Natural polymorphisms and unusual mutations in HIV-1 protease with potential antiretroviral resistance: a bioinformatic analysis
1 Doctorado en Farmacología, Departamento de Fisiología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, México
2 Laboratorio de Inmunodeficiencias y Retrovirus Humanos, Centro de Investigación Biomédica de Occidente, CMNO, IMSS, Guadalajara 44340, México
3 Unidad de Investigación Cardiovascular, Departamento de Fisiología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, México
4 División de Excelencia Clínica, Coordinación Médica de Unidades de Alta Especialidad, Unidad de Atención Médica, IMSS, México, D.F 06700, México
5 UMAE, Hospital de Especialidades, CMNO, IMSS, Guadalajara 44340, México
6 Departamento de Producción Agrícola, Centro Universitario de Ciencias Biológicas y Agropecuarias, Universidad de Guadalajara, Zapopan 45110, México
7 Departamento de Clínicas Médicas, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, México
8 Departamento de Farmacobiología, CUCEI, Universidad de Guadalajara, Guadalajara 44430, México
BMC Bioinformatics 2014, 15:72 doi:10.1186/1471-2105-15-72Published: 15 March 2014
The correlations of genotypic and phenotypic tests with treatment, clinical history and the significance of mutations in viruses of HIV-infected patients are used to establish resistance mutations to protease inhibitors (PIs). Emerging mutations in human immunodeficiency virus type 1 (HIV-1) protease confer resistance to PIs by inducing structural changes at the ligand interaction site. The aim of this study was to establish an in silico structural relationship between natural HIV-1 polymorphisms and unusual HIV-1 mutations that confer resistance to PIs.
Protease sequences isolated from 151 Mexican HIV-1 patients that were naïve to, or subjected to antiretroviral therapy, were examined. We identified 41 unrelated resistance mutations with a prevalence greater than 1%. Among these mutations, nine exhibited positive selection, three were natural polymorphisms (L63S/V/H) in a codon associated with drug resistance, and six were unusual mutations (L5F, D29V, L63R/G, P79L and T91V). The D29V mutation, with a prevalence of 1.32% in the studied population, was only found in patients treated with antiretroviral drugs. Using in silico modelling, we observed that D29V formed unstable protease complexes when were docked with lopinavir, saquinavir, darunavir, tipranavir, indinavir and atazanavir.
The structural correlation of natural polymorphisms and unusual mutations with drug resistance is useful for the identification of HIV-1 variants with potential resistance to PIs. The D29V mutation likely confers a selection advantage in viruses; however, in silico, presence of this mutation results in unstable enzyme/PI complexes, that possibly induce resistance to PIs.