Drug-resistant strains are rapidly selected during AIDS therapy because of the high rate of mutation in HIV. In this report, we present an evolutionary simulation method for analysis of viral mutation and its use for optimization of HIV-1 protease drugs to improve their robustness in the face of resistance mutation. We first present an analysis of the range of resistant mutants that produce viable viruses by using a volume-based viral fitness model. Then, we analyze how this range of mutant proteases allows development of resistance to an optimal inhibitor previously designed by computational coevolution techniques. Finally, we evaluate the resistance patterns of commercially available drugs, and we discuss how resistance might be overcome by optimizing the size of specific side-chains of these inhibitors.
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Stoffler et al. (2002) studied this question.
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