Journal of Chemical Information and Modeling · 2015 · 95 citations · 31 references
PharmacyMedicinal ChemistryPharmacologyComputational Medicinal ChemistryDrug DesignDrug DiscoveryChemical Space ExplorationComputational Drug DiscoveryLigand-based DesignMolecular SimilarityProtein-ligand DockingVirtual ScreeningButyrylcholinesterase InhibitionChemical Scaffold HoppingClique AlgorithmsComputer-aided Drug DiscoveryLigand ScreeningLigand-based ScreeningMolecular Similarity SearchSimilarity Searching
We developed LiSiCA (ligand similarity using clique algorithm)--ligand-based virtual screening software that uses a fast maximum clique algorithm to find two- and three-dimensional similarities between pairs of molecules and applied it to the discovery of novel potent butyrylcholinesterase inhibitors. LiSiCA, which runs in parallel on multiple processor cores, was successfully tested on the Database of Useful Decoys-Enhanced, to evaluate its ability to discriminate active molecules from decoys. We then applied LiSiCA for the discovery of novel inhibitors of human butyrylcholinesterase, a promising anti-Alzheimer target, using a known inhibitor as the reference compound. We demonstrated that LiSiCA is capable of finding potent nanomolar inhibitors, whose scaffolds differed from the reference compound, thus proving its ability for scaffold hopping and usefulness in drug discovery.
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