Abstract
Owing to significant efforts in genome sequencing over nearly three decades (McPherson et al. 2001; Venter et al. 2001), gene sequences from many organisms have been deduced. Over 100 million nucleotide sequences from over 300 thousand different organisms have been deposited in the major DNA databases, DDBJ/EMBL/GenBank (Benson et al. 2003; Miyazaki et al. 2003; Kulikova et al. 2004), totaling almost 200 billion nucleotide bases (about the number of stars in the Milky Way). Over 5 million of these nucleotide sequences have been translated into amino acid sequences and deposited in the UniProtKB database (Release 12.8) (Bairoch et al. 2005). The protein sequences in UniParc triple this number. However, the protein sequences themselves are usually insufficient for determining protein function as the biological function of proteins is intrinsically linked to three dimensional protein structure (Skolnick et al. 2000).
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References
Bairoch A, Apweiler R, Wu CH, Barker WC, Boeckmann B, Ferro S et al (2005) The Universal Protein Resource (UniProt). Nucleic Acids Res 33(Database issue):D154–D159
Bateman A, Coin L, Durbin R, Finn RD, Hollich V, Griffiths-Jones S et al (2004) The Pfam protein families database. Nucleic Acids Res 32(Database issue):D138–D141
Battey JN, Kopp J, Bordoli L, Read RJ, Clarke ND, Schwede T (2007) Automated server predictions in CASP7. Proteins 69(S8):68–82
Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL (2003) GenBank. Nucleic Acids Res 31(1):23–27
Berendsen HJC, Postma JPM, van Gunsteren WF, Hermans J (1981) Interaction models for water in relation to protein hydration. Intermolecular forces, Reidel, Dordrecht, The Netherlands
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H et al (2000) The Protein Data Bank. Nucleic Acids Res 28(1):235–242
Bowie JU, Eisenberg D (1994) An evolutionary approach to folding small alpha-helical proteins that uses sequence information and an empirical guiding fitness function. Proc Natl Acad Sci U S A 91(10):4436–4440
Bowie JU, Luthy R, Eisenberg D (1991) A method to identify protein sequences that fold into a known three-dimensional structure. Science 253:164–170
Bradley P, Misura KM, Baker D (2005) Toward high-resolution de novo structure prediction for small proteins. Science 309(5742):1868–1871
Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M (1983) CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. J Comput Chem 4(2):187–217
Burley SK, Almo SC, Bonanno JB, Capel M, Chance MR, Gaasterland T et al (1999) Structural genomics: beyond the human genome project. Nat Genet 23(2):151–157
Case DA, Pearlman DA, Caldwell JA, Cheatham TE, Ross WS (1997) AMBER 5.0. University of California, San Francisco, CA
Chandonia JM, Brenner SE (2006) The impact of structural genomics: expectations and outcomes. Science 311(5759):347–351
Chen J, Brooks CL III (2007) Can molecular dynamics simulations provide high-resolution refinement of protein structure? Proteins 67(4):922–930
Cheng J, Baldi P (2006) A machine learning information retrieval approach to protein fold recognition. Bioinformatics 22(12):1456–1463
Das R, Qian B, Raman S, Vernon R, Thompson J, Bradley P et al (200) Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home. Proteins 69(S8):118–128
Dominy BN, Brooks CL (2002) Identifying native-like protein structures using physics-based potentials. J Comput Chem 23(1):147–160
Duan Y, Kollman PA (1998) Pathways to a protein folding intermediate observed in a 1-microsecond simulation in aqueous solution. Science 282(5389):740–744
Fan H, Mark AE (2004) Refinement of homology-based protein structures by molecular dynamics simulation techniques. Protein Sci 13(1):211–220
Feig M, Brooks CL, 3rd (2002) Evaluating CASP4 predictions with physical energy functions. Proteins 49(2):232–245
Felts AK, Gallicchio E, Wallqvist A, Levy RM (2002) Distinguishing native conformations of proteins from decoys with an effective free energy estimator based on the OPLS all-atom force field and the Surface Generalized Born solvent model. Proteins 48(2):404–422
Fischer D (2003) 3D-SHOTGUN: a novel, cooperative, fold-recognition meta-predictor. Proteins 51(3):434–441
Fischer D (2006) Servers for protein structure prediction. Curr Opin Struct Biol 16(2):178–182
Fischer D, Rychlewski L, Dunbrack RL Jr, Ortiz AR, Elofsson A (2003) CAFASP3: the third critical assessment of fully automated structure prediction methods. Proteins 53(Suppl 6):503–516
Ginalski K, Pas J, Wyrwicz LS, von Grotthuss M, Bujnicki JM, Rychlewski L (2003) ORFeus: Detection of distant homology using sequence profiles and predicted secondary structure. Nucleic Acids Res 31(13):3804–3807
Helles G (2008) A comparative study of the reported performance of ab initio protein structure prediction algorithms. J R Soc Interface 5(21):387–396
Hsieh MJ, Luo R (2004) Physical scoring function based on AMBER force field and Poisson-Boltzmann implicit solvent for protein structure prediction. Proteins 56(3):475–486
Im W, Lee MS, Brooks CL III (2003) Generalized born model with a simple smoothing function. J Comput Chem 24(14):1691–1702
Jaroszewski L, Rychlewski L, Li Z, Li W, Godzik A (2005) FFAS03: a server for profile–profile sequence alignments. Nucleic Acids Res 33(Web Server issue):W284–W288
Jauch R, Yeo HC, Kolatkar PR, Clarke ND (2007) Assessment of CASP7 structure predictions for template free targets. Proteins 69(Suppl 8):57–67
Jones DT (1999) GenTHREADER: an efficient and reliable protein fold recognition method for genomic sequences. J Mol Biol 287(4):797–815
Jones DT, Taylor WR, Thornton JM (1992) A new approach to protein fold recognition. Nature 358(6381):86–89
Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79:926–935
Jorgensen WL, Tirado-Rives J (1988) The OPLS potential functions for proteins. Energy minimizations for crystals of cyclic peptides and crambin. J Am Chem Soc 110:1657–1666
Kaminski GA, Friesner RA, Tirado-Rives J, Jorgensen WL (2001) Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. J Phys Chem B 105:6474–6487
Karplus K, Barrett C, Hughey R (1998) Hidden Markov models for detecting remote protein homologies. Bioinformatics 14:846–856
Kihara D, Lu H, Kolinski A, Skolnick J (2001) TOUCHSTONE: An ab initio protein structure prediction method that uses threading-based tertiary restraints. Proc Natl Acad Sci U S A 98:10125–10130
Klepeis JL, Floudas CA (2003) ASTRO-FOLD: a combinatorial and global optimization framework for Ab initio prediction of three-dimensional structures of proteins from the amino acid sequence. Biophys J 85(4):2119–2146
Klepeis JL, Wei Y, Hecht MH, Floudas CA (2005) Ab initio prediction of the three-dimensional structure of a de novo designed protein: a double-blind case study. Proteins 58(3):560–570
Kopp J, Bordoli L, Battey JN, Kiefer F, Schwede T (2007) Assessment of CASP7 predictions for template-based modeling targets. Proteins 6(S8):38–56
Kulikova T, Aldebert P, Althorpe N, Baker W, Bates K, Browne P et al (2004) The EMBL nucleotide sequence database. Nucleic Acids Res 32(Database issue):D27–D30
Lazaridis T, Karplus M (1999) Effective energy function for proteins in solution. Proteins 35(2):133–152
Lee MR, Tsai J, Baker D, Kollman PA (2001) Molecular dynamics in the endgame of protein structure prediction. J Mol Biol 313(2):417–430
Lee MC, Duan Y (2004) Distinguish protein decoys by using a scoring function based on a new AMBER force field, short molecular dynamics simulations, and the generalized born solvent model. Proteins 55(3):620–634
Levitt M, Hirshberg M, Sharon R, Daggett V (1995) Potential-energy function and parameters for simulations of the molecular-dynamics of proteins and nucleic-acids in solution. Comput Phys Commun 91(1–3):215–231
Lindahl E, Hess B, van der Spoel D (2001) GROMACS 3.0: A package for molecular simulation and trajectory analysis. J Mol Modeling 7:306–317
Liwo A, Lee J, Ripoll DR, Pillardy J, Scheraga HA (1999) Protein structure prediction by global optimization of a potential energy function. Proc Natl Acad Sci U S A 96(10):5482–5485
Liwo A, Pincus MR, Wawak RJ, Rackovsky S, Scheraga HA (1993) Calculation of protein backbone geometry from alpha-carbon coordinates based on peptide-group dipole alignment. Protein Sci 2(10):1697–1714
MacKerell AD Jr, Bashford D, Bellott M, Dunbrack RL, Evanseck JD, Field MJ et al (1998) All-atom empirical potential for molecular Modeling and dynamics studies of proteins. J Phys Chem B 102(18):3586–3616
Marti-Renom MA, Stuart AC, Fiser A, Sanchez R, Melo F, Sali A (2000) Comparative protein structure modeling of genes and genomes. Annu Rev Biophys Biomol Struct 29:291–325
McPherson JD, Marra M, Hillier L, Waterston RH, Chinwalla A, Wallis J et al (2001) A physical map of the human genome. Nature 409(6822):934–941
Misura KM, Chivian D, Rohl CA, Kim DE, Baker D (2006) Physically realistic homology models built with ROSETTA can be more accurate than their templates. Proc Natl Acad Sci U S A 103(14):5361–5366
Miyazaki S, Sugawara H, Gojobori T, Tateno Y (2003) DNA Data Bank of Japan (DDBJ) in XML. Nucleic Acids Res 31(1):13–16
Moult J, Fidelis K, Kryshtafovych A, Rost B, Hubbard T, Tramontano A (2007) Critical assessment of methods of protein structure prediction-Round VII. Proteins 69(Suppl 8):3–9
Moult J, Fidelis K, Zemla A, Hubbard T (2001) Critical assessment of methods of protein structure prediction (CASP): round IV. Proteins Suppl 5:2–7
Nemethy G, Gibson KD, Palmer KA, Yoon CN, Paterlini G, Zagari A et al (1992) Energy Parameters in Polypeptides. 10. Improved geometric parameters and nonbonded interactions for use in the ECEPP/3 algorithm, with application to proline-containing peptides. J Phys Chem B 96:6472–6484
Neria E, Fischer S, Karplus M (1996) Simulation of activation free energies in molecular systems. J Chem Phys 105(5):1902–1921
Nilges M, Brunger AT (1991) Automated modeling of coiled coils: application to the GCN4 dimerization region. Protein Eng 4(6):649–659
Park B, Levitt M (1996) Energy functions that discriminate X-ray and near native folds from well-constructed decoys. J Mol Biol 258(2):367–392
Pieper U, Eswar N, Braberg H, Madhusudhan MS, Davis FP, Stuart AC et al (2004) MODBASE, a database of annotated comparative protein structure models, and associated resources. Nucleic Acids Res 32(Database issue):D217–D222
Pieper U, Eswar N, Davis FP, Braberg H, Madhusudhan MS, Rossi A et al (2006) MODBASE: a database of annotated comparative protein structure models and associated resources. Nucleic Acids Res 34(Database issue):D291–D295
Rychlewski L, Fischer D (2005) LiveBench-8: the large-scale, continuous assessment of automated protein structure prediction. Protein Sci 14(1):240–245
Sadreyev R, Grishin N (2003) COMPASS: a tool for comparison of multiple protein alignments with assessment of statistical significance. J Mol Biol 326(1):317–336
Sali A (1998) 100, 000 protein structures for the biologist. Nat Struct Biol 5(12):1029–1032
Sali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234(3):779–815
Shi J, Blundell TL, Mizuguchi K (2001) FUGUE: sequence-structure homology recognition using environment-specific substitution tables and structure-dependent gap penalties. J Mol Biol 310(1):243–257
Simons KT, Kooperberg C, Huang E, Baker D (1997) Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. J Mol Biol 268(1):209–225
Skolnick J, Fetrow JS, Kolinski A (2000) Structural genomics and its importance for gene function analysis. Nat Biotechnol 18(3):283–287
Skolnick J, Kihara D, Zhang Y (2004) Development and large scale benchmark testing of the PROSPECTOR 3.0 threading algorithm. Protein 56:502–518
Smaglik P (2000) Protein structure groups seek to draft common ground rules. Nature 403(6771):691
Soding J (2005) Protein homology detection by HMM-HMM comparison. Bioinformatics 21(7):951–960
Sorin EJ, Pande VS (2005) Exploring the helix-coil transition via all-atom equilibrium ensemble simulations. Biophys J 88(4):2472–2493
Stevens RC, Yokoyama S, Wilson IA (2001) Global efforts in structural genomics. Science 294(5540):89–92
Summa CM, Levitt M (2007) Near-native structure refinement using in vacuo energy minimization. Proc Natl Acad Sci U S A 104(9):3177–3182
Terwilliger TC, Waldo G, Peat TS, Newman JM, Chu K, Berendzen J (1998) Class-directed structure determination: foundation for a protein structure initiative. Protein Sci 7(9):1851–1856
Tsai J, Bonneau R, Morozov AV, Kuhlman B, Rohl CA, Baker D (2003) An improved protein decoy set for testing energy functions for protein structure prediction. Proteins 53(1):76–87
van Gunsteren WF, Billeter SR, Eising AA, Hunenberger PH, Kruger P, Mark AE et al (1996) Biomolecular Simulation: The GROMOS96 Manual and User Guide. Vdf Hochschulverlag AG an der ETH Zürich, Zürich
Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG et al (2001) The sequence of the human genome. Science 291(5507):1304–1351
Vieth M, Kolinski A, Brooks CL III, Skolnick J (1994) Prediction of the folding pathways and structure of the GCN4 leucine zipper. J Mol Biol 237(4):361–367
Vitkup D, Melamud E, Moult J, Sander C (2001) Completeness in structural genomics. Nat Struct Biol 8(6):559–566
Wallner B, Elofsson A (2007) Prediction of global and local model quality in CASP7 using Pcons and ProQ. Proteins 69(S8):184–193
Wang JM, Cieplak P, Kollman PA (2000) How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules? J Comput Chem 21(12):1049–1074
Weiner SJ, Kollman PA, Case DA, Singh UC, Ghio C, Alagona G et al (1984) A new force field for molecular mechanical simulation of nucleic acids and proteins. J Am Chem Soc 106:765–784
Wroblewska L, Skolnick J (2007) Can a physics-based, all-atom potential find a protein’s native structure among misfolded structures? I. Large scale AMBER benchmarking. J Comput Chem 28(12):2059–2066
Wu S, Skolnick J, Zhang Y (2007) Ab initio modeling of small proteins by iterative TASSER simulations. BMC Biol 5:17
Wu S, Zhang Y (2007) LOMETS: a local meta-threading-server for protein structure prediction. Nucleic Acids Res 35(10):3375–3382
Wu S, Zhang Y (2008) MUSTER: Improving protein sequence profile-profile alignments by using multiple sources of structure information. Proteins 72(2):547–556
Zagrovic B, Snow CD, Shirts MR, Pande VS (2002) Simulation of folding of a small alpha-helical protein in atomistic detail using worldwide-distributed computing. J Mol Biol 323(5):927–937
Zhang Y (2007) Template-based modeling and free modeling by I-TASSER in CASP7. Proteins 69(Suppl 8):108–117
Zhang Y, Kolinski A, Skolnick J (2003) TOUCHSTONE II: A new approach to ab initio protein structure prediction. Biophys J 85:1145–1164
Zhang Y, Skolnick J (2004a) Automated structure prediction of weakly homologous proteins on a genomic scale. Proc Natl Acad Sci U S A 101:7594–7599
Zhang Y, Skolnick J (2004b) Scoring function for automated assessment of protein structure template quality. Proteins 57(4):702–710
Zhang Y, Skolnick J (2005a) The protein structure prediction problem could be solved using the current PDB library. Proc Natl Acad Sci U S A 102:1029–1034
Zhang Y, Skolnick J (2005b) TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res 33(7):2302–2309
Zhou H, Zhou Y (2005) Fold recognition by combining sequence profiles derived from evolution and from depth-dependent structural alignment of fragments. Proteins 58(2):321–328
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Wu, S., Zhang, Y. (2009). Protein Structure Prediction. In: Edwards, D., Stajich, J., Hansen, D. (eds) Bioinformatics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-92738-1_11
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