Key Methods Papers in Molecular Modeling
Per a request from the NIH's National Center for Research Resources, the Resource for Macromolecular Modeling and Bioinformatics identified three key papers in molecular modeling and simulation, for use in development of a bibliographic evaluation tool. Many candidate papers were suggested by Resource members before the top three were identified. Below are the top three papers, followed by suggested top papers from Resource and non-Resource authors.
The Top Three Papers in Molecular Modeling and Simulation
Scalable molecular dynamics with NAMD. J. C. Phillips, R. Braun, W. Wang, J. Gumbart, E. Tajkhorshid, E. Villa, C. Chipot, R. D. Skeel, L. Kale, and K. Schulten. Journal of Computational Chemistry, 26:1781-1802, 2005.
Coarse grained model for semiquantitative lipid simulations. S. J. Marrink, S. J., A. H. de Vries, and A. E. Mark. Journal of Physical Chemistry B., 108:750–760, 2004.
Replica-exchange molecular dynamics method for protein folding. Y. Sugita and Y. Okamoto. Chemical Physics Letters, 314:141-151, 1999.
Other Key Papers
Ankyrin
Key Papers from the Resource for Macromolecular Modeling and Bioinformatics:
Calculating potentials of mean force from steered molecular dynamics simulations. S. Park and K. Schulten. Journal of Chemical Physics, 120:5946-5961, 2004.
Free energy calculation from steered molecular dynamics simulations using Jarzynski's equality. S. Park, F. Khalili-Araghi, E. Tajkhorshid, and K. Schulten. Journal of Chemical Physics, 119:3559-3566, 2003.
Reaction paths based on mean first-passage times. S. Park, M. K. Sener, D. Lu, and K. Schulten. Journal of Chemical Physics, 119:1313-1319, 2003.
Energetics of glycerol conduction through aquaglyceroporin GlpF. M. Ø. Jensen, S. Park, E. Tajkhorshid, and K. Schulten. Proceedings of the National Academy of Sciences, USA, 99:6731-6736, 2002.
Single-molecule experiments in vitro and in silico. M. Sotomayor and K. Schulten. Science, 316:1144-1148, 2007.
Steered molecular dynamics and mechanical functions of proteins. B. Isralewitz, M. Gao, and K. Schulten. Current Opinion in Structural Biology, 11:224-230, 2001.
Steered molecular dynamics. S. Izrailev, S. Stepaniants, B. Isralewitz, D. Kosztin, H. Lu, F. Molnar, W. Wriggers, and K. Schulten. In P. Deuflhard, J. Hermans, B. Leimkuhler, A. E. Mark, S. Reich, and R. D. Skeel, editors, Computational Molecular Dynamics: Challenges, Methods, Ideas, volume 4 of Lecture Notes in Computational Science and Engineering, pp. 39-65. Springer-Verlag, Berlin, 1998.
Multiscale Lac Repressor
Accelerating molecular modeling applications with graphics processors. J. E. Stone, J. C. Phillips, P. L. Freddolino, D. J. Hardy, L. G. Trabuco, and K. Schulten. Journal of Computational Chemistry, 28:2618-2640, 2007.
Scalable molecular dynamics with NAMD. J. C. Phillips, R. Braun, W. Wang, J. Gumbart, E. Tajkhorshid, E. Villa, C. Chipot, R. D. Skeel, L. Kale, and K. Schulten. Journal of Computational Chemistry, 26:1781-1802, 2005.
NAMD2: Greater scalability for parallel molecular dynamics. L. Kalé, R. Skeel, M. Bhandarkar, R. Brunner, A. Gursoy, N. Krawetz, J. Phillips, A. Shinozaki, K. Varadarajan, and K. Schulten. Journal of Computational Physics, 151:283-312, 1999.
Modeling DNA loops using the theory of elasticity. A. Balaeff, L. Mahadevan, and K. Schulten. Physical Review E, 73:031919, 2006.
Ion-nanotube terahertz oscillator. D. Lu, Y. Li, U. Ravaioli, and K. Schulten. Physical Review Letters, 95:246801, 2005.
Multi-scale method for simulating protein-DNA complexes. E. Villa, A. Balaeff, L. Mahadevan, and K. Schulten. Multiscale Modeling and Simulation, 2:527-553, 2004.
Elastic rod model of a DNA loop in the lac operon. A. Balaeff, L. Mahadevan, and K. Schulten. Physical Review Letters, 83:4900-4903, 1999.
Principal component analysis and long time protein dynamics. M. A. Balsera, W. Wriggers, Y. Oono, and K. Schulten. Journal of Physical Chemistry, 100:2567-2572, 1996.
Polarized Nanotube
Key Papers from Other Sources:
Aggregation and vesiculation of membrane proteins by curvature-mediated interactions. B. J. Reynwar, G. Illya, V. A. Harmandaris, M. M. Müller, K. Kremer and M. Deserno. Nature, 447:461-464, 2007.
All-atom empirical potential for molecular modeling and dynamics studies of protein. A. D. MacKerell, Jr., D. Bashford, M. Bellott, R. L. Dunbrack, Jr., J. D. Evanseck, M. J. Field, S. Fischer, J. Gao, H. Guo, S. Ha, D. Joseph-McCarthy, L. Kuchnir, K. Kuczera, F. T. K. Lau, C. Mattos, S. Michnick, T. Ngo, D. T. Nguyen, B. Prodhom, W. E. Reiher, III, B. Roux, M. Schlenkrich, J. C. Smith, R. Stote, J. Straub, M. Watanabe, J. Wiórkiewicz-Kuczera, D. Yin, and M. Karplus. Journal of Physical Chemistry B, 102:3586-3616, 1998.
Force fields for protein simulations. J.W. Ponder and D.A. Case. Advances in Protein Chemistry, 66:27-85, 2003.
Mechanism of Na+/H+ antiporting. I. T. Arkin, H. Xu, M.O. Jensen, E. Arbely, E. R. Bennett, K. J. Bowers, E. Chow, R. O. Dror, M. P. Eastwood, R. Flitman-Tene, B. A. Gregersen, J. L. Klepeis, I. Kolossvary, Y. Shan, and D. E Shaw. Science, 317:799-803, 2008.
Molecular dynamics simulations of biomolecules. M. Karplus and J. A. McCammon. Nature Structural Biology, 9:646-652, 2002.
Molecular dynamics simulations of lipid bilayers. S. E. Feller. Current Opinion in Colloid & Interface Science, 5:217–223, 2000.
The Amber biomolecular simulation programs. D.A. Case, T.E. Cheatham, III, T. Darden, H. Gohlke, R. Luo, K.M. Merz, Jr., A. Onufriev, C. Simmerling, B. Wang and R. Woods. Journal of Computational Chemistry, 26:1668-1688, 2005.
The MARTINI forcefield: coarse grained model for biomolecular simulations. S. J. Marrink, H. J. Risselada, S. Yefimov, D. P. Tieleman, and A. H.de Vries. Journal of Physical Chemistry B., 111:7812-7824, 2007.
A coarse grain model for phospholipid simulations. J. C. Shelley, M. Y. Shelley, R. C. Reeder, S. Bandyopadhyay, and M. L. Klein. Journal of Physical Chemistry B., 105:4464–4470, 2001.
GROMACS 3.0: A package for molecular simulation and trajectory analysis. E. Lindahl and B. Hess and D. van der Spoel. Journal of Molecular Modeling, 7:306-317, 2001.
CHARMM fluctuating charge force field for proteins: II protein/solvent properties from molecular dynamics simulations using a nonadditive electrostatic model. S. Patel, A. D. MacKerell, Jr., and C. L. Brooks III. Journal of Computational Chemistry, 25: 1504-1514, 2004.
Coarse grained model for semiquantitative lipid simulations. S. J. Marrink, S. J., A. H. de Vries, and A. E. Mark. Journal of Physical Chemistry B., 108:750–760, 2004.
Constant pH molecular dynamics in generalized Born implicit solvent. J. Mongan and D. A. Case and J. A. McCammon. Journal of Computational Chemistry, 24:2038-2048, 2004.
Electrostatics calculations: latest methodological advances. P. Koehl. Current Opinion in Structural Biology, 16:142-151, 2006.
ElNemo: a normal mode web server for protein movement analysis and the generation of templates for molecular replacement. K. Suhre and Y. Sanejouand. Nucleic Acids Research, 32:W610–W614, 2004.
Empirical force fields for biological macromolecules: Overview and issues. A. D. MacKerell. Journal of Computational Chemistry, 25:1584-1604, 2004.
Fast, Flexible, and Free. D. Van der Spoel, E. Lindahl, B. Hess, G. Groenhof, A. E. Mark, H. J. C. Berendsen. GROMACS: Journal of Computational Chemistry, 16:1701-1718, 2005.
Fitting of high-resolution structures into electron microscopy reconstruction images. F. Fabiola and M. S. Chapman. Structure, 13:389-400, 2005.
Using massively parallel simulation and Markovian models to study protein folding: Examining the dynamics of the villin headpiece. G. Jayachandran, V. Vishal, and V. S. Pande. Journal of Chemical Physics, 124:164902-1-164902-12, 2006.
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. S. Altschul, T. Madden, A. A. Schaffer, J.H. Zhang, Z. Zhang, W. Miller, and D. J. Lipman. Nucleic Acids Research, 25:3389-3402, 1997.
Intrinsic motions along an enzymatic reaction trajectory. K. A. Henzler-Wildman, V. Thai, M. Lei, M. Ott, M. Wolf-Watz, T. Fenn, E. Pozharski, M. A. Wilson, G. A. Petsko, M. Karplus, C. G. Hübner, and D. Kern. Nature, 450:838-44, 2007.
Molecular dynamics simulation of nucleic acids: successes, limitations, and promise. T. E. Cheatham and M. A. Young. Biopolymers, 56:232-256, 2000.
Optimized particle-mesh Ewald/multiple-time step integration for molecular dynamics simulations. P. F. Batcho, D. A. Case, and T. Schlick. Journal of Chemical Physics, 115:4003–4018, 2001.
Polarizable empirical force field for aromatic compounds based on the classical drude oscillator. P. E. M. Lopes, G. Lamoureux, B. Roux, and A. D. MacKerell, Jr. Journal of Physical Chemistry B., 111, 2873-2885, 2007.
Progress in modeling of protein structures and interactions. O. Schueler-Furman, C. Wang, P. Bradley, K. Misura and D. Baker. Science, 310:638-642, 2005.
Replica-exchange molecular dynamics method for protein folding. Y. Sugita and Y. Okamoto. Chemical Physics Letters, 314:141-151, 1999.
Resolution exchange simulations. E. Lyman, F. M. Ytreberg and D. M. Zuckerman. Physical Review Letters, 96:028105, 2006.
Screen Savers of the World Unite! M. Shirts and V. S. Pande. Science, 290:1903-1904, 2000.
Simulating movement of tRNA into the ribosome during decoding. K. Y. Sanbonmatsu, S. Joseph, and C. S. Tung. Proceedings of the National Academy of Sciences of the United States, 102: 15854-15859, 2005.
