The DOI matches its Crossref record; 173 of the 173 references it cites were found in a registry or an index.
Combining docking and molecular dynamic simulations in drug design
Abstract
A rational approach is needed to maximize the chances of finding new drugs, and to exploit the opportunities of potential new drug targets emerging from genomic and proteomic initiatives, and from the large libraries of small compounds now readily available through combinatorial chemistry. Despite a shaky early history, computer-aided drug design techniques can now be effective in reducing costs and speeding up drug discovery. This happy outcome results from development of more accurate and reliable algorithms, use of more thoughtfully planned strategies to apply them, and greatly increased computer power to allow studies with the necessary reliability to be performed. Our review focuses on applications and protocols, with the main emphasis on critical analysis of recent studies where docking calculations and molecular dynamics (MD) simulations were combined to dock small molecules into protein receptors. We highlight successes to demonstrate what is possible now, but also point out drawbacks and future directions. The review is structured to lead the reader from the simpler to more compute-intensive methods. Thus, while inexpensive and fast docking algorithms can be used to scan large compound libraries and reduce their size, more accurate but expensive MD simulations can be applied when a few selected ligand candidates remain. MD simulations can be used: during the preparation of the protein receptor before docking, to optimize its structure and account for protein flexibility; for the refinement of docked complexes, to include solvent effects and account for induced fit; to calculate binding free energies, to provide an accurate ranking of the potential ligands; and in the latest developments, during the docking process itself to find the binding site and correctly dock the ligand a priori.
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Cites
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Cited by
Molecular Docking: A Powerful Approach for Structure-Based Drug Discovery
Meng, X.-Y., Zhang, H.-X., Mezei, M., & Cui, M. (2011) · Current Computer Aided-Drug Design · doi:10.2174/157340911795677602 · Cited by 3,771
Molecular dynamics simulations and novel drug discovery
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Thafar, M. A., Olayan, R. S., Ashoor, H., Albaradei, S., Bajic, V. B., Gao, X., Gojobori, T., & Essack, M. (2020) · Journal of Cheminformatics · doi:10.1186/s13321-020-00447-2 · Cited by 143
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning
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Metadata
- Authors
- Alonso, H., Bliznyuk, A. A., & Gready, J. E.
- Venue
- Medicinal Research Reviews
- Publisher
- Wiley
- Published
- 2006
- Volume
- 26
- Issue
- 5
- Pages
- 531-568
- ISSN
- 0198-6325 (ISSN-L)
- 1098-1128
- OpenAlex
- W2149302140
- Cited by
- 759
- References
- 173
- FWCI
- 20.16
- Type
- journal article
- Language
- en
- Open access
- closed
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