The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Improved side‐chain torsion potentials for the Amber ff99SB protein force field
Open accessAbstract
Recent advances in hardware and software have enabled increasingly long molecular dynamics (MD) simulations of biomolecules, exposing certain limitations in the accuracy of the force fields used for such simulations and spurring efforts to refine these force fields. Recent modifications to the Amber and CHARMM protein force fields, for example, have improved the backbone torsion potentials, remedying deficiencies in earlier versions. Here, we further advance simulation accuracy by improving the amino acid side‐chain torsion potentials of the Amber ff99SB force field. First, we used simulations of model alpha‐helical systems to identify the four residue types whose rotamer distribution differed the most from expectations based on Protein Data Bank statistics. Second, we optimized the side‐chain torsion potentials of these residues to match new, high‐level quantum‐mechanical calculations. Finally, we used microsecond‐timescale MD simulations in explicit solvent to validate the resulting force field against a large set of experimental NMR measurements that directly probe side‐chain conformations. The new force field, which we have termed Amber ff99SB‐ILDN, exhibits considerably better agreement with the NMR data. Proteins 2010. © 2010 Wiley‐Liss, Inc.
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Cites
Relation between native ensembles and experimental structures of proteins
Best, R. B., Lindorff-Larsen, K., DePristo, M. A., & Vendruscolo, M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0511156103 · Cited by 152
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Kumari, R., Kumar, R., Open Source Drug Discovery Consortium, & Lynn, A. (2014) · Journal of Chemical Information and Modeling · doi:10.1021/ci500020m · Cited by 4,882
OpenMM 7: Rapid development of high performance algorithms for molecular dynamics
Eastman, P., Swails, J., Chodera, J. D., McGibbon, R. T., Zhao, Y., Beauchamp, K. A., Wang, L.-P., Simmonett, A. C., Harrigan, M. P., Stern, C. D., et al. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005659 · Cited by 2,748
Atomic-level characterization of the structural dynamics of proteins
Shaw, D. E., Maragakis, P., Lindorff-Larsen, K., Piana, S., Dror, R. O., Eastwood, M. P., Bank, J. A., Jumper, J. M., Salmon, J. K., Shan, Y., et al. (2010) · Science · doi:10.1126/science.1187409 · Cited by 1,923
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Lu, A., Magupalli, V. G., Ruan, J., Yin, Q., Atianand, M. K., Vos, M. R., Schröder, G. F., Fitzgerald, K. A., Wu, H., & Egelman, E. H. (2014) · Cell · doi:10.1016/j.cell.2014.02.008 · Cited by 1,353
Identification of slow molecular order parameters for Markov model construction
Pérez-Hernández, G., Paul, F., Giorgino, T., De Fabritiis, G., & Noé, F. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4811489 · Cited by 990
“The system was then parametrized with the AMBER ff99SB-ILDN forcefield [49]; water and ions were modeled respectively with the TIP3P and Joung-Cheatham parameter sets [38, 37].”
Method
Metadata
- Authors
- Lindorff‐Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J. L., Dror, R. O., & Shaw, D. E.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2010-04-05
- Volume
- 78
- Issue
- 8
- Pages
- 1950-1958
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2161605421
- Cited by
- 6,134
- References
- 1
- FWCI
- 36.63
- Type
- journal article
- Language
- en
- Open access
- bronze
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