Successful discrimination of protein interactions
We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our algorithm, SmoothDock, comprises four steps: (1) we perform rigid body docking using the program DOT, keeping the top 20,000 structures as r...
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Published in | Proteins, structure, function, and bioinformatics Vol. 52; no. 1; pp. 92 - 97 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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01.07.2003
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Abstract | We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our algorithm, SmoothDock, comprises four steps: (1) we perform rigid body docking using the program DOT, keeping the top 20,000 structures as ranked by surface complementarity; (2) we rerank these structures according to a free energy estimate that includes both desolvation and electrostatics and retain the top 2000 complexes; (3) we cluster the filtered complexes using a pairwise root‐mean‐square deviation (RMSD) criterion; (4) the 25 largest clusters are subject to a smooth docking discrimination algorithm where van der Waals forces are taken into account. We predicted targets 1, 6, and 7 with RMSDs of 9.5, 2.4, and 2.6 Å, respectively. More importantly, from the perspective of biological applications, our approach consistently ranked the correct model first (i.e., with highest confidence). For target 5 we identified the binding region but not the correct orientation. Although we were able to find reasonable clusters for all targets, low‐affinity complexes (Kd < nM) were harder to discriminate. For four of seven targets, the top models predicted by our automated procedure were among the best communitywide predictions. Proteins 2003;52:92–97. © 2003 Wiley‐Liss, Inc. |
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AbstractList | We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our algorithm, SmoothDock, comprises four steps: (1) we perform rigid body docking using the program DOT, keeping the top 20,000 structures as ranked by surface complementarity; (2) we rerank these structures according to a free energy estimate that includes both desolvation and electrostatics and retain the top 2000 complexes; (3) we cluster the filtered complexes using a pairwise root-mean-square deviation (RMSD) criterion; (4) the 25 largest clusters are subject to a smooth docking discrimination algorithm where van der Waals forces are taken into account. We predicted targets 1, 6, and 7 with RMSDs of 9.5, 2.4, and 2.6 A, respectively. More importantly, from the perspective of biological applications, our approach consistently ranked the correct model first (i.e., with highest confidence). For target 5 we identified the binding region but not the correct orientation. Although we were able to find reasonable clusters for all targets, low-affinity complexes (K(d) < nM) were harder to discriminate. For four of seven targets, the top models predicted by our automated procedure were among the best communitywide predictions. We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our algorithm, SmoothDock, comprises four steps: (1) we perform rigid body docking using the program DOT, keeping the top 20,000 structures as ranked by surface complementarity; (2) we rerank these structures according to a free energy estimate that includes both desolvation and electrostatics and retain the top 2000 complexes; (3) we cluster the filtered complexes using a pairwise root‐mean‐square deviation (RMSD) criterion; (4) the 25 largest clusters are subject to a smooth docking discrimination algorithm where van der Waals forces are taken into account. We predicted targets 1, 6, and 7 with RMSDs of 9.5, 2.4, and 2.6 Å, respectively. More importantly, from the perspective of biological applications, our approach consistently ranked the correct model first (i.e., with highest confidence). For target 5 we identified the binding region but not the correct orientation. Although we were able to find reasonable clusters for all targets, low‐affinity complexes (Kd < nM) were harder to discriminate. For four of seven targets, the top models predicted by our automated procedure were among the best communitywide predictions. Proteins 2003;52:92–97. © 2003 Wiley‐Liss, Inc. We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our algorithm, SmoothDock, comprises four steps: (1) we perform rigid body docking using the program DOT, keeping the top 20,000 structures as ranked by surface complementarity; (2) we rerank these structures according to a free energy estimate that includes both desolvation and electrostatics and retain the top 2000 complexes; (3) we cluster the filtered complexes using a pairwise root-mean-square deviation (RMSD) criterion; (4) the 25 largest clusters are subject to a smooth docking discrimination algorithm where van der Waals forces are taken into account. We predicted targets 1, 6, and 7 with RMSDs of 9.5, 2.4, and 2.6 A, respectively. More importantly, from the perspective of biological applications, our approach consistently ranked the correct model first (i.e., with highest confidence). For target 5 we identified the binding region but not the correct orientation. Although we were able to find reasonable clusters for all targets, low-affinity complexes (K(d) < nM) were harder to discriminate. For four of seven targets, the top models predicted by our automated procedure were among the best communitywide predictions.We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our algorithm, SmoothDock, comprises four steps: (1) we perform rigid body docking using the program DOT, keeping the top 20,000 structures as ranked by surface complementarity; (2) we rerank these structures according to a free energy estimate that includes both desolvation and electrostatics and retain the top 2000 complexes; (3) we cluster the filtered complexes using a pairwise root-mean-square deviation (RMSD) criterion; (4) the 25 largest clusters are subject to a smooth docking discrimination algorithm where van der Waals forces are taken into account. We predicted targets 1, 6, and 7 with RMSDs of 9.5, 2.4, and 2.6 A, respectively. More importantly, from the perspective of biological applications, our approach consistently ranked the correct model first (i.e., with highest confidence). For target 5 we identified the binding region but not the correct orientation. Although we were able to find reasonable clusters for all targets, low-affinity complexes (K(d) < nM) were harder to discriminate. For four of seven targets, the top models predicted by our automated procedure were among the best communitywide predictions. We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our algorithm, SmoothDock, comprises four steps: (1) we perform rigid body docking using the program DOT, keeping the top 20,000 structures as ranked by surface complementarity; (2) we rerank these structures according to a free energy estimate that includes both desolvation and electrostatics and retain the top 2000 complexes; (3) we cluster the filtered complexes using a pairwise root‐mean‐square deviation (RMSD) criterion; (4) the 25 largest clusters are subject to a smooth docking discrimination algorithm where van der Waals forces are taken into account. We predicted targets 1, 6, and 7 with RMSDs of 9.5, 2.4, and 2.6 Å, respectively. More importantly, from the perspective of biological applications, our approach consistently ranked the correct model first (i.e., with highest confidence). For target 5 we identified the binding region but not the correct orientation. Although we were able to find reasonable clusters for all targets, low‐affinity complexes (K d < nM) were harder to discriminate. For four of seven targets, the top models predicted by our automated procedure were among the best communitywide predictions. Proteins 2003;52:92–97. © 2003 Wiley‐Liss, Inc. |
Author | Gatchell, David W. Camacho, Carlos J. |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/12784373$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.1002/1097-0134(20000815)40:3<525::AID-PROT190>3.0.CO;2-F 10.1073/pnas.89.6.2195 10.1110/ps.19202 10.1093/nar/28.1.235 10.1002/prot.10111 10.1016/S0959-440X(02)00286-5 10.1016/S1074-7613(00)80646-9 10.1016/S0959-440X(02)00285-3 10.1006/viro.2001.1320 10.1073/pnas.181147798 10.1080/08927029308022163 10.1016/S0969-2126(02)00759-1 10.1002/jcc.540040211 10.1073/pnas.192368699 10.1006/jmbi.1996.0859 10.1021/jp9521621 10.1074/jbc.M202327200 |
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References | Barbey-Martin C, Gigant B, Bizebard T, Calder LJ, Wharton SA, Skehel JJ, Knossow M. An antibody that prevents the hemagglutinin low pH fusgenic transition. Virology 2002; 294: 70-74. Sundberg EJ, Hongmin L, Liera AS, McCormick JK, Tormo J, Schlievert PM, Karjalainen K, Mariuzza RA. Structures of two streptococcal superantigens bound to TCR β chains reveal diversity in the architecture of T cell signaling complexes. Structure 2002; 10: 687-699. Li H, Llera A, Tsuchiya D, Ysern X, Schlievert PM, Karjalainen K, Mariuzza RA. Three-dimensional structure of the complex between a T cell receptor beta chain and the superantigen staphylococcal enterotoxin B. Immunity 1998; 9: 807-816. Desmyter A, Spinelli S, Payan F, Lauwereys M, Wyns L, Muyldermans S, Cambillau C. Three camelid VHH domains in complex with porcine pancreatic α-amylase. Inhibition and versatility of binding topology. J Biol Chem 2002; 277: 23645-23650. Janin J. Welcome to CAPRI: a critical assessment of predicted interactions. Proteins 2002; 47: 257. Fernández-Recio J, Totrov M, Abagyan R. Soft protein-protein docking in internal coordinates. Protein Sci 2002; 11: 280-291. Fieulaine S, Morera S, Poncet S, Mijakovic I, Galinier A, Janin J, Deutscher J, Nessler S. X-ray structure of a bifunctional protein kinase in complex with its protein substrate HPr. Proc Natl Acad Sci USA 2002; 99: 13437-13441. Schaefer, M. Karplus, M. A comprehensive analytical treatment of continuum electrostatics. J Phys Chem 1996; 100: 1578-1599. Bruccoleri RE. Application of systematic conformational search to protein modeling. Mol Simulat 1993; 10: 151-174. Camacho CJ, Vajda S. Protein docking along smooth association pathways. Proc Natl Acad Sci USA 2001; 98: 10636-10641. Camacho CJ, Gatchell DW, Kimura SR, Vajda S. Scoring docked conformations generated by rigid-body protein-protein docking. Proteins 2000; 40: 525-537. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res 2000; 28: 235-242. Camacho CJ, Vajda S. Protein-protein association kinetics and protein docking. Curr Opin Struct Biol 2002; 12: 36-40. Smith GR, Sternberg MJE. Prediction of protein-protein interactions by docking methods. Curr Opin Struct Biol 2002; 12: 28-35. Katchalski-Katzir E, Shariv I, Eisenstein M, Friesem A, Aflalo C, Vakser I. Molecular surface recognition: determinination of geometric fit between proteins and their ligands by correlation techniques. Proc Natl Acad Sci USA 1992; 89: 2195-2199. Zhang C, Vasmatzis G, Cornette JL. Determination of atomic desolvation energies from the structures of crystallized proteins. J Mol Biol 1997; 267: 707-726. Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M. CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. J Comput Chem 1983; 4: 187-217. 1997; 267 2002; 47 2000; 28 2002; 294 2002; 12 1993; 10 2002; 10 1983; 4 2002; 11 2002; 99 2002; 277 2000; 40 1995 1996; 100 1992; 89 1998; 9 2001; 98 e_1_2_6_20_2 Ten Eyck LF (e_1_2_6_9_2) 1995 e_1_2_6_8_2 e_1_2_6_7_2 e_1_2_6_18_2 e_1_2_6_19_2 e_1_2_6_4_2 e_1_2_6_3_2 e_1_2_6_6_2 e_1_2_6_5_2 e_1_2_6_12_2 e_1_2_6_13_2 e_1_2_6_2_2 e_1_2_6_10_2 e_1_2_6_11_2 e_1_2_6_16_2 e_1_2_6_17_2 e_1_2_6_14_2 e_1_2_6_15_2 |
References_xml | – reference: Fernández-Recio J, Totrov M, Abagyan R. Soft protein-protein docking in internal coordinates. Protein Sci 2002; 11: 280-291. – reference: Fieulaine S, Morera S, Poncet S, Mijakovic I, Galinier A, Janin J, Deutscher J, Nessler S. X-ray structure of a bifunctional protein kinase in complex with its protein substrate HPr. Proc Natl Acad Sci USA 2002; 99: 13437-13441. – reference: Li H, Llera A, Tsuchiya D, Ysern X, Schlievert PM, Karjalainen K, Mariuzza RA. Three-dimensional structure of the complex between a T cell receptor beta chain and the superantigen staphylococcal enterotoxin B. Immunity 1998; 9: 807-816. – reference: Smith GR, Sternberg MJE. Prediction of protein-protein interactions by docking methods. Curr Opin Struct Biol 2002; 12: 28-35. – reference: Camacho CJ, Vajda S. Protein-protein association kinetics and protein docking. Curr Opin Struct Biol 2002; 12: 36-40. – reference: Sundberg EJ, Hongmin L, Liera AS, McCormick JK, Tormo J, Schlievert PM, Karjalainen K, Mariuzza RA. Structures of two streptococcal superantigens bound to TCR β chains reveal diversity in the architecture of T cell signaling complexes. Structure 2002; 10: 687-699. – reference: Camacho CJ, Gatchell DW, Kimura SR, Vajda S. Scoring docked conformations generated by rigid-body protein-protein docking. Proteins 2000; 40: 525-537. – reference: Camacho CJ, Vajda S. Protein docking along smooth association pathways. Proc Natl Acad Sci USA 2001; 98: 10636-10641. – reference: Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res 2000; 28: 235-242. – reference: Desmyter A, Spinelli S, Payan F, Lauwereys M, Wyns L, Muyldermans S, Cambillau C. Three camelid VHH domains in complex with porcine pancreatic α-amylase. Inhibition and versatility of binding topology. J Biol Chem 2002; 277: 23645-23650. – reference: Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M. CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. J Comput Chem 1983; 4: 187-217. – reference: Janin J. Welcome to CAPRI: a critical assessment of predicted interactions. Proteins 2002; 47: 257. – reference: Zhang C, Vasmatzis G, Cornette JL. Determination of atomic desolvation energies from the structures of crystallized proteins. J Mol Biol 1997; 267: 707-726. – reference: Barbey-Martin C, Gigant B, Bizebard T, Calder LJ, Wharton SA, Skehel JJ, Knossow M. An antibody that prevents the hemagglutinin low pH fusgenic transition. Virology 2002; 294: 70-74. – reference: Schaefer, M. Karplus, M. A comprehensive analytical treatment of continuum electrostatics. J Phys Chem 1996; 100: 1578-1599. – reference: Bruccoleri RE. Application of systematic conformational search to protein modeling. 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Snippet | We present results from the prediction of protein complexes associated with the first Critical Assessment of PRediction of Interactions (CAPRI) experiment. Our... |
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SubjectTerms | Algorithms alpha-Amylases - chemistry alpha-Amylases - metabolism Animals Antibodies - chemistry Antibodies - immunology Antigens, Viral Bacterial Proteins - chemistry Bacterial Proteins - metabolism Binding Sites CAPRI Capsid Proteins - chemistry Capsid Proteins - immunology clusters decoys desolvation docking Exotoxins - chemistry Exotoxins - metabolism Hemagglutinin Glycoproteins, Influenza Virus - chemistry Hemagglutinin Glycoproteins, Influenza Virus - immunology Macromolecular Substances Membrane Proteins - chemistry Membrane Proteins - metabolism Models, Molecular Phosphoenolpyruvate Sugar Phosphotransferase System - chemistry Phosphoenolpyruvate Sugar Phosphotransferase System - metabolism Protein Interaction Mapping Protein-Serine-Threonine Kinases - chemistry Protein-Serine-Threonine Kinases - metabolism Proteins - chemistry Proteins - metabolism Receptors, Antigen, T-Cell, alpha-beta - chemistry Receptors, Antigen, T-Cell, alpha-beta - metabolism SmoothDock |
Title | Successful discrimination of protein interactions |
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