The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Docking Screens for Novel Ligands Conferring New Biology: Miniperspective
Open accessAbstract
It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking's greatest impact over the next few years.
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Cites
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ZINC − A Free Database of Commercially Available Compounds for Virtual Screening
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Self-citationZINC 15 – Ligand Discovery for Everyone
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Self-citationDirectory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking.
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Self-citationPredicting Absolute Ligand Binding Free Energies to a Simple Model Site
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Self-citationCovalent docking using autodock: two-point attractor and flexible side chain methods.
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Cited by
Ultra-large library docking for discovering new chemotypes
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Self-citationA practical guide to large-scale docking
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“For instance, docking typically undersamples conformational states, ignores important terms (e.g., ligand strain) and approximates terms that it does include (e.g., fi xed potentials) 19,20 .”
BackgroundSelf-citationSynthon-based ligand discovery in virtual libraries of over 11 billion compounds
Sadybekov, A. A., Sadybekov, A. V., Liu, Y., Iliopoulos-Tsoutsouvas, C., Huang, X.-P., Pickett, J., Houser, B., Patel, N., Tran, N. K., Tong, F., et al. (2022) · Nature · doi:10.1038/s41586-021-04220-9 · Cited by 417
“Standard libraries for high-throughput screening (HTS) 10 and virtual ligand screening (VLS) 11–13 have been historically limited to fewer than 10 million available compounds, which is a small fraction of the enormous chemical space, estimated to be 10 20 to 10 60 drug-like compounds 14,15 .”
BackgroundPerformance of machine-learning scoring functions in structure-based virtual screening.
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Virtual discovery of melatonin receptor ligands to modulate circadian rhythms
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Metadata
- Authors
- Irwin, J. J., & Shoichet, B. K.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2016-03-15
- Volume
- 59
- Issue
- 9
- Pages
- 4103-4120
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W2274656763
- Cited by
- 277
- References
- 17
- FWCI
- 32.45
- Type
- journal article
- Language
- en
- Open access
- green
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