deletions and internal repetitions. An investigation of such evolutionary events requires a method to find the domain architecture from which each protein originates. Therefore, we defined a novel measure, domain distance, which is calculated as the number of domains that differ between two domain architectures. Using this measure the evolutionary events that distinguish a protein from its closest ancestor have been studied and it was found that indels are more common than internal repetition and that the exchange of a domain is rare. Indels and repetitions are common at both the N and C-terminals while they are rare between domains. The evolution of the majority of multi-domain proteins can be explained by the stepwise insertions of single domains, with the exception of repeats that sometimes are duplicated several domains in tandem. We show that domain distances agree with sequence similarity and semantic similarity based on gene ontology annotations. In addition, we demonstrate the use of the domain distance measure to build evolutionary trees. Finally, the evolution of multi-domain proteins is exemplified by a closer study of the evolution of two protein families, non-receptor tyrosine kinases and RhoGEFs.
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Affiliation(s)
- Asa K Björklund
- Stockholm Bioinformatics Center, Stockholm University, SE-10691 Stockholm, Sweden
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117
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Abstract
We can now assign about two thirds of the sequences from completed genomes to as few as 1400 domain families for which structures are known and thus more ancient evolutionary relationships established. About 200 of these domain families are common to all kingdoms of life and account for nearly 50% of domain structure annotations in the genomes. Some of these domain families have been very extensively duplicated within a genome and combined with different domain partners giving rise to different multidomain proteins. The ways in which these domain combinations evolve tend to be specific to the organism so that less than 15% of the protein families found within a genome appear to be common to all kingdoms of life. Recent analyses of completed genomes, exploiting the structural data, have revealed the extent to which duplication of these domains and modifications of their functions can expand the functional repertoire of the organism, contributing to increasing complexity.
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Affiliation(s)
- Christine A Orengo
- Department of Biochemistry and Molecular Biology, University College, London WC1E 6BT, United Kingdom.
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118
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Pugalenthi G, Bhaduri A, Sowdhamini R. GenDiS: Genomic Distribution of protein structural domain Superfamilies. Nucleic Acids Res 2005; 33:D252-5. [PMID: 15608190 PMCID: PMC540041 DOI: 10.1093/nar/gki087] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Several proteins that have substantially diverged during evolution retain similar three-dimensional structures and biological function inspite of poor sequence identity. The database on Genomic Distribution of protein structural domain Superfamilies (GenDiS) provides record for the distribution of 4001 protein domains organized as 1194 structural superfamilies across 18 997 genomes at various levels of hierarchy in taxonomy. GenDiS database provides a survey of protein domains enlisted in sequence databases employing a 3-fold sequence search approach. Lineage-specific literature is obtained from the taxonomy database for individual protein members to provide a platform for performing genomic and phyletic studies across organisms. The database documents residual properties and provides alignments for the various superfamily members in genomes, offering insights into the rational design of experiments and for the better understanding of a superfamily. GenDiS database can be accessed at http://www.ncbs.res.in/~faculty/mini/gendis/home.html.
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Affiliation(s)
- Ganesan Pugalenthi
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore 560 065, Karnataka, India
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119
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Haas BJ, Wortman JR, Ronning CM, Hannick LI, Smith RK, Maiti R, Chan AP, Yu C, Farzad M, Wu D, White O, Town CD. Complete reannotation of the Arabidopsis genome: methods, tools, protocols and the final release. BMC Biol 2005; 3:7. [PMID: 15784138 PMCID: PMC1082884 DOI: 10.1186/1741-7007-3-7] [Citation(s) in RCA: 109] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2004] [Accepted: 03/22/2005] [Indexed: 11/29/2022] Open
Abstract
Background Since the initial publication of its complete genome sequence, Arabidopsis thaliana has become more important than ever as a model for plant research. However, the initial genome annotation was submitted by multiple centers using inconsistent methods, making the data difficult to use for many applications. Results Over the course of three years, TIGR has completed its effort to standardize the structural and functional annotation of the Arabidopsis genome. Using both manual and automated methods, Arabidopsis gene structures were refined and gene products were renamed and assigned to Gene Ontology categories. We present an overview of the methods employed, tools developed, and protocols followed, summarizing the contents of each data release with special emphasis on our final annotation release (version 5). Conclusion Over the entire period, several thousand new genes and pseudogenes were added to the annotation. Approximately one third of the originally annotated gene models were significantly refined yielding improved gene structure annotations, and every protein-coding gene was manually inspected and classified using Gene Ontology terms.
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Affiliation(s)
- Brian J Haas
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Jennifer R Wortman
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Catherine M Ronning
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Linda I Hannick
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Roger K Smith
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Rama Maiti
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Agnes P Chan
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Chunhui Yu
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Maryam Farzad
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Dongying Wu
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Owen White
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
| | - Christopher D Town
- The Institute for Genomic Research, 9172 Medical Center Drive, Rockville, Maryland, 20850, USA
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120
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Vogel C, Teichmann SA, Pereira-Leal J. The relationship between domain duplication and recombination. J Mol Biol 2004; 346:355-65. [PMID: 15663950 DOI: 10.1016/j.jmb.2004.11.050] [Citation(s) in RCA: 123] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2004] [Revised: 11/18/2004] [Accepted: 11/19/2004] [Indexed: 10/26/2022]
Abstract
Protein domains represent the basic evolutionary units that form proteins. Domain duplication and shuffling by recombination are probably the most important forces driving protein evolution and hence the complexity of the proteome. While the duplication of whole genes as well as domain-encoding exons increases the abundance of domains in the proteome, domain shuffling increases versatility, i.e. the number of distinct contexts in which a domain can occur. Here, we describe a comprehensive, genome-wide analysis of the relationship between these two processes. We observe a strong and robust correlation between domain versatility and abundance: domains that occur more often also have many different combination partners. This supports the view that domain recombination occurs in a random way. However, we do not observe all the different combinations that are expected from a simple random recombination scenario, and this is due to frequent duplication of specific domain combinations. When we simulate the evolution of the protein repertoire considering stochastic recombination of domains followed by extensive duplication of the combinations, we approximate the observed data well. Our analyses are consistent with a stochastic process that governs domain recombination and thus protein divergence with respect to domains within a polypeptide chain. At the same time, they support a scenario in which domain combinations are formed only once during the evolution of the protein repertoire, and are then duplicated to various extents. The extent of duplication of different combinations varies widely and, in nature, will depend on selection for the domain combination based on its function. Some of the pair-wise domain combinations that are highly duplicated also recur frequently with other partner domains, and thus represent evolutionary units larger than single protein domains, which we term "supra-domains".
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Affiliation(s)
- Christine Vogel
- MRC Laboratory of Molecular Biology, Hills Rd, Cambridge CB2 2QH, UK.
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121
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Littler SJ, Hubbard SJ. Conservation of orientation and sequence in protein domain--domain interactions. J Mol Biol 2004; 345:1265-79. [PMID: 15644220 DOI: 10.1016/j.jmb.2004.11.011] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2004] [Accepted: 11/05/2004] [Indexed: 11/16/2022]
Abstract
The repertoire of naturally occurring protein structures is usually characterised in structural terms at the domain level by their constituent folds. As structure is acknowledged to be an important stepping stone to the understanding of protein function, an appreciation of how individual domain interactions are built to form complete, functional protein structures is essential. A comprehensive study of protein domain interactions has been undertaken, covering all those observed in known structures, as well as those predicted to occur in 46 completed genome sequences from all three domains of life. In particular, we examine the promiscuity of protein domains characterised by SCOP superfamilies in terms of their interacting partners, the surface they use to form these interactions, and the relative orientations of their domain partners. Protein domains are shown to display a variety of behaviours, ranging from high promiscuity to absolute monogamy of domain surface employed, with both multiple and single domain partners. In addition, the conservation of sequence and volume at domain interface surfaces is observed to be significantly higher than at accessible surface in general, acting as a powerful potential predictor for domain interactions. We also examine the separation of interacting domains in protein sequence, showing that standard thresholds of 30 amino acid residues lead to a significant false positive rate, and an even more significant false negative rate of approximately 40%. These data suggest that there may be many more than the 2000 domain--domain interactions that have not yet been observed structurally, and we provide a top 30 hit-list of putative domain interactions which should be targeted.
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Affiliation(s)
- Stephen J Littler
- Faculty of Life Sciences, The University of Manchester, Jackson's Mill, P.O. Box 88, Manchester M60 1QD, UK
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122
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Abstract
MOTIVATION In this paper, we shall examine the evolution of domain architectures across 62 genomes of known phylogeny including all kingdoms of life. We look in particular at the possibility of convergent evolution, with a view to determining the extent to which the architectures observed in the genomes are due to functional necessity or evolutionary descent. We used domains of known structure, because from this and other information we know their evolutionary relationships. We use a range of methods including phylogenetic grouping, sequence similarity/alignment, mutation rates and comparative genomics to approach this difficult problem from several angles. RESULTS Although we do not claim an exhaustive analysis, we conclude that between 0.4 and 4% of sequences are involved in convergent evolution of domain architectures, and expect the actual number to be close to the lower bound. We also made two incidental observations, albeit on a small sample: the events leading to convergent evolution appear to be random with no functional or structural preferences, and changes in the number of tandem repeat domains occur more readily than changes which alter the domain composition. CONCLUSION The principal conclusion is that the observed domain architectures of the sequences in the genomes are driven by evolutionary descent rather than functional necessity. CONTACT gough@supfam.org.
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Affiliation(s)
- Julian Gough
- RIKEN Genomic Sciences Centre, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan.
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123
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Shiozawa K, Maita N, Tomii K, Seto A, Goda N, Akiyama Y, Shimizu T, Shirakawa M, Hiroaki H. Structure of the N-terminal domain of PEX1 AAA-ATPase. Characterization of a putative adaptor-binding domain. J Biol Chem 2004; 279:50060-8. [PMID: 15328346 DOI: 10.1074/jbc.m407837200] [Citation(s) in RCA: 61] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Peroxisomes are responsible for several pathways in primary metabolism, including beta-oxidation and lipid biosynthesis. PEX1 and PEX6 are hexameric AAA-type ATPases, both of which are indispensable in targeting over 50 peroxisomal resident proteins from the cytosol to the peroxisomes. Although the tandem AAA-ATPase domains in the central region of PEX1 and PEX6 are highly similar, the N-terminal sequences are unique. To better understand the distinct molecular function of these two proteins, we analyzed the unique N-terminal domain (NTD) of PEX1. Extensive computational analysis revealed weak similarity (<10% identity) of PEX1 NTD to the N-terminal domains of other membrane-related type II AAA-ATPases, such as VCP (p97) and NSF. We have determined the crystal structure of mouse PEX1 NTD at 2.05-A resolution, which clearly demonstrated that the domain belongs to the double-psi-barrel fold family found in the other AAA-ATPases. The N-domains of both VCP and NSF are structural neighbors of PEX1 NTD with a 2.7- and 2.1-A root mean square deviation of backbone atoms, respectively. Our findings suggest that the supradomain architecture, which is composed of a single N-terminal domain followed by tandem AAA domains, is a common feature of organellar membrane-associating AAA-ATPases. We propose that PEX1 functions as a protein unfoldase in peroxisomal biogenesis, using its N-terminal putative adaptor-binding domain.
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Affiliation(s)
- Kumiko Shiozawa
- Graduate School of Integrated Science, Yokohama City University, 1-7-29 Suehiro, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
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124
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Vogel C, Bashton M, Kerrison ND, Chothia C, Teichmann SA. Structure, function and evolution of multidomain proteins. Curr Opin Struct Biol 2004; 14:208-16. [PMID: 15093836 DOI: 10.1016/j.sbi.2004.03.011] [Citation(s) in RCA: 286] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Proteins are composed of evolutionary units called domains; the majority of proteins consist of at least two domains. These domains and nature of their interactions determine the function of the protein. The roles that combinations of domains play in the formation of the protein repertoire have been found by analysis of domain assignments to genome sequences. Additional findings on the geometry of domains have been gained from examination of three-dimensional protein structures. Future work will require a domain-centric functional classification scheme and efforts to determine structures of domain combinations.
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Affiliation(s)
- Christine Vogel
- MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 2QH, UK.
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125
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Mizuta S, Munakata H, Aimaiti A, Oosawa K, Shimizu T. Evaluation of the color-coding method for searching tandem repeats in prokaryotic genomes. CHEM-BIO INFORMATICS JOURNAL 2004. [DOI: 10.1273/cbij.4.133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Satoshi Mizuta
- Department of Electronic and Information System Engineering, Faculty of Science and Technology, Hirosaki University
| | - Hikaru Munakata
- Department of Electronic and Information System Engineering, Faculty of Science and Technology, Hirosaki University
| | - Abulimiti Aimaiti
- Department of Electronic and Information System Engineering, Faculty of Science and Technology, Hirosaki University
| | - Kenji Oosawa
- Department of Nano-Material Systems, Graduate School of Engineering, Gunma University
| | - Toshio Shimizu
- Department of Electronic and Information System Engineering, Faculty of Science and Technology, Hirosaki University
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