Analysis of the protease sequences of HIV-1 infected individuals after Indinavir monotherapy.

ABSTRACT

BACKGROUND: Protease inhibitors (PI) are an important HIV-1 treatment tool. The HIV-1 genetic diversity as a result of antiretroviral exposure is a potential barrier to successful antiretroviral therapy. OBJECTIVES: To describe the impact of the selective pressure of the PI Indinavir in the protease region of the pol gene of HIV-1. STUDY DESIGN: We have examined the extent of protease sequence heterogeneity in previously antiretroviral drug naive HIV-1 infected individuals receiving Indinavir as monotherapy for at least 48 weeks. RESULTS: Analysis based on the consensus of this group of sequences showed regions with higher and lower polymorphism. The degree of genetic variation was greater in regions less critical for the structure and function of the enzyme. To investigate the selective pressure imposed by drug therapy, we have analyzed the rate of synonymous (ds) and nonsynonymous (dn) substitutions. The three critical regions for enzyme activity showed ds/dn ratio >1. whereas other regions had ds/dn ratio <1. The detected amino acid mutations had a trend to be conservative, thus maintaining the physical chemical amino acid characteristics. Phylogenetic analysis established the presence of subtype B (n=38), subtype F (n=9), and B/F recombinants within the protease region of pol gene (n=3). More prevalent detected mutations, thought to contribute to antiretroviral resistance, were L63P (42%), L10I (35%), M36I (30%), V82A/T/F (26%). CONCLUSIONS: A great deal of predicted cross-resistance between PIs was observed. Out of the 50 individuals, 34% were considered to have major mutations to Indinavir, and 66% had minor or no mutations to Indinavir. Viral loads were significantly higher among patients with major mutations, compared with patients minor/no mutations, although no differences in the CD4 counts were found. The viral load at baseline and nadir (week 4) was able to predict the group of individuals with greater chances of selecting drug resistance related mutations.