HIV-1 Subtype B Protease and Reverse Transcriptase Amino Acid Covariation

Abstract

Despite the high degree of HIV-1 protease and reverse transcriptase (RT) mutation in the setting of antiretroviral therapy, the spectrum of possible virus variants appears to be limited by patterns of amino acid covariation. We analyzed patterns of amino acid covariation in protease and RT sequences from more than 7,000 persons infected with HIV-1 subtype B viruses obtained from the Stanford HIV Drug Resistance Database (http://hivdb.stanford.edu). In addition, we examined the relationship between conditional probabilities associated with a pair of mutations and the order in which those mutations developed in viruses for which longitudinal sequence data were available. Patterns of RT covariation were dominated by the distinct clustering of Type I and Type II thymidine analog mutations and the Q151M-associated mutations. Patterns of protease covariation were dominated by the clustering of nelfinavir-associated mutations (D30N and N88D), two main groups of protease inhibitor (PI)–resistance mutations associated either with V82A or L90M, and a tight cluster of mutations associated with decreased susceptibility to amprenavir and the most recently approved PI darunavir. Different patterns of covariation were frequently observed for different mutations at the same position including the RT mutations T69D versus T69N, L74V versus L74I, V75I versus V75M, T215F versus T215Y, and K219Q/E versus K219N/R, and the protease mutations M46I versus M46L, I54V versus I54M/L, and N88D versus N88S. Sequence data from persons with correlated mutations in whom earlier sequences were available confirmed that the conditional probabilities associated with correlated mutation pairs could be used to predict the order in which the mutations were likely to have developed. Whereas accessory nucleoside RT inhibitor–resistance mutations nearly always follow primary nucleoside RT inhibitor–resistance mutations, accessory PI-resistance mutations often preceded primary PI-resistance mutations. The identification of which mutations in a protein covary has played a major role in both structural and evolutionary biology. Covariation analysis has been used to help predict unsolved protein structures and to better understand the functions of proteins with known structures. The large number of published genetic sequences of the targets of HIV-1 therapy has provided an unprecedented opportunity to identify dependencies among mutations in these proteins that can be exploited to design inhibitors that have high genetic barriers to resistance. In our analysis, we identified many pairs of covarying drug-resistance mutations in HIV-1 protease and reverse transcriptase and organized them into clusters of mutations that often develop in a predictable order. Inhibitors that are active against early drug-resistant mutants are likely to be less prone to the development of resistance, whereas inhibitors that are active against fully evolved clusters of mutations may be useful drugs for salvage therapy.