Computational coevolution of antiviral drug resistance

An understanding of antiviral drug resistance is important in the design of effective drugs. Comprehensive features of the interaction between drug de signs and resistance mutations are difficult to study experimentally becaus e of the very large numbers of drugs and mutants involved. We describe a co mputational framework for studying antiviral drug resistance. Data on HIV-1 protease are used to derive an approximate model that predicts interaction of a wide range of mutant forms of the protease with a broad class of prot ease inhibitors. An algorithm based on competitive coevolution is used to f ind highly resistant mutant forms of the protease, and effective inhibitors against such mutants, in the context of the model. We use this method to c haracterize general features of inhibitors that are effective in overcoming resistance, and to study related issues of selection pathways, cross-resis tance, and combination therapies.