Perutz, MF, Rossmann, MG, Cullis, AF, Muirhead, H, Will, G, North, ACT. Structure of haemoglobin—3‐dimensional fourier synthesis at 5.5‐Å resolution, obtained by X‐ray analysis. Nature 1960, 185:416–422.
Kendrew, JC, Bodo, G, Dintzis, HM, Parrish, RG, Wyckoff, H, Phillips, DC. 3‐Dimensional model of the myoglobin molecule obtained by X‐ray analysis. Nature 1958, 181:662–666.
Whisstock, JC, Lesk, AM. Prediction of protein function from protein sequence and structure. Q Rev Biophys 2003, 36:307–340.
Gane, PJ, Dean, PM. Recent advances in structure‐based rational drug design. Curr Opin Struct Biol 2000, 10:401–404.
Lutz, S. Beyond directed evolution—semi‐rational protein engineering and design. Curr Opin Biotechnol 2010, 21:734–743.
Durbin, RM. A map of human genome variation from population‐scale sequencing. Nature 2010, 467:1061–1073.
Rose, PW, Prlić, A, Altunkaya, A, Bi, C, Bradley, AR, Christie, CH, Costanzo, LD, Duarte, JM, Dutta, S, Feng, Z, et al. The RCSB protein data bank: integrative view of protein, gene and 3D structural information. Nucleic Acids Res 2016, 45:D271–D281.
Levitt, M. Protein conformation, dynamics, and folding by computer‐simulation. Annu Rev Biophys Bioeng 1982, 11:251–271.
Garnier, J. Protein‐structure prediction. Biochimie 1990, 72:513–524.
Liwo, A, Lee, J, Ripoll, DR, Pillardy, J, Scheraga, HA. Protein structure prediction by global optimization of a potential energy function. Proc Natl Acad Sci USA 1999, 96:5482–5485.
Hardin, C, Pogorelov, TV, Luthey‐Schulten, Z. Ab initio protein structure prediction. Curr Opin Struct Biol 2002, 12:176–181.
Levitt, M. Simplified representation of protein conformations for rapid simulation of protein folding. J Mol Biol 1976, 104:59–107.
Dill, KA, Bromberg, S, Yue, KZ, Fiebig, KM, Yee, DP, Thomas, PD, Chan, HS. Principles of protein‐folding—a perspective from simple exact models. Protein Sci 1995, 4:561–602.
Shakhnovich, E. Protein folding thermodynamics and dynamics: where physics, chemistry, and biology meet. Chem Rev 2006, 106:1559–1588.
Bonneau, R, Baker, D. Ab initio protein structure prediction: progress and prospects. Annu Rev Biophys Biomol Struct 2001, 30:173–189.
Simmerling, C, Strockbine, B, Roitberg, AE. All‐atom structure prediction and folding simulations of a stable protein. J Am Chem Soc 2002, 124:11258–11259.
Baker, D, Sali, A. Protein structure prediction and structural genomics. Science 2001, 294:93–96.
Al‐Lazikani, B, Jung, J, Xiang, ZX, Honig, B. Protein structure prediction. Curr Opin Chem Biol 2001, 5:51–56.
Blundell, TL, Sibanda, BL, Sternberg, MJE, Thornton, JM. Knowledge‐based prediction of protein structures and the design of novel molecules. Nature 1987, 326:347–352.
Dudek, MJ, Ramnarayan, K, Ponder, JW. Protein structure prediction using a combination of sequence homology and global energy minimization: II. Energy functions. J Comput Chem 1998, 19:548–573.
Sali, A, Blundell, TL. Comparative protein modeling by satisfaction of spatial restraints. J Mol Biol 1993, 234:779–815.
Xu, D, Zhang, Y. Ab initio protein structure assembly using continuous structure fragments and optimized knowledge‐based force field. Proteins 2012, 80:1715–1735.
Zhang, Y, Arakaki, AK, Skolnick, JR. TASSER: an automated method for the prediction of protein tertiary structures in CASP6. Proteins 2005, 61:91–98.
Rohl, CA, Strauss, CE, Misura, KM, Baker, D. Protein structure prediction using rosetta. Methods Enzymol 2004, 383:66–93.
Kryshtafovych, A, Fidelis, K, Moult, J. CASP10 results compared to those of previous CASP experiments. Proteins 2014, 82:164–174.
Moult, J, Fidelis, K, Kryshtafovych, A, Schwede, T, Tramontano, A. Critical assessment of methods of protein structure prediction: progress and new directions in round XI. Proteins 2016, 84(suppl 1):4–14.
Yang, J, Zhang, W, He, B, Walker, SE, Zhang, H, Govindarajoo, B, Virtanen, J, Xue, Z, Shen, H‐B, Zhang, Y. Template‐based protein structure prediction in CASP11 and retrospect of I‐TASSER in the last decade. Proteins 2016, 84(suppl 1):233–246.
Zhu, J, Xie, L, Honig, B. Structural refinement of protein segments containing secondary structure elements: local sampling, knowledge‐based potentials, and clustering. Proteins 2006, 65:463–479.
Xun, S, Jiang, F, Wu, Y‐D. Significant refinement of protein structure models using a residue‐specific force field. J Chem Theory Comput 2015, 11:1949–1956.
Verma, A, Wenzel, W. Protein structure prediction by all‐atom free‐energy refinement. BMC Struct Biol 2007, 7:12.
Stumpff‐Kane, AW, Maksimiak, K, Lee, MS, Feig, M. Sampling of near‐native protein conformations during protein structure refinement using a coarse‐grained model, normal modes, and molecular dynamics simulations. Proteins 2008, 70:1345–1356.
Raval, A, Piana, S, Eastwood, MP, Dror, RO, Shaw, DE. Refinement of protein structure homology models via long, all‐atom molecular dynamics simulations. Proteins 2012, 80:2071–2079.
Misura, KMS, Baker, D. Progress and challenges in high‐resolution refinement of protein structure models. Proteins 2005, 2005:15–29.
Chen, J, Brooks, CL III. Can molecular dynamics simulations provide high‐resolution refinement of protein structure? Proteins 2007, 67:922–930.
Lee, MS, Olson, MA. Assessment of detection and refinement strategies for de novo protein structures using force field and statistical potentials. J Chem Theory Comput 2007, 3:312–324.
Fan, H, Mark, AE. Refinement of homology‐based protein structures by molecular dynamics simulation techniques. Protein Sci 2004, 13:211–220.
Chen, JH, Im, W, Brooks, CL. Refinement of NMR structures using implicit solvent and advanced sampling techniques. J Am Chem Soc 2004, 126:16038–16047.
Lee, SY, Zhang, Y, Skolnick, J. TASSER‐based refinement of NMR structures. Proteins 2006, 63:451–456.
Raves, ML, Doreleijers, JF, Vis, H, Vorgias, CE, Wilson, KS, Kaptein, R. Joint refinement as a tool for thorough comparison between NMR and X‐ray data and structures of HU protein. J Biomol NMR 2001, 21:235–248.
Adams, PD, Pannu, NS, Brünger, AT. Cross‐validated maximum likelihood enhances crystallographic simulated annealing refinement. Proc Natl Acad Sci USA 1997, 94:5018–5023.
Kidera, A, Go, N. Refinement of protein dynamic structure—normal mode refinement. Proc Natl Acad Sci USA 1990, 87:3718–3722.
Topf, M, Baker, ML, Marti‐Renom, MA, Chiu, W, Sali, A. Refinement of protein structures by iterative comparative modeling and cryoEM density fitting. J Mol Biol 2006, 357:1655–1668.
Grishaev, A, Ying, J, Canny, MD, Pardi, A, Bax, A. Solution structure of tRNAVal from refinement of homology model against residual dipolar coupling and SAXS data. J Biomol NMR 2008, 42:99–109.
Rozycki, B, Kim, YC, Hummer, G. SAXS ensemble refinement of ESCRT‐III CHMP3 conformational transitions. Structure 2010, 19:109–116.
Rozbesky, D, Man, P, Kavan, D, Chmelik, J, Cerny, J, Bezouska, K, Novak, P. Chemical cross‐linking and H/D exchange for fast refinement of protein crystal structure. Anal Chem 2012, 84:867–870.
Modi, V, Dunbrack, RLJ. Assessment of refinement of template‐based models in CASP11. Proteins 2016, 84(Suppl. 1):260–281.
Heo, L, Park, H, Seok, C. GalaxyRefine: protein structure refinement driven by side‐chain repacking. Nucleic Acids Res 2013, 41:W384–W388.
Headd, JJ, Immormino, RM, Keedy, DA, Emsley, P, Richardson, DC, Richardson, JS. Autofix for backward‐fit sidechains: using molprobity and real‐space refinement to put misfits in their place. J Struct Funct Genomics 2009, 10:83–93.
Feig, M. Local protein structure refinement via molecular dynamics simulation with locPREFMD. J Chem Inf Model 2016, 56:1304–1312.
Laskowski, RA, MacArthur, MW, Moss, DS, Thornton, JM. PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Cryst 1993, 26:283–291.
Gront, D, Kmiecik, S, Blaszczyk, M, Ekonomiuk, D, Kolinski, A. Optimization of protein models. Wiley Interdiscp Rev Comput Mol Sci 2012, 2:479–493.
Lee, MR, Tsai, J, Baker, D, Kollman, PA. Molecular dynamics in the endgame of protein structure prediction. J Mol Biol 2001, 2001:417–430.
Park, H, Seok, C. Refinement of unreliable local regions in template‐based protein models. Proteins 2012, 80:1974–1986.
Park, H, Ko, J, Joo, K, Lee, J, Seok, C, Lee, J. Refinement of protein termini in template‐based modeling using conformational space annealing. Proteins 2011, 79:2725–2734.
Bhattacharya, D, Cheng, JL. 3Drefine: consistent protein structure refinement by optimizing hydrogen bonding network and atomic‐level energy minimization. Proteins 2013, 81:119–131.
Lu, H, Skolnick, J. Application of statistical potentials to protein structure refinement from low resolution ab initio models. Biopolymers 2003, 70:575–584.
Jonassen, I, Klose, D, Taylor, WR. Protein model refinement using structural fragment tessellation. Comput Biol Chem 2006, 30:360–366.
Park, IH, Gangupomu, V, Wagner, J, Jain, A, Vaidehi, N. Structure refinement of protein low resolution models using the GNEIMO constrained dynamics method. J Phys Chem B 2012, 116:2365–2375.
Cao, W, Terada, T, Nakamura, S, Shimizu, K. Refinement of comparative‐modeling structures by multicanonical molecular dynamics. Genome Inf 2003, 14:484–485.
Ishitani, R, Terada, T, Shimizu, K. Refinement of comparative models of protein structure by using multicanonical molecular dynamics simulations. Mol Simul 2008, 34:327–336.
Mirjalili, V, Noyes, K, Feig, M. Physics‐based protein structure refinement through multiple molecular dynamics trajectories and structure averaging. Proteins 2014, 82:196–207.
Mirjalili, V, Feig, M. Protein structure refinement through structure selection and averaging from molecular dynamics ensembles. J Chem Theory Comput 2013, 9:1294–1303.
Nugent, T, Cozzetto, D, Jones, DT. Evaluation of predictions in the CASP10 model refinement category. Proteins 2014, 82:98–111.
MacCallum, JL, Perez, A, Schnieders, MJ, Hua, L, Jacobson, MP, Dill, KA. Assessment of protein structure refinement in CASP9. Proteins 2011, 79:74–90.
MacCallum, JL, Hua, L, Schnieders, MJ, Pande, VS, Jacobson, MP, Dill, KA. Assessment of the protein‐structure refinement category in CASP8. Proteins 2009, 77:66–80.
Feig, M, Mirjalili, V. Protein structure refinement via molecular‐dynamics simulations: what works and what does not? Proteins 2016, 84 (Suppl. 1):282–292.
Cruickshank, DWJ. Remarks about protein structure precision. Acta Crystallogr D 1999, 55:583–601.
Himo, F. Quantum chemical modeling of enzyme active sites and reaction mechanisms. Theor Chem Acc 2006, 116:232–240.
Cavasotto, CN. Homology models in docking and high‐throughput docking. Curr Top Med Chem 2011, 11:1528–1534.
Capriotti, E. Comparative modeling and structure prediction: application to drug discovery. In: Lill M, ed. In Silico Drug Discovery and Design. London: Future Medicine; 2013, 34–48.
Vajda, S, Kozakov, D. Convergence and combination of methods in protein‐protein docking. Curr Opin Struct Biol 2009, 19:164–170.
Wieman, H, Tondel, K, Anderssen, E, Drablos, F. Homology‐based modelling of targets for rational drug design. Mini Rev Med Chem 2004, 4:793–804.
Bordogna, A, Pandini, A, Bonati, L. Predicting the accuracy of protein‐ligand docking on homology models. J Comput Chem 2011, 32:81–98.
Du, H, Brender, JR, Zhang, J, Zhang, Y. Protein structure prediction provides comparable performance to crystallographic structures in docking‐based virtual screening. Methods 2015, 71:77–84.
Wang, C, Bradley, P, Baker, D. Protein‐protein docking with backbone flexibility. J Mol Biol 2007, 373:503–519.
Bonvin, AMJJ. Flexible protein‐protein docking. Curr Opin Struct Biol 2006, 16:194–200.
Bastard, K, Prévost, C, Zacharias, M. Accounting for loop flexibility during protein‐protein docking. Proteins 2006, 62:956–969.
Janin, J, Rodier, F. Protein‐protein interaction at crystal contacts. Proteins 1995, 23:580–587.
Jacobson, MP, Friesner, RA, Xiang, Z, Honig, B. On the role of the crystal environment in determining protein side‐chain conformations. J Mol Biol 2002, 320:597–608.
Kundu, S, Melton, JS, Sorensen, DC, Phillips, GN Jr. Dynamics of proteins in crystals: comparison of experiment with simple models. Biophys J 2002, 83:723–732.
Burnley, BT, Afonine, PV, Adams, PD, Gros, P. Modelling dynamics in protein crystal structures by ensemble refinement. Elife 2012, 1:e00311.
Summa, CM, Levitt, M. Near‐native structure refinement using in vacuo energy minimization. Proc Natl Acad Sci USA 2007, 104:3177–3182.
Rodrigues, JPGLM, Levitt, M, Chopra, G. KoBaMIN: a knowledge‐based minimization web server for protein structure refinement. Nucleic Acids Res 2012, 40:W323–W328.
Larsen, AB, Wagner, JR, Jain, A, Vaidehi, N. Protein structure refinement of CASP target proteins using GNEIMO torsional dynamics method. J Chem Inf Model 2014, 54:508–517.
Feig, M, Gopal, SM, Vadivel, K, Stumpff‐Kane, AW. Conformational sampling in structure prediction and refinement with atomistic and coarse‐grained models. In: Kolinski, A, ed. Multiscale Approaches to Protein Modeling: Structure Prediction, Dynamics, Thermodynamics and Macromolecular Assemblies. New York City: Springer; 2010.
Engh, RA, Huber, R. Accurate bond and angle parameters for X‐ray protein‐structure refinement. Acta Crystallogr A 1991, 47:392–400.
Jagielska, A, Wroblewska, L, Skolnick, J. Protein model refinement using an optimized physics‐based all‐atom force field. Proc Natl Acad Sci USA 2008, 105:8268–8273.
Carlsen, M, Rogen, P. Protein structure refinement by optimization. Proteins 2015, 83:1616–1624.
Della Corte, D, Wildberg, A, Schröder, GF. Protein structure refinement with adaptively restrained homologous replicas. Proteins 2016, 84(Suppl. 1):302–313.
Wildberg, A, Della Corte, D, Schroder, GF. Coupling an ensemble of homologues improves refinement of protein homology models. J Chem Theory Comput 2015, 11:5578–5582.
Kmiecik, S, Gront, D, Kolinski, A. Towards the high‐resolution protein structure prediction: fast refinement of reduced models with all‐atom force field. BMC Struct Biol 2007, 7:43.
Zhang, Y. Protein structure prediction: when is it useful? Curr Opin Struct Biol 2009, 19:145–155.
Bhattacharya, D, Cheng, JL. i3Drefine software for protein 3D structure refinement and its assessment in CASP10. PLoS One 2013, 8:e69648.
Lin, MS, Head‐Gordon, T. Reliable protein structure refinement using a physical energy function. J Comput Chem 2011, 32:709–717.
Lee, GR, Heo, L, Seok, C. Effective protein model structure refinement by loop modeling and overall relaxation. Proteins 2016, 84(suppl 1):293–301.
Hospital, A, Goñi, JR, Orozco, M, Gelpi, JL. Molecular dynamics simulations: advances and applications. Adv Appl Bioinform Chem 2015, 8:37–47.
Best, RB, Zhu, X, Shim, J, Lopes, P, Mittal, J, Feig, M, MacKerell, AD Jr. Optimization of the additive CHARMM all‐atom protein force field targeting improved sampling of the backbone ϕ, ψ and side‐chain χ1 and χ2 dihedral angles. J Chem Theory Comput 2012, 8:3257–3273.
Lindorff‐Larsen, K, Maragakis, P, Piana, S, Eastwood, MP, Dror, RO, Shaw, DE. Systematic validation of protein force fields against experimental data. PLoS One 2012, 7:e32131.
Lindorff‐Larsen, K, Piana, S, Dror, RO, Shaw, DE. How fast‐folding proteins fold. Science 2011, 334:517–520.
Best, RB, Mittal, J, Feig, M, MacKerell, AD. Inclusion of many‐body effects in the additive CHARMM protein CMAP potential results in enhanced cooperativity of α‐helix and β‐hairpin formation. Biophys J 2012, 103:1045–1051.
Lane, TJ, Shukla, D, Beauchamp, KA, Pande, VS. To milliseconds and beyond: challenges in the simulation of protein folding. Curr Opin Struct Biol 2013, 23:58–65.
Perez, A, Morrone, JA, Simmerling, C, Dill, KA. Advances in free‐energy‐based simulations of protein folding and ligand binding. Curr Opin Struct Biol 2016, 36:25–31.
Lee, MR, Baker, D, Kollman, PA. 2.1 and 1.8 A average C(alpha) RMSD structure predictions on two small proteins, HP‐36 and s15. J Am Chem Soc 2001, 123:1040–1046.
van der Kamp, MW, Schaeffer, RD, Jonsson, AL, Scouras, AD, Simms, AM, Toofanny, RD, Benson, NC, Anderson, PC, Merkley, ED, Rysavy, S, et al. Dynameomics: a comprehensive database of protein dynamics. Structure 2010, 18:423–435.
Wroblewska, L, Skolnick, J. Can a physics‐based, all‐atom potential find a protein`s native structure among misfolded structures? I. Large scale AMBER benchmarking. J Comput Chem 2007, 28:2059–2066.
Zhang, J, Liang, Y, Zhang, Y. Atomic‐level protein structure refinement using fragment‐guided molecular dynamics conformation sampling. Structure 2011, 19:1784–1795.
Huang, J, Rauscher, S, Nawrocki, G, Ran, T, Feig, M, de Groot, BL, Grubmüller, H, MacKerell, AD Jr. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat Methods 2017, 14:71–73.
Cino, EA, Choy, WY, Karttunen, M. Comparison of secondary structure formation using 10 different force fields in microsecond molecular dynamics simulations. J Chem Theory Comput 2012, 8:2725–2740.
Maier, JA, Martinez, C, Kasavajhala, K, Wickstrom, L, Hauser, KE, Simmerling, C. ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB. J Chem Theory Comput 2015, 11:3696–3713.
Zhou, CY, Jiang, F, Wu, YD. Residue‐specific force field based on protein coil library. RSFF2: modification of AMBER ff99SB. J Phys Chem B 2015, 119:1035–1047.
Mackerell, AD. Empirical force fields for biological macromolecules: overview and issues. J Comput Chem 2004, 25:1584–1604.
Lindorff‐Larsen, K, Piana, S, Palmo, K, Maragakis, P, Klepeis, JL, Dror, RO, Shaw, DE. Improved side‐chain torsion potentials for the Amber ff99SB protein force field. Proteins 2010, 78:1950–1958.
Oostenbrink, C, Villa, A, Mark, AE, van Gunsteren, WF. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force‐field parameter sets 53A5 and 53A6. J Comput Chem 2004, 25:1656–1676.
Fluitt, AM, de Pablo, JJ. An analysis of biomolecular force fields for simulations of polyglutamine in solution. Biophys J 2015, 109:1009–1018.
Lindorff‐Larsen, K, Trbovic, N, Maragakis, P, Piana, S, Shaw, DE. Structure and dynamics of an unfolded protein examined by molecular dynamics simulation. J Am Chem Soc 2012, 134:3787–3791.
Best, RB, Zheng, W, Mittal, J. Balanced protein‐water interactions improve properties of disorderd proteins and non‐specific protein association. J Chem Theory Comput 2014, 10:5113–5124.
Piana, S, Donchev, AG, Robustelli, P, Shaw, DE. Water dispersion interactions strongly influence simulated structural properties of disordered protein states. J Phys Chem B 2015, 119:5113–5123.
Zhang, J, Barz, B, Zhang, JF, Xu, D, Kosztin, I. Selective refinement and selection of near‐native models in protein structure prediction. Proteins 2015, 83:1823–1835.
Wroblewska, L, Jagielska, A, Skolnick, J. Development of a physics‐based force field for the scoring and refinement of protein models. Biophys J 2008, 94:3227–3240.
Zhu, J, Fan, H, Periole, X, Honig, B, Mark, AE. Refining homology models by combining replica‐exchange molecular dynamics and statistical potentials. Proteins 2008, 72:1171–1188.
Chopra, G, Summa, CM, Levitt, M. Solvent dramatically affects protein structure refinement. Proc Natl Acad Sci USA 2008, 105:20239–20244.
Krol, M. Comparison of various implicit solvent models in molecular dynamics simulations of immunoglobulin G light chain dimer. J Comput Chem 2003, 24:531–546.
Roux, B, Simonson, T. Implicit solvent models. Biophys Chem 1999, 78:1–20.
Feig, M, Brooks, CL III. Recent advances in the development and application of implicit solvent models in biomolecule simulations. Curr Opin Struct Biol 2004, 14:217–224.
Feig, M, Chocholousova, J, Tanizaki, S. Extending the horizon: towards the efficient modeling of large biomolecular complexes in atomic detail. Theor Chem Acc 2006, 116:194–205.
Khoury, GA, Tamamis, P, Pinnaduwage, N, Smadbeck, J, Kieslich, CA, Floudas, CA. Princeton_TIGRESS: protein geometry refinement using simulations and support vector machines. Proteins 2014, 82:794–814.
Olson, MA, Lee, MS. Structure refinement of protein model decoys requires accurate side‐chain placement. Proteins 2013, 81:469–478.
Olson, MA, Chaudhury, S, Lee, MS. Comparison between self‐guided langevin dynamics and molecular dynamics simulations for structure refinement of protein loop conformations. J Comput Chem 2011, 32:3014–3022.
Lee, MS, Olson, MA. Protein folding simulations combining self‐guided langevin dynamics and temperature‐based replica exchange. J Chem Theory Comput 2010, 6:2477–2487.
Vitalis, A, Pappu, RV. ABSINTH: a new continuum solvation model for simulations of polypeptides in aqueous solutions. J Comput Chem 2009, 30:673–699.
Felts, AK, Gallicchio, E, Chekmarev, D, Paris, KA, Friesner, RA, Levy, RM. Prediction of protein loop conformations using the AGBNP implicit solvent model and torsion angle sampling. J Chem Theory Comput 2008, 4:855–868.
Olson, MA, Feig, M, Brooks, CL. Prediction of protein loop conformations using multiscale Modeling methods with physical energy scoring functions. J Comput Chem 2008, 29:820–831.
Zhu, J, Alexov, E, Honig, B. Comparative study of generalized Born models: Born radii and peptide folding. J Phys Chem B 2005, 109:3008–3022.
Nymeyer, H, Garcia, AE. Simulation of the folding equilibrium of α‐helical peptides: a comparison of the generalized Born approximation with explicit solvent. Proc Natl Acad Sci USA 2003, 100:13934–13939.
Zhou, RH. Free energy landscape of protein folding in water: explicit vs. implicit solvent. Proteins 2003, 53:148–161.
Ozkan, SB, Wu, GA, Chodera, JD, Dill, KA. Protein folding by zipping and assembly. Proc Natl Acad Sci USA 2007, 104:11987–11992.
Chen, JH, Brooks, CL, Khandogin, J. Recent advances in implicit solvent‐based methods for biomolecular simulations. Curr Opin Struct Biol 2008, 18:140–148.
Chen, JH, Im, WP, Brooks, CL. Balancing solvation and intramolecular interactions: Toward a consistent generalized born force field. J Am Chem Soc 2006, 128:3728–3736.
Onufriev, A, Bashford, D, Case, DA. Exploring protein native states and large‐scale conformational changes with a modified generalized born model. Proteins 2004, 55:383–394.
Roe, DR, Okur, A, Wickstrom, L, Hornak, V, Simmerling, C. Secondary structure bias in generalized born solvent models: comparison of conformational ensembles and free energy of solvent polarization from explicit and implicit solvation. J Phys Chem B 2007, 111:1846–1857.
Tozzini, V. Coarse‐grained models for proteins. Curr Opin Struct Biol 2005, 15:144–150.
Kar, P, Feig, M. Recent advances in transferable coarse‐grained modeling of proteins. Adv Prot Chem Struct Biol 2014, 96:143–180.
Krupa, P, Mozolewska, MA, Wisniewska, M, Yin, YP, He, Y, Sieradzan, AK, Ganzynkowicz, R, Lipska, AG, Karczynska, A, Slusarz, M, et al. Performance of protein‐structure predictions with the physics‐based UNRES force field in CASP11. Bioinformatics 2016, 32:3270–3278.
Lee, J, Liwo, A, Scheraga, HA. Energy‐based de novo protein folding by conformational space annealing and an off‐lattice united‐residue force field: application to the 10–55 fragment of Staphylococcal protein A and to apo calbindin D9K. Proc Natl Acad Sci USA 1999, 96:2025–2030.
Gopal, SM, Mukherjee, S, Cheng, Y‐M, Feig, M. PRIMO/PRIMONA: a coarse‐grained model for proteins and nucleic acids that preserves near‐atomistic accuracy. Proteins 2010, 78:1266–1281.
Kar, P, Gopal, SM, Cheng, YM, Predeus, AV, Feig, M. PRIMO: a transferable coarse‐grained force field for proteins. J Chem Theory Comput 2013, 9:3769–3788.
Kumar, A, Campitelli, P, Thorpe, MF, Ozkan, SB. Partial unfolding and refolding for structure refinement: a unified approach of geometric simulations and molecular dynamics. Proteins 2015, 83:2279–2292.
Perez, A, Morrone, JA, Brini, E, MacCallum, JL, Dill, KA. Blind protein structure prediction using accelerated free‐energy simulations. Sci Adv 2016, 2:e1601274.
Sugita, Y, Okamoto, Y. Replica‐exchange molecular dynamics method for protein folding. Chem Phys Lett 1999, 314:141–151.
Abrams, C, Bussi, G. Enhanced Sampling in molecular dynamics using metadynamics, replica‐exchange, and temperature‐acceleration. Entropy 2014, 16:163–199.
Rao, F, Caflisch, A. Replica exchange molecular dynamics simulations of reversible folding. J Chem Phys 2003, 119:4035–4042.
Rhee, YM, Pande, VS. Multiplexed‐replica exchange molecular dynamics method for protein folding simulation. Biophys J 2003, 84:775–786.
Paschek, D, Gnanakaran, S, Garcia, AE. Simulations of the pressure and temperature unfolding of an alpha‐helical peptide. Proc Natl Acad Sci USA 2005, 102:6765–6770.
Baumketner, A, Shea, JE. The thermodynamics of folding of a beta hairpin peptide probed through replica exchange molecular dynamics simulations. Theor Chem Acc 2006, 116:262–273.
Paschek, D, Nymeyer, H, Garcia, AE. Replica exchange simulation of reversible folding/unfolding of the Trp‐cage miniprotein in explicit solvent: on the structure and possible role of internal water. J Struct Biol 2007, 157:524–533.
Su, L, Cukier, RI. Hamiltonian and distance replica exchange method studies of Met‐enkephalin. J Phys Chem B 2007, 111:12310–12321.
Olson, MA, Lee, MS. Evaluation of unrestrained replica‐exchange simulations using dynamic walkers in temperature space for protein structure refinement. PLoS One 2014, 9:e96638.
Park, H, DiMaio, F, Baker, D. CASP11 refinement experiments with ROSETTA. Proteins 2016, 84(suppl 1):314–322.
Chen, JH, Im, W, Brooks, CL. Application of torsion angle molecular dynamics for efficient sampling of protein conformations. J Comput Chem 2005, 26:1565–1578.
Jacobson, MP, Pincus, DL, Rapp, CS, Day, TJF, Honig, B, Shaw, DE, Friesner, RA. A hierarchical approach to all‐atom protein loop prediction. Proteins 2004, 55:351–367.
Chinchio, M, Czaplewski, C, Oldziej, S, Scheraga, HA. A hierarchical multiscale approach to protein structure prediction: production of low‐resolution packing arrangements of helices and refinement of the best models with a united‐residue force field. Multiscale Model Simul 2006, 5:1175–1195.
Harada, R, Kitao, A. Exploring the folding free energy landscape of a beta‐hairpin miniprotein, chignolin, using multiscale free energy landscape calculation method. J Phys Chem B 2011, 115:8806–8812.
Feig, M, Karanicolas, J, Brooks, CL III. MMTSB tool set: enhanced sampling and multiscale modeling methods for applications in structural biology. J Mol Graph Model 2004, 22:377–395.
Zhang, W, Chen, J. Accelerate sampling in atomistic energy landscapes using topology‐based coarse‐grained models. J Chem Theory Comput 2014, 10:918–923.
Chen, Y, Roux, B. Enhanced sampling of an atomic model with hybrid nonequilibrium molecular dynamics‐Monte Carlo simulations guided by a coarse‐grained model. J Chem Theory Comput 2015, 11:3572–3583.
Bhattacharya, D, Cheng, J. Protein structure refinement by iterative fragment exchange. In: International Conference on Bioinformatics, Computational Biology and Biomedical Informatics, BCB`13, Washington, DC; 2013.
Lee, MC, Duan, Y. Distinguishing 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 2004, 55:620–634.
Stumpff‐Kane, AW, Feig, M. A correlation‐based method for the enhancement of scoring functions on funnel‐shaped energy landscapes. Proteins 2006, 63:155–164.
Shen, MY, Sali, A. Statistical potential for assessment and prediction of protein structures. Protein Sci 2006, 15:2507–2524.
Feig, M, Brooks, CL III. Evaluating CASP4 predictions with physical energy functions. Proteins 2002, 49:232–245.
Zhang, C, Liu, S, Zhou, HY, Zhou, YQ. An accurate, residue‐level, pair potential of mean force for folding and binding based on the distance‐scaled, ideal‐gas reference state. Protein Sci 2004, 13:400–411.
Zhang, Y, Skolnick, J. SPICKER: a clustering approach to identify near‐native protein folds. J Comput Chem 2004, 25:865–871.
Skolnick, J. In quest of an empirical potential for protein structure prediction. Curr Opin Struct Biol 2006, 16:166–171.
Rykunov, D, Fiser, A. New statistical potential for quality assessment of protein models and a survey of energy functions. BMC Bioinformatics 2010, 11:128.
Park, H, DiMaio, F, Baker, D. The origin of consistent protein structure refinement from structural averaging. Structure 2015, 23:1–6.
Cerutti, DS, Freddolino, PL, Duke, RE Jr, Case, DA. Simulations of a protein crystal with a high resolution X‐ray structure: evaluation of force fields and water models. J Phys Chem B 2010, 114:12811–12824.
Chen, VB, Arendall, WB, Headd, JJ, Keedy, DA, Immormino, RM, Kapral, GJ, Murray, LW, Richardson, JS, Richardson, DC. MolProbity: all‐atom structure validation for macromolecular crystallography. Acta Crystallogr D 2010, 66:12–21.
Kalisman, N, Levi, A, Maximova, T, Reshef, D, Zafiri‐Lynn, S, Gleyzer, Y, Kaesar, C. MESHI: a new library of Java classes for molecular modeling. Bioinformatics 2005, 21:3931–3932.
Kortemme, T, Morozov, AV, Baker, D. An orientation‐dependent hydrogen bonding potential improves prediction of specificity and structure for proteins and protein‐protein complexes. J Mol Biol 2003, 326:1239–1259.
Zemla, A, Venclovas, C, Moult, J, Fidelis, K. Processing and analysis of CASP3 protein structure predictions. Proteins 1999, 37(suppl 3):22–29.
Bhattacharya, D, Nowotny, J, Cao, RZ, Cheng, JL. 3Drefine: an interactive web server for efficient protein structure refinement. Nucleic Acids Res 2016, 44:W406–W409.
Zhou, HY, Zhou, YQ. Distance‐scaled, finite ideal‐gas reference state improves structure‐derived potentials of mean force for structure selection and stability prediction. Protein Sci 2002, 11:2714–2726.
Zhang, J, Zhang, Y. A novel side‐chain orientation dependent potential derived from random‐walk reference state for protein fold selection and structure prediction. PLoS One 2010, 5:e15386.
Wang, K, Fain, B, Levitt, M, Samudrala, R. Improved protein structure selection using decoy‐dependent discriminatory functions. BMC Struct Biol 2004, 4:8.
Zhou, H, Skolnick, J. GOAP: a generalized orientation‐dependent, all‐atom statistical potential for protein structure prediction. Biophys J 2011, 101:2043–2052.
Yang, YD, Zhou, YQ. Specific interactions for ab initio folding of protein terminal regions with secondary structures. Proteins 2008, 72:793–803.
Ko, J, Park, H, Heo, L, Seok, C. GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Res 2012, 40:W294–W297.
Huang, YJP, Mao, BC, Aramini, JM, Montelione, GT. Assessment of template‐based protein structure predictions in CASP10. Proteins 2014, 82:43–56.
Liu, T, Wang, YH, Eickholt, J, Wang, Z. Benchmarking deep networks for predicting residue‐specific quality of individual protein models in CASP11. Sci Rep‐UK 2016, 6:19301.
Paton, RS, Goodman, JM. Hydrogen bonding and pi‐stacking: how reliable are force fields? A critical evaluation of force field descriptions of nonbonded interactions. J Chem Inf Model 2009, 49:944–955.
Lopes, PEM, Huang, J, Shim, J, Luo, Y, Li, H, Roux, B, MacKerell, AD Jr. Polarizable force field for peptides and proteins based on the classical drude oscillator. J Chem Theory Comput 2013, 9:5430–5449.
Cheng, J. A multi‐template combination algorithm for protein comparative modeling. BMC Struct Biol 2008, 8:18.
Martin, J, Hartl, FU. Chaperone‐assisted protein folding. Curr Opin Struct Biol 1997, 7:41–52.
Yu, I, Mori, T, Ando, T, Harada, R, Jung, J, Sugita, Y, Feig, M. Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm. Elife 2016, 5:e19274.
Feig, M, Sugita, Y. Reaching new levels of realism in modeling biological macromolecules in cellular environments. J Mol Graph Model 2013, 45:144–156.
Barth, P, Wallner, B, Baker, D. Prediction of membrane protein structures with complex topologies using limited constraints. Proc Natl Acad Sci USA 2009, 106:1409–1414.
Elofsson, A, von Heijne, G. Membrane protein structure: prediction versus reality. Annu Rev Biochem 2007, 76:125–140.
Leman, JK, Umschneider, MB, Gray, JJ. Computational modeling of membrane proteins. Proteins 2015, 83:1–24.
Yuzlenko, O, Lazaridis, T. Membrane protein native state discrimination by implicit membrane models. J Comput Chem 2013, 34:731–738.
Gao, C, Stern, HA. Scoring function accuracy for membrane protein structure prediction. Proteins 2007, 68:67–75.
Weiner, BE, Woetzel, N, Karakas, M, Alexander, N, Meiler, J. BCL::MP‐Fold: folding membrane proteins through assembly of transmembrane helices. Structure 2013, 21:1107–1117.