Fast optimization of statistical potentials for structurally constrained phylogenetic models

BMC Evolutionary Biology

Volumn 9, Issue 1, 2009, Pages

  Bonnard, Cécile ^a,b   Kleinman, Claudia L ^b   Rodrigue, Nicolas ^c   Lartillot, Nicolas ^b  

^a LIRMM   (France)

^b UNIVERSITÉ DE MONTRÉAL   (Canada)

^c UNIVERSITY OF OTTAWA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID SEQUENCE; ARTICLE; BAYES THEOREM; GENETIC MODEL; MAXIMUM LIKELIHOOD METHOD; MOLECULAR EVOLUTION; MONTE CARLO METHOD; PHYLOGENY; PROBABILITY; ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; METHODOLOGY; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; LIKELIHOOD FUNCTIONS; MARKOV CHAINS; MODELS, GENETIC; MODELS, STATISTICAL; MONTE CARLO METHOD; PHYLOGENY;

EID: 70350676692     PISSN: None     EISSN: 14712148     Source Type: Journal    
DOI: 10.1186/1471-2148-9-227     Document Type: Article

References (42)

1. Evolutionary distances for protein-coding sequences: Modeling site-specific residue frequencies. AL Halpern WJ Bruno, Mol Biol Evol 1998 15 7 910 917 9656490
2. Mutation-Selection models of codon substitution and their use to estimate selective strengths on codon usage. Z Yang R Nielsen, Mol Biol Evol 2008 25 3 568 579 10.1093/molbev/msm284 18178545
3. Computational methods for evaluating phylogenetic models of coding sequence evolution with dependence between codons. N Rodrigue CL Kleinman H Philippe N Lartillot, Molecular Biology and Evolution 2009 26 7 1663 1676 10.1093/molbev/msp078 19383983
4. Protein evolution with dependence among codons due to tertiary structure. DM Robinson DT Jones H Kishino N Goldman JL Thorne, Molecular Biology and Evolution 2003 20 10 1692 1704 10.1093/molbev/msg184 12885968
5. Site interdependence attributed to tertiary structure in protein evolution. N Rodrigue N Lartillot D Bryant H Philippe, Gene 2005 347 2 207 217 10.1016/j.gene.2004.12.011 15733531
6. Quantifying the impact of protein tertiary Structure on molecular evolution. SC Choi A Hobolth DM Robinson H Kishino JL Thorne, Mol Biol Evol 2007 24 8 1769 1782 10.1093/molbev/msm097 17522088
7. Structural constraints and emergence of sequence patterns in protein evolution. G Parisi J Echave, Mol Biol Evol 2001 18 5 750 756 11319259
8. Basing population genetic inferences and models of molecular evolution upon desired stationary distribution of DNA or protein sequences. SC Choi BD Redelings JL Thorne, Phil trans R Soc B 2008 363 3931 3939 10.1098/rstb.2008. 0167 18852105
9. Principles that govern the folding of protein chains. CB Anfinsen, Science 1973 181 223 230 10.1126/science.181.4096.223 4124164
10. D Case TA A Darden TE Cheatham III CL Simmerling J Wang RE Duke R Luo M Crowley RC Walker W Zhang KM Merz B Wang S Hayik A Roitberg G Seabra I Kolossvry KF Wong F Paesani J Vanicek X Wu SR Brozell T Steinbrecher H Gohlke L Yang C Tan J Mongan V Hornak G Cui DH Mathews MG Seetin C Sagui V Babin KP A, AMBER 10 University of California, San Francisco 2008
11. CHARMM: The Energy Function and Its Parameterization with an Overview of the Program. AD MacKerel Jr CL Brooks III L Nilsson B Roux Y Won M Karplus, The Encyclopedia of Computational Chemistry John Wiley & Sons: Chichester, v Schleyer RP, et al, 1998 1 271 277
12. Estimation of effective interresidue contact energies from protein crystal structures: quasi-chemical approximation. S Miyazawa RL Jernigan, Macromolecules 1985 18 534 552 10.1021/ma00145a039
13. Residue-residue potentials with a favorable contact pair term and an unfavorable hight packing density term, for simulation and threading. S Miyazawa RL Jernigan, Journal of molecular biology 1996 256 3 623 644 10.1006/jmbi.1996.0114 8604144
14. Boltzmann's principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures. MJ Sippl, Journal of computer-aided molecular design 1993 7 473 501 10.1007/BF02337562 8229096
15. Improvement of statistical potentials and threading score functions using information maximixation. AD Solis S Rackovsky, Proteins 2006 62 4 892 908 10.1002/prot.20501 16395676
16. Coarse-grained model for proteins. V Tozzini, Current opinion in structural biology 2005 15 144 150 10.1016/j.sbi.2005.02.005 15837171
17. Optimal protein design procedures. F Seno M Vendruscolo A Maritan JR Banavar, Physical review letter 1996 77 9 1901 1904 10.1103/PhysRevLett.77.1901
18. New algorithm for protein design. JM Deutsch T Kurowski, Physical review letter 1996 76 323 326 10.1103/PhysRevLett.76.323
19. Variational approach to protein design and extraction of interactional potentials. F Seno M Micheletti A Maritan JR Banavar, Physical review letter 1998 81 2172 2175 10.1103/PhysRevLett.81.2172
20. A novel iterative strategy for protein design. A Rossi A Maritan C Micheletti, Journal of Chemical physics 2000 112 4 2050 2055 10.1063/1.480766
21. A self-consistent knowledge-based approach to protein design. A Rossi C Micheletti F Seno A Maritan, Biophysical journal 2001 80 1 480 490 10.1016/S0006-3495(01)76030-4 11159418
22. Comparison of database potentials and molecular mechanics force fields. J Moult, Current opinion in structural biology 1997 7 2 194 1999 10.1016/S0959-440X(97)80025-5 9094335
23. Energy estimation in protein design. J Mendes R Guerois L Serrano, Current opinion in structural biology 2002 12 4 441 446 10.1016/S0959-440X(02) 00345-7 12163065
24. A method to identify protein sequences that fold into a known three-dimensional structure. JU Bowie R Luthy D Eisenberg, Science 1991 253 5016 164 170 10.1126/science.1853201 1853201
25. Optimizing potentials for the inverse protein folding problem. TL Chiu RA Goldstein, Protein engineering 1998 11 749 752 10.1093/protein/11.9.749 9796822
26. A maximum likelihood framework for protein design. CL Kleinman N Rodrigue C Bonnard H Philippe N Lartillot, BMC Bioinformatics 2006 7 326 343 10.1186/1471-2105-7-326 16808841
27. Native protein sequences are close to optimal for their structure. B Kuhlman D Baker, PNAS 2000 97 19 10383 10388 10.1073/pnas.97.19.10383 10984534
28. Engineering of stable and fast-folding sequences of model proteins. E Shakhnovich A Gutin, Proceedings Natl Academy of sciences USA 1993 90 15 7195 7199 10.1073/pnas.90.15.7195
29. Designing amino acid sequences to fold with good hydrophobic cores. S Sun R Brem R Chan K Dill, Protein Engineering 1995 8 12 1205 1213 10.1093/protein/8.12.1205 8869633
30. Statistical mechanics of simple model of protein folding and design. VS Pande AY Grosberg T Tanaka, Biophysical journal 1997 73 6 3192 3210 10.1016/S0006-3495(97)78345-0 9414231
31. A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitutions, with applications to cholorplast genome. SV Muse BS Gaut, Mol Biol Evol 1994 11 715 724 7968485
32. A protein evolution model with independent sites that reproduces site-specific amino acid distributions from the Protein Data Bank. U Bastolla M Porto HE Roman M Vendruscolo, BMC Evolutionary Biology 2006 6 43 10.1186/1471-2148-6-43 16737532
33. Evolutionary potentials: structure specific knowledge-based potentials exploiting the evolutionary record of sequence homologs. A Panjkovich F Melo M Marti-Renom, Genome Biology 2008 9 68 10.1186/gb-2008-9-4-r68 18397517
34. PISCES: a protein sequence culling server. G Wang RLJ Dunbrack, Bioinformatics 2003 19 12 1589 1591 10.1093/bioinformatics/btg224 12912846
35. NACCESS. SJ Hubbard JM Thornton, Computer Program, Department of Biochemistry and Molecular Biology, University College London 1993
36. Codon substitution models for heterogeneous selection pressure at amino acid sites. Z Yang R Nielsen N Goldman P K, Genetics 2000 155 431 449 10790415
37. PhyloBayes 3. A Bayesian software for phylogenetic reconstruction and molecular dating. N Lartillot T Lepage S Blanquart, Bioinformatics 2009 25 17 2286 2288 10.1093/bioinformatics/btp368 19535536
38. Resolution of the Early Placental Mammal Radiation Using Bayesian Phylogenics. WJ Murphy E Eizirik SJ O'Brien O Madsen M Scally CJ Douady E Teeling OA Ryder MJ Stanhope WW de Jong MS Springer, Science 2001 294 5550 2348 2351 10.1126/science.1067179 11743200 (Pubitemid 33140557)
39. Maximum likelihood analysis of molecular adaptation in abalone sperm lysin reveals variable selective pressures among lineages and sites. Z Yang WJ Swanson VD Vacquier, Molecular Biology and Evolution 2000 17 1446 1455 11018152
40. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. S Guindon O Gascuel, Systematic Biology 2003 52 5 696 704 10.1080/10635150390235520 14530136
41. The rapid generation of mutation data matrices from protein sequences. DT Jones WR Taylor JM Thornton, CABIOS 1992 8 275 282 1633570
42. Maximum-likelihood estimation of phylogeny from DNA sequences when substitution rates differ over sites. Z Yang, Mol Biol Evol 1993 10 1396 1401 8277861