The DOI matches its Crossref record; 127 of the 127 references it cites were found in a registry or an index.
Force fields and molecular dynamics simulations
Open accessAbstract
The objective of this review is to serve as an introductory guide for the non-expert to the exciting field of Molecular Dynamics (MD). MD simulations generate a phase space trajectory by integrating the classical equations of motion for a system of N particles. Here I review the basic concepts needed to understand the technique, what are the key elements to perform a simulation and which is the information that can be extracted from it. I will start defining what is a force field, which are the terms composing a classical force field, how the parameters of the potential are optimized, and which are the more popular force fields currently employed and the lines of research to improve them. Then the Molecular Dynamics technique will be introduced, including a general overview of the main algorithms employed to integrate the equations of motion, compute the long-range forces, work on different thermodynamic ensembles, or reduce the computational time. Finally the main properties that can be computed from a MD trajectory are briefly introduced.
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Cites
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Cited by
Unke, O. T., Chmiela, S., Sauceda, H. E., Gastegger, M., Poltavsky, I., Schütt, K. T., Tkatchenko, A., & Müller, K.-R. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c01111 · Cited by 1,647
Molecular dynamics-driven drug discovery: leaping forward with confidence
Ganesan, A., Coote, M. L., & Barakat, K. (2017) · Drug Discovery Today · doi:10.1016/j.drudis.2016.11.001 · Cited by 357
Geo-Measures: A PyMOL plugin for protein structure ensembles analysis
Kagami, L. P., das Neves, G. M., Timmers, L. F. S. M., Caceres, R. A., & Eifler-Lima, V. L. (2020) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2020.107322 · Cited by 298
Metadata
- Authors
- González, M. A.
- Venue
- École thématique de la Société Française de la Neutronique
- Publisher
- EDP Sciences
- Published
- 2011
- Volume
- 12
- Pages
- 169-200
- ISSN
- 2107-7223 (ISSN-L)
- 2107-7231
- OpenAlex
- W2153789213
- Cited by
- 295
- References
- 127
- FWCI
- 0.63
- Type
- journal article
- Language
- fr
- Open access
- hybrid
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
