The DOI matches its Crossref record; 151 of the 151 references it cites were found in a registry or an index.
Challenges, Applications, and Recent Advances of Protein-Ligand Docking in Structure-Based Drug Design
Open accessAbstract
The docking methods used in structure-based virtual database screening offer the ability to quickly and cheaply estimate the affinity and binding mode of a ligand for the protein receptor of interest, such as a drug target. These methods can be used to enrich a database of compounds, so that more compounds that are subsequently experimentally tested are found to be pharmaceutically interesting. In addition, like all virtual screening methods used for drug design, structure-based virtual screening can focus on curated libraries of synthesizable compounds, helping to reduce the expense of subsequent experimental verification. In this review, we introduce the protein-ligand docking methods used for structure-based drug design and other biological applications. We discuss the fundamental challenges facing these methods and some of the current methodological topics of interest. We also discuss the main approaches for applying protein-ligand docking methods. We end with a discussion of the challenging aspects of evaluating or benchmarking the accuracy of docking methods for their improvement, and discuss future directions.
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A new paradigm for applying deep learning to protein–ligand interaction prediction
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Metadata
- Authors
- Grinter, S., & Zou, X.
- Venue
- Molecules
- Publisher
- MDPI AG
- Published
- 2014-07-11
- Volume
- 19
- Issue
- 7
- Pages
- 10150-10176
- ISSN
- 1420-3049 (ISSN-L)
- OpenAlex
- W2000864931
- Cited by
- 260
- References
- 151
- FWCI
- 20.43
- Type
- journal article
- Language
- en
- Open access
- gold
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