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. Proteins 2012. © 2011 Wiley Periodicals, Inc.