Over the past 10 years, classical computer-aided molecular design methods have not been frequently applied for the discovery of novel HIV-1 integrase (IN) inhibitors, due to the intrinsic challenges that this enzyme presents. Therefore, a novel approach that combines the chemical information of known integrase inhibitors with the enzymes detailed 3D structure in a stepwise fashion is proposed: (I) use of a pharmacophore model (PM), which takes into account in a weighted fashion the chemical features of known ligands, in analogous manner to the to search the Maybridge and the NCI 3D databases; (II) drug-likeness optimization; (III) virtual high-throughput screening of the hits matching the PM query against 1QS4 wild-type IN structure using different Docking/Scoring combinations; (IV) visual inspection and selection of the hits in function of: binding free energies; binding mode type within the active site; retrieval among the best 20% hits in more than 6 Docking/Scoring protocols at the same time. This approach aims at a rational selection of new potential HIV-1 integrase inhibitors.
Keywords: high throughput docking, hiv Integrase, diketo acid hiv Integrase inhibitors
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