Mona Minkara - Multiple Drugs and Multiple Targets: An Analysis of the Electrostatic Determinants of Binding Between Non-nucleoside HIV-1 Reverse Transcriptase (RT) Inhibitors and Variants of HIV-1 RT

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  Minkara, M. S.; Davis, P. H.;   Radhakrishnan; M. L. “Multiple Drugs and Multiple Targets: An   Analysis of the Electrostatic Determinants of Binding Between   Non-nucleoside HIV-1 Reverse Transcriptase (RT) Inhibitors and   Variants of HIV-1 RT” Proteins 2012,   80, 573-590.


    We present a systematic, computational analysis of the   electrostatic component of binding of three HIV-1 RT   inhibitors—nevirapine (NVP), efavirenz (EFV), and the recently   approved rilpivirine (RPV)—to wild-type (WT) and mutant variants   of RT. Electrostatic charge optimization was applied to determine   how suited each molecule's charge distribution is for binding WT   and individual mutants of HIV-1 RT. Although the charge   distributions of NVP and EFV are rather far from being optimal   for tight binding, RPVs charge distribution is close to the   theoretical, optimal charge distribution for binding WT HIV-1 RT,   although slight changes in charge can dramatically impact binding   energetics. Moreover, toward the L100I/K103N double mutant, RPVs   charge distribution is quite far from optimal. We also determine   the contributions of chemical moieties on each molecule toward   the electrostatic component of binding and show that different   regions of a drug molecule may be used for recognition by   different RT variants. The electrostatic contributions of certain   RT residues toward drug binding are also computed to highlight   critical residues for each interaction. Finally, the charge   distribution of RPV is optimized to promiscuously bind to three   RT variants rather than to each one in turn, with the resulting   charge distribution being a compromise between the optimal charge   distributions to each individual variant. Taken together, this   work demonstrates that even in a binding site considered quite   hydrophobic, electrostatics play a subtle yet varying role that   must be considered in designing next-generation molecules that   recognize rapidly mutating targets.

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