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Malik AJ, Langer D, Verma CS, Poole AM, Allison JR. Structome: a tool for the rapid assembly of datasets for structural phylogenetics. BIOINFORMATICS ADVANCES 2023; 3:vbad134. [PMID: 38046099 PMCID: PMC10692761 DOI: 10.1093/bioadv/vbad134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 08/17/2023] [Accepted: 09/29/2023] [Indexed: 12/05/2023]
Abstract
Summary Protein structures carry signal of common ancestry and can therefore aid in reconstructing their evolutionary histories. To expedite the structure-informed inference process, a web server, Structome, has been developed that allows users to rapidly identify protein structures similar to a query protein and to assemble datasets useful for structure-based phylogenetics. Structome was created by clustering ∼ 94 % of the structures in RCSB PDB using 90% sequence identity and representing each cluster by a centroid structure. Structure similarity between centroid proteins was calculated, and annotations from PDB, SCOP, and CATH were integrated. To illustrate utility, an H3 histone was used as a query, and results show that the protein structures returned by Structome span both sequence and structural diversity of the histone fold. Additionally, the pre-computed nexus-formatted distance matrix, provided by Structome, enables analysis of evolutionary relationships between proteins not identifiable using searches based on sequence similarity alone. Our results demonstrate that, beginning with a single structure, Structome can be used to rapidly generate a dataset of structural neighbours and allows deep evolutionary history of proteins to be studied. Availability and Implementation Structome is available at: https://structome.bii.a-star.edu.sg.
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Affiliation(s)
- Ashar J Malik
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671 Singapore
| | - Desiree Langer
- School of Biological Sciences, University of Auckland, 1142 Auckland, New Zealand
| | - Chandra S Verma
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671 Singapore
- Department of Biological Sciences, National University of Singapore, 117543 Singapore
- School of Biological Sciences, Nanyang Technological University, 637551 Singapore
| | - Anthony M Poole
- School of Biological Sciences, University of Auckland, 1142 Auckland, New Zealand
- Digital Life Institute, University of Auckland, Auckland 1142, New Zealand
| | - Jane R Allison
- School of Biological Sciences, University of Auckland, 1142 Auckland, New Zealand
- Digital Life Institute, University of Auckland, Auckland 1142, New Zealand
- Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, 1142 Auckland, New Zealand
- Biomolecular Interaction Centre, University of Canterbury, 8041 Christchurch, New Zealand
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2
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Webb DR. Soluble Immune Response Suppressor (SIRS): Reassessing the immunosuppressant potential of an elusive peptide. Biochem Pharmacol 2016; 117:1-9. [PMID: 27038657 DOI: 10.1016/j.bcp.2016.03.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Accepted: 03/28/2016] [Indexed: 11/30/2022]
Abstract
A previously studied immunosuppressive cytokine, Soluble Immune Response Suppressor (SIRS), may have relevance to current studies of immune suppression in a variety of human disease states. Despite extensive efforts using experimental models, mainly in mice, much remains to be discovered as to how autoimmune cells in mice and humans escape normal regulation and, conversely, how tumor cells evade evoking an immune response. It is the contention of this commentary that the literature pre-2000 contain results that might inform current studies. The broadly immunosuppressive protein, SIRS, was studied extensively from the 1970s to 1990s and culminated in the determination of the n-terminal 21mer sequence of this 15kDa protein which had high homology to the short neurotoxins from sea snakes, that are canonical members of the three finger neurotoxin superfamily (3FTx). It was not until 2007 that the prophylactic administration of the synthetic N-terminal peptide of the SIRS 21mer, identical to the published sequence, was reported to inhibit or delay the development of two autoimmune diseases in mice: experimental allergic encephalomyelitis (EAE) and type I diabetes (T1D). These findings were consistent with other studies of the 3FTx superfamily as important probes in the study of mammalian pharmacology. It is the perspective of this commentary that SIRS, SIRS peptide and the anti-peptide mAb, represent useful, pharmacologically-active probes for the study of the immune response as well as in the potential treatment of autoimmune, inflammatory diseases and cancer.
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Affiliation(s)
- David R Webb
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, 10550 N. Torrey Pines Rd, La Jolla, CA 92037, United States.
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3
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Stamm M, Forrest LR. Structure alignment of membrane proteins: Accuracy of available tools and a consensus strategy. Proteins 2015; 83:1720-32. [PMID: 26178143 DOI: 10.1002/prot.24857] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Revised: 05/07/2015] [Accepted: 06/07/2015] [Indexed: 12/31/2022]
Abstract
Protein structure alignment methods are used for the detection of evolutionary and functionally related positions in proteins. A wide array of different methods are available, but the choice of the best method is often not apparent to the user. Several studies have assessed the alignment accuracy and consistency of structure alignment methods, but none of these explicitly considered membrane proteins, which are important targets for drug development and have distinct structural features. Here, we compared 13 widely used pairwise structural alignment methods on a test set of homologous membrane protein structures (called HOMEP3). Each pair of structures was aligned and the corresponding sequence alignment was used to construct homology models. The model accuracy compared to the known structures was assessed using scoring functions not incorporated in the tested structural alignment methods. The analysis shows that fragment-based approaches such as FR-TM-align are the most useful for aligning structures of membrane proteins. Moreover, fragment-based approaches are more suitable for comparison of protein structures that have undergone large conformational changes. Nevertheless, no method was clearly superior to all other methods. Additionally, all methods lack a measure to rate the reliability of a position within a structure alignment. To solve both of these problems, we propose a consensus-type approach, combining alignments from four different methods, namely FR-TM-align, DaliLite, MATT, and FATCAT. Agreement between the methods is used to assign confidence values to each position of the alignment. Overall, we conclude that there remains scope for the improvement of structural alignment methods for membrane proteins.
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Affiliation(s)
- Marcus Stamm
- Computational Structural Biology Group, Max Planck Institute of Biophysics, Frankfurt Am Main, Germany
| | - Lucy R Forrest
- Computational Structural Biology Group, Max Planck Institute of Biophysics, Frankfurt Am Main, Germany.,Computational Structural Biology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland
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4
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Wang HW, Chu CH, Wang WC, Pai TW. A local average distance descriptor for flexible protein structure comparison. BMC Bioinformatics 2014; 15:95. [PMID: 24694083 PMCID: PMC3992163 DOI: 10.1186/1471-2105-15-95] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2013] [Accepted: 03/22/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Protein structures are flexible and often show conformational changes upon binding to other molecules to exert biological functions. As protein structures correlate with characteristic functions, structure comparison allows classification and prediction of proteins of undefined functions. However, most comparison methods treat proteins as rigid bodies and cannot retrieve similarities of proteins with large conformational changes effectively. RESULTS In this paper, we propose a novel descriptor, local average distance (LAD), based on either the geodesic distances (GDs) or Euclidean distances (EDs) for pairwise flexible protein structure comparison. The proposed method was compared with 7 structural alignment methods and 7 shape descriptors on two datasets comprising hinge bending motions from the MolMovDB, and the results have shown that our method outperformed all other methods regarding retrieving similar structures in terms of precision-recall curve, retrieval success rate, R-precision, mean average precision and F1-measure. CONCLUSIONS Both ED- and GD-based LAD descriptors are effective to search deformed structures and overcome the problems of self-connection caused by a large bending motion. We have also demonstrated that the ED-based LAD is more robust than the GD-based descriptor. The proposed algorithm provides an alternative approach for blasting structure database, discovering previously unknown conformational relationships, and reorganizing protein structure classification.
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Affiliation(s)
| | | | | | - Tun-Wen Pai
- Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung, Taiwan.
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5
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Going over the three dimensional protein structure similarity problem. Artif Intell Rev 2013. [DOI: 10.1007/s10462-013-9416-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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6
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Raffaele S, Perraki A, Mongrand S. The Remorin C-terminal Anchor was shaped by convergent evolution among membrane binding domains. PLANT SIGNALING & BEHAVIOR 2013; 8:e23207. [PMID: 23299327 PMCID: PMC3676492 DOI: 10.4161/psb.23207] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
StREM1.3 Remorin is a well-established plant raftophilic protein, predominantly associated with sterol- and sphingolipid-rich membrane rafts. We recently identified a C-terminal domain (RemCA) required and sufficient for StREM1.3 anchoring to the plasma membrane. Here, we report a search for homologs and analogs of RemCA domain in publicly available protein sequence and structure databases. We could not identify RemCA homologous domains outside the Remorin family but we identified domains sharing bias in amino-acid composition and predicted structural fold with RemCA in bacterial, viral and animal proteins. These results suggest that RemCA emerged by convergent evolution among unrelated membrane binding domain.
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Affiliation(s)
- Sylvain Raffaele
- Laboratoire des Interactions Plantes-Microorganismes (LIPM); UMR441 INRA-CNRS; Castanet-Tolosan, France
- Correspondence to: Sylvain Raffaele,
| | - Artemis Perraki
- Laboratoire de Biogenese Membraniare; UMR 5200 CNRS; Université Bordeaux Segalen; INRA Bordeaux Aquitaine BP81; Villenave d'Ornon Cédex, France
| | - Sébastien Mongrand
- Laboratoire de Biogenese Membraniare; UMR 5200 CNRS; Université Bordeaux Segalen; INRA Bordeaux Aquitaine BP81; Villenave d'Ornon Cédex, France
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7
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Wilkins AD, Bachman BJ, Erdin S, Lichtarge O. The use of evolutionary patterns in protein annotation. Curr Opin Struct Biol 2012; 22:316-25. [PMID: 22633559 DOI: 10.1016/j.sbi.2012.05.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2012] [Accepted: 05/01/2012] [Indexed: 01/13/2023]
Abstract
With genomic data skyrocketing, their biological interpretation remains a serious challenge. Diverse computational methods address this problem by pointing to the existence of recurrent patterns among sequence, structure, and function. These patterns emerge naturally from evolutionary variation, natural selection, and divergence--the defining features of biological systems--and they identify molecular events and shapes that underlie specificity of function and allosteric communication. Here we review these methods, and the patterns they identify in case studies and in proteome-wide applications, to infer and rationally redesign function.
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Affiliation(s)
- Angela D Wilkins
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
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8
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Abstract
Motivation: Structural alignment methods are widely used to generate gold standard alignments for improving multiple sequence alignments and transferring functional annotations, as well as for assigning structural distances between proteins. However, the correctness of the alignments generated by these methods is difficult to assess objectively since little is known about the exact evolutionary history of most proteins. Since homology is an equivalence relation, an upper bound on alignment quality can be found by assessing the consistency of alignments. Measuring the consistency of current methods of structure alignment and determining the causes of inconsistencies can, therefore, provide information on the quality of current methods and suggest possibilities for further improvement. Results: We analyze the self-consistency of seven widely-used structural alignment methods (SAP, TM-align, Fr-TM-align, MAMMOTH, DALI, CE and FATCAT) on a diverse, non-redundant set of 1863 domains from the SCOP database and demonstrate that even for relatively similar proteins the degree of inconsistency of the alignments on a residue level is high (30%). We further show that levels of consistency vary substantially between methods, with two methods (SAP and Fr-TM-align) producing more consistent alignments than the rest. Inconsistency is found to be higher near gaps and for proteins of low structural complexity, as well as for helices. The ability of the methods to identify good structural alignments is also assessed using geometric measures, for which FATCAT (flexible mode) is found to be the best performer despite being highly inconsistent. We conclude that there is substantial scope for improving the consistency of structural alignment methods. Contact:msadows@nimr.mrc.ac.uk Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- M I Sadowski
- Division of Mathematical Biology, MRC National Institute for Medical Research, The Ridgeway, Mill Hill, London, UK
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9
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Kalaimathy S, Sowdhamini R, Kanagarajadurai K. Critical assessment of structure-based sequence alignment methods at distant relationships. Brief Bioinform 2011; 12:163-75. [PMID: 21422071 DOI: 10.1093/bib/bbq025] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Accurate sequence alignments are crucial for modelling and to provide an evolutionary picture of related proteins. It is well-known that alignments are hard to obtain during distant relationships. Three thousand and fifty-two alignments of 218 pairs of protein domain structural entries, with <40% sequence identity, belonging to different structural classes, of diverse domain sizes and length-rigid/variable domains were performed using 12 programs. Structural parameters such as root mean square deviation, secondary-structural content and equivalences were considered for critical assessment. Methods that compare fragments and permit twists and translations align well during distant relationships and length variations.
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Affiliation(s)
- Singarevelu Kalaimathy
- National Centre for Biological Sciences (TIFR), GKVK Campus, Bellary Road, Bangalore 560065, India
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10
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Murai MJ, Chruszcz M, Reddy G, Grembecka J, Cierpicki T. Crystal structure of menin reveals binding site for mixed lineage leukemia (MLL) protein. J Biol Chem 2011; 286:31742-8. [PMID: 21757704 DOI: 10.1074/jbc.m111.258186] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Menin is a tumor suppressor protein that is encoded by the MEN1 (multiple endocrine neoplasia 1) gene and controls cell growth in endocrine tissues. Importantly, menin also serves as a critical oncogenic cofactor of MLL (mixed lineage leukemia) fusion proteins in acute leukemias. Direct association of menin with MLL fusion proteins is required for MLL fusion protein-mediated leukemogenesis in vivo, and this interaction has been validated as a new potential therapeutic target for development of novel anti-leukemia agents. Here, we report the first crystal structure of menin homolog from Nematostella vectensis. Due to a very high sequence similarity, the Nematostella menin is a close homolog of human menin, and these two proteins likely have very similar structures. Menin is predominantly an α-helical protein with the protein core comprising three tetratricopeptide motifs that are flanked by two α-helical bundles and covered by a β-sheet motif. A very interesting feature of menin structure is the presence of a large central cavity that is highly conserved between Nematostella and human menin. By employing site-directed mutagenesis, we have demonstrated that this cavity constitutes the binding site for MLL. Our data provide a structural basis for understanding the role of menin as a tumor suppressor protein and as an oncogenic co-factor of MLL fusion proteins. It also provides essential structural information for development of inhibitors targeting the menin-MLL interaction as a novel therapeutic strategy in MLL-related leukemias.
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Affiliation(s)
- Marcelo J Murai
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, USA
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11
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Nguyen MN, Tan KP, Madhusudhan MS. CLICK--topology-independent comparison of biomolecular 3D structures. Nucleic Acids Res 2011; 39:W24-8. [PMID: 21602266 PMCID: PMC3125785 DOI: 10.1093/nar/gkr393] [Citation(s) in RCA: 100] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2011] [Revised: 04/19/2011] [Accepted: 05/03/2011] [Indexed: 01/28/2023] Open
Abstract
Our server, CLICK: http://mspc.bii.a-star.edu.sg/click, is capable of superimposing the 3D structures of any pair of biomolecules (proteins, DNA, RNA, etc.). The server makes use of the Cartesian coordinates of the molecules with the option of using other structural features such as secondary structure, solvent accessible surface area and residue depth to guide the alignment. CLICK first looks for cliques of points (3-7 residues) that are structurally similar in the pair of structures to be aligned. Using these local similarities, a one-to-one equivalence is charted between the residues of the two structures. A least square fit then superimposes the two structures. Our method is especially powerful in establishing protein relationships by detecting similarities in structural subdomains, domains and topological variants. CLICK has been extensively benchmarked and compared with other popular methods for protein and RNA structural alignments. In most cases, CLICK alignments were statistically significantly better in terms of structure overlap. The method also recognizes conformational changes that may have occurred in structural domains or subdomains in one structure with respect to the other. For this purpose, the server produces complementary alignments to maximize the extent of detectable similarity. Various examples showcase the utility of our web server.
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Affiliation(s)
- M. N. Nguyen
- Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Department of Biological Sciences, National University of Singapore and School of Biological Sciences, Nanyang Technological University, Singapore
| | - K. P. Tan
- Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Department of Biological Sciences, National University of Singapore and School of Biological Sciences, Nanyang Technological University, Singapore
| | - M. S. Madhusudhan
- Bioinformatics Institute, 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Department of Biological Sciences, National University of Singapore and School of Biological Sciences, Nanyang Technological University, Singapore
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12
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Nguyen MN, Madhusudhan MS. Biological insights from topology independent comparison of protein 3D structures. Nucleic Acids Res 2011; 39:e94. [PMID: 21596786 PMCID: PMC3152366 DOI: 10.1093/nar/gkr348] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Comparing and classifying the three-dimensional (3D) structures of proteins is of crucial importance to molecular biology, from helping to determine the function of a protein to determining its evolutionary relationships. Traditionally, 3D structures are classified into groups of families that closely resemble the grouping according to their primary sequence. However, significant structural similarities exist at multiple levels between proteins that belong to these different structural families. In this study, we propose a new algorithm, CLICK, to capture such similarities. The method optimally superimposes a pair of protein structures independent of topology. Amino acid residues are represented by the Cartesian coordinates of a representative point (usually the Cα atom), side chain solvent accessibility, and secondary structure. Structural comparison is effected by matching cliques of points. CLICK was extensively benchmarked for alignment accuracy on four different sets: (i) 9537 pair-wise alignments between two structures with the same topology; (ii) 64 alignments from set (i) that were considered to constitute difficult alignment cases; (iii) 199 pair-wise alignments between proteins with similar structure but different topology; and (iv) 1275 pair-wise alignments of RNA structures. The accuracy of CLICK alignments was measured by the average structure overlap score and compared with other alignment methods, including HOMSTRAD, MUSTANG, Geometric Hashing, SALIGN, DALI, GANGSTA+, FATCAT, ARTS and SARA. On average, CLICK produces pair-wise alignments that are either comparable or statistically significantly more accurate than all of these other methods. We have used CLICK to uncover relationships between (previously) unrelated proteins. These new biological insights include: (i) detecting hinge regions in proteins where domain or sub-domains show flexibility; (ii) discovering similar small molecule binding sites from proteins of different folds and (iii) discovering topological variants of known structural/sequence motifs. Our method can generally be applied to compare any pair of molecular structures represented in Cartesian coordinates as exemplified by the RNA structure superimposition benchmark.
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Affiliation(s)
- Minh N Nguyen
- Bioinformatics Institute, 30 Biopolis Street, #07-01 Matrix, Singapore 138671
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13
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Erdin S, Lisewski AM, Lichtarge O. Protein function prediction: towards integration of similarity metrics. Curr Opin Struct Biol 2011; 21:180-8. [PMID: 21353529 DOI: 10.1016/j.sbi.2011.02.001] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2011] [Accepted: 02/03/2011] [Indexed: 11/16/2022]
Abstract
Genomic centers discover increasingly many protein sequences and structures, but not necessarily their full biological functions. Thus, currently, less than one percent of proteins have experimentally verified biochemical activities. To fill this gap, function prediction algorithms apply metrics of similarity between proteins on the premise that those sufficiently alike in sequence, or structure, will perform identical functions. Although high sensitivity is elusive, network analyses that integrate these metrics together hold the promise of rapid gains in function prediction specificity.
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Affiliation(s)
- Serkan Erdin
- Department of Molecular and Human Genetics, 1 Baylor Plaza, Baylor College of Medicine, Houston, TX 77030, USA
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14
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Prlic A, Bliven S, Rose PW, Bluhm WF, Bizon C, Godzik A, Bourne PE. Pre-calculated protein structure alignments at the RCSB PDB website. Bioinformatics 2010; 26:2983-5. [PMID: 20937596 PMCID: PMC3003546 DOI: 10.1093/bioinformatics/btq572] [Citation(s) in RCA: 149] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Summary: With the continuous growth of the RCSB Protein Data Bank (PDB), providing an up-to-date systematic structure comparison of all protein structures poses an ever growing challenge. Here, we present a comparison tool for calculating both 1D protein sequence and 3D protein structure alignments. This tool supports various applications at the RCSB PDB website. First, a structure alignment web service calculates pairwise alignments. Second, a stand-alone application runs alignments locally and visualizes the results. Third, pre-calculated 3D structure comparisons for the whole PDB are provided and updated on a weekly basis. These three applications allow users to discover novel relationships between proteins available either at the RCSB PDB or provided by the user. Availability and Implementation: A web user interface is available at http://www.rcsb.org/pdb/workbench/workbench.do. The source code is available under the LGPL license from http://www.biojava.org. A source bundle, prepared for local execution, is available from http://source.rcsb.org Contact:andreas@sdsc.edu; pbourne@ucsd.edu
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Affiliation(s)
- Andreas Prlic
- San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, Mailcode 0505 La Jolla, CA 92093-0505, USA.
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15
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Ren J, Sainsbury S, Nettleship JE, Saunders NJ, Owens RJ. The crystal structure of NGO0477 from Neisseria gonorrhoeae reveals a novel protein fold incorporating a helix-turn-helix motif. Proteins 2010; 78:1798-802. [PMID: 20196080 DOI: 10.1002/prot.22698] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Jingshan Ren
- The Oxford Protein Production Facility and Division of Structural Biology, University of Oxford, Oxford OX3 7BN, United Kingdom
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16
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Abstract
Our web site (http://ekhidna.biocenter.helsinki.fi/dali_server) runs the Dali program for protein structure comparison. The web site consists of three parts: (i) the Dali server compares newly solved structures against structures in the Protein Data Bank (PDB), (ii) the Dali database allows browsing precomputed structural neighbourhoods and (iii) the pairwise comparison generates suboptimal alignments for a pair of structures. Each part has its own query form and a common format for the results page. The inputs are either PDB identifiers or novel structures uploaded by the user. The results pages are hyperlinked to aid interactive analysis. The web interface is simple and easy to use. The key purpose of interactive analysis is to check whether conserved residues line up in multiple structural alignments and how conserved residues and ligands cluster together in multiple structure superimpositions. In favourable cases, protein structure comparison can lead to evolutionary discoveries not detected by sequence analysis.
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Affiliation(s)
- Liisa Holm
- Institute of Biotechnology and Department of Biosciences, University of Helsinki, Helsinki, Finland.
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17
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Veeramalai M, Gilbert D, Valiente G. An optimized TOPS+ comparison method for enhanced TOPS models. BMC Bioinformatics 2010; 11:138. [PMID: 20236520 PMCID: PMC2858036 DOI: 10.1186/1471-2105-11-138] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2009] [Accepted: 03/17/2010] [Indexed: 11/28/2022] Open
Abstract
Background Although methods based on highly abstract descriptions of protein structures, such as VAST and TOPS, can perform very fast protein structure comparison, the results can lack a high degree of biological significance. Previously we have discussed the basic mechanisms of our novel method for structure comparison based on our TOPS+ model (Topological descriptions of Protein Structures Enhanced with Ligand Information). In this paper we show how these results can be significantly improved using parameter optimization, and we call the resulting optimised TOPS+ method as advanced TOPS+ comparison method i.e. advTOPS+. Results We have developed a TOPS+ string model as an improvement to the TOPS [1-3] graph model by considering loops as secondary structure elements (SSEs) in addition to helices and strands, representing ligands as first class objects, and describing interactions between SSEs, and SSEs and ligands, by incoming and outgoing arcs, annotating SSEs with the interaction direction and type. Benchmarking results of an all-against-all pairwise comparison using a large dataset of 2,620 non-redundant structures from the PDB40 dataset [4] demonstrate the biological significance, in terms of SCOP classification at the superfamily level, of our TOPS+ comparison method. Conclusions Our advanced TOPS+ comparison shows better performance on the PDB40 dataset [4] compared to our basic TOPS+ method, giving 90% accuracy for SCOP alpha+beta; a 6% increase in accuracy compared to the TOPS and basic TOPS+ methods. It also outperforms the TOPS, basic TOPS+ and SSAP comparison methods on the Chew-Kedem dataset [5], achieving 98% accuracy. Software Availability The TOPS+ comparison server is available at http://balabio.dcs.gla.ac.uk/mallika/WebTOPS/.
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Affiliation(s)
- Mallika Veeramalai
- Joint Center for Molecular Modeling, Sanford-Burnham Medical Research Institute, La Jolla, CA 92037, USA.
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18
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Malygin AA, Bondarenko EI, Ivanisenko VA, Protopopova EV, Karpova GG, Loktev VB. C-terminal fragment of human laminin-binding protein contains a receptor domain for Venezuelan equine encephalitis and tick-borne encephalitis viruses. BIOCHEMISTRY (MOSCOW) 2010; 74:1328-36. [DOI: 10.1134/s0006297909120050] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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19
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Valas RE, Bourne PE. Structural analysis of polarizing indels: an emerging consensus on the root of the tree of life. Biol Direct 2009; 4:30. [PMID: 19706177 PMCID: PMC3224940 DOI: 10.1186/1745-6150-4-30] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2009] [Accepted: 08/25/2009] [Indexed: 11/18/2022] Open
Abstract
Background The root of the tree of life has been a holy grail ever since Darwin first used the tree as a metaphor for evolution. New methods seek to narrow down the location of the root by excluding it from branches of the tree of life. This is done by finding traits that must be derived, and excluding the root from the taxa those traits cover. However the two most comprehensive attempts at this strategy, performed by Cavalier-Smith and Lake et al., have excluded each other's rootings. Results The indel polarizations of Lake et al. rely on high quality alignments between paralogs that diverged before the last universal common ancestor (LUCA). Therefore, sequence alignment artifacts may skew their conclusions. We have reviewed their data using protein structure information where available. Several of the conclusions are quite different when viewed in the light of structure which is conserved over longer evolutionary time scales than sequence. We argue there is no polarization that excludes the root from all Gram-negatives, and that polarizations robustly exclude the root from the Archaea. Conclusion We conclude that there is no contradiction between the polarization datasets. The combination of these datasets excludes the root from every possible position except near the Chloroflexi. Reviewers This article was reviewed by Greg Fournier (nominated by J. Peter Gogarten), Purificación López-García, and Eugene Koonin.
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Affiliation(s)
- Ruben E Valas
- Bioinformatics Program, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
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Hasegawa H, Holm L. Advances and pitfalls of protein structural alignment. Curr Opin Struct Biol 2009; 19:341-8. [PMID: 19481444 DOI: 10.1016/j.sbi.2009.04.003] [Citation(s) in RCA: 303] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2009] [Accepted: 04/16/2009] [Indexed: 11/30/2022]
Abstract
Structure comparison opens a window into the distant past of protein evolution, which has been unreachable by sequence comparison alone. With 55,000 entries in the Protein Data Bank and about 500 new structures added each week, automated processing, comparison, and classification are necessary. A variety of methods use different representations, scoring functions, and optimization algorithms, and they generate contradictory results even for moderately distant structures. Sequence mutations, insertions, and deletions are accommodated by plastic deformations of the common core, retaining the precise geometry of the active site, and peripheral regions may refold completely. Therefore structure comparison methods that allow for flexibility and plasticity generate the most biologically meaningful alignments. Active research directions include both the search for fold invariant features and the modeling of structural transitions in evolution. Advances have been made in algorithmic robustness, multiple alignment, and speeding up database searches.
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Affiliation(s)
- Hitomi Hasegawa
- Institute of Biotechnology, University of Helsinki, P.O. Box 56 (Viikinkaari 5), 00014 University of Helsinki, Finland
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Veeramalai M, Gilbert D. A novel method for comparing topological models of protein structures enhanced with ligand information. Bioinformatics 2008; 24:2698-705. [DOI: 10.1093/bioinformatics/btn518] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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