ArticleACS omega2017
Compound Ranking Based on Fuzzy Three-Dimensional Similarity Improves the Performance of Docking into Homology Models of G-Protein-Coupled Receptors.
Article in ACS omega, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Antioxidant evaluation and computational prediction of prospective drug-like compounds from polyphenolic-rich extract of Hibiscus cannabinus L. seed as antidiabetic and neuroprotective targets: assessment through in vitro and in silico studies.BMC complementary medicine and therapies · 2023Article
- Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches.Molecules (Basel, Switzerland) · 2020Review
- Exploring ensembles of bioactive or virtual analogs of X-ray ligands for shape similarity searching.Journal of computer-aided molecular design · 2018Article
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Authors and funding
2 authors.
Funding
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Abstract
Ligand docking into homology models of G-protein-coupled receptors (GPCRs) is a widely used approach in computational compound screening. The generation of "double-hypothetical" models of ligand-target complexes has intrinsic accuracy limitations that further complicate compound ranking and selection compared to those of X-ray structures. Given these uncertainties, we have explored "fuzzy 3D similarity" between hypothetical binding modes of known ligands in homology models and docking poses of database compounds as an alternative to conventional scoring schemes. Therefore, GPCR homology models at varying accuracy levels were generated and used for docking. Increases in recall performance were observed for fuzzy 3D similarity ranking using single or multiple ligand poses compared to that of conventional scoring functions and interaction fingerprints. Fuzzy similarity ranking was also successfully applied to docking into an external model of a GPCR for which no experimental structure is currently available. Taken together, our results indicate that the use of putative ligand poses, albeit approximate at best, increases the odds of identifying active compounds in docking screens of GPCR homology models.
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Registered trials
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