ArticleJournal of chemical information and modeling2011
Approximating protein flexibility through dynamic pharmacophore models: application to fatty acid amide hydrolase (FAAH).
Article in Journal of chemical information and modeling, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 19 citations in OpenAlex.
- Machine Learning and Computational Chemistry for the Endocannabinoid System.Methods in molecular biology (Clifton, N.J.) · 2023Review
- Identifying FAAH Inhibitors as New Therapeutic Options for the Treatment of Chronic Pain through Drug Repurposing.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Comparing pharmacophore models derived from crystallography and NMR ensembles.Journal of computer-aided molecular design · 2017Article
- Pharmacophore modeling using site-identification by ligand competitive saturation (SILCS) with multiple probe molecules.Journal of chemical information and modeling · 2015Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
A structure-based drug discovery method is described that incorporates target flexibility through the use of an ensemble of protein conformations. The approach was applied to fatty acid amide hydrolase (FAAH), a key deactivating enzyme in the endocannabinoid system. The resultant dynamic pharmacophore models are rapidly able to identify known FAAH inhibitors over drug-like decoys. Different sources of FAAH conformational ensembles were explored, with both snapshots from molecular dynamics simulations and a group of X-ray structures performing well. Results were compared to those from docking and pharmacophore models generated from a single X-ray structure. Increasing conformational sampling consistently improved the pharmacophore models, emphasizing the importance of incorporating target flexibility in structure-based drug design.
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