The DOI matches its Crossref record; 235 of the 235 references it cites were found in a registry or an index.
Role of Molecular Dynamics and Related Methods in Drug Discovery
Open accessAbstract
Molecular dynamics (MD) and related methods are close to becoming routine computational tools for drug discovery. Their main advantage is in explicitly treating structural flexibility and entropic effects. This allows a more accurate estimate of the thermodynamics and kinetics associated with drug-target recognition and binding, as better algorithms and hardware architectures increase their use. Here, we review the theoretical background of MD and enhanced sampling methods, focusing on free-energy perturbation, metadynamics, steered MD, and other methods most consistently used to study drug-target binding. We discuss unbiased MD simulations that nowadays allow the observation of unsupervised ligand-target binding, assessing how these approaches help optimizing target affinity and drug residence time toward improved drug efficacy. Further issues discussed include allosteric modulation and the role of water molecules in ligand binding and optimization. We conclude by calling for more prospective studies to attest to these methods' utility in discovering novel drug candidates.
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Molecular Docking: Shifting Paradigms in Drug Discovery
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Artificial intelligence to deep learning: machine intelligence approach for drug discovery
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Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
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Metadata
- Authors
- De Vivo, M., Masetti, M., Bottegoni, G., & Cavalli, A.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-02-08
- Volume
- 59
- Issue
- 9
- Pages
- 4035-4061
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W2271736303
- Cited by
- 1,297
- References
- 235
- FWCI
- 78.90
- Type
- journal article
- Language
- en
- Open access
- hybrid
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