From docking false-positive to active anti-HIV agent

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.

Figure 1

Computed structure for 1 bound to HIV-1 reverse transcriptase from Glide docking followed by energy minimization with MacroModel. Only protein residues in the first layer around the ligand are illustrated. The ligand is positioned as expected from known structures such as for 4.,

Figure 2

Training results for scoring using BOMB for 339 complexes with HIV-RT (magenta – uracil derivatives, green – analogs of 2), COX-2 (blue), FKBP (red), and p38 kinase (black). The correlation coefficient for the fit, r², is 0.58 and the rms error is 0.82 log unit. Indicator variables are used to provide constant offsets for three datasets.

Figure 3

Structure for the complex of 1 with HIV-RT as computed by BOMB. The 176 residues nearest the ligand are included in the calculations.

Scheme 1

Recent NNRTI Hits from HTS (Reference 12)

Scheme 2

Synthesis of 2,5-oxadiazole derivatives.