From Docking False-Positive to Active Anti-HIV Agent

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Abstract

Virtual screening of the Maybridge library of ca. 70 000 compounds was performed using a similarity filter, docking, and molecular mechanics-generalized Born/surface area postprocessing to seek potential non-nucleoside inhibitors of human immunodeficiency virus-1 (HIV-1) reverse transcriptase (NNRTIs). Although known NNRTIs were retrieved well, purchase and assaying of representative, top-scoring compounds from the library failed to yield any active anti-HIV agents. However, the highest-ranked library compound, oxadiazole 1, was pursued as a potential "near-miss" with the BOMB program to seek constructive modifications. Subsequent synthesis and assaying of several polychloro-analogs did yield anti-HIV agents with EC50 values as low as 310 nM. The study demonstrates that it is possible to learn from a formally unsuccessful virtual-screening exercise and, with the aid of computational analyses, to efficiently evolve a false positive into a true active.

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