Amprenavir resistance imparted by the I50V mutation in HIV-1 protease can be suppressed by the N88S mutation.
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Asparagine↗
Biomedical subjects
Neil T Parkin
Publications and source records attributed to Neil T Parkin.
Mechanistic basis for reduced viral and enzymatic fitness of HIV-1 reverse transcriptase containing both K65R and M184V mutations.
HIV-1 drug resistance mutations are often inversely correlated with viral fitness, which remains poorly described at the molecular level. Some resistance mutations can also suppress resistance caused by other resistance mutations. We report the molecular mechanisms by which a virus resistant to lamivudine with the M184V reverse transcriptase mutation shows increased susceptibility to tenofovir and can suppress the effects of the tenofovir resistance mutation K65R. Additionally, we report how the decreased viral replication capacity of resistant viruses is directly linked to their decreased ability to use natural nucleotide substrates and that combination of the K65R and M184V resistance mutations leads to greater decreases in viral replication capacity. All together, these results define at the molecular level how nucleoside-resistant viruses can be driven to reduced viral fitness.
Adenine↗
Broad nucleoside reverse-transcriptase inhibitor cross-resistance in human immunodeficiency virus type 1 clinical isolates.
Nucleoside reverse-transcriptase inhibitors (NRTIs) are important components of most antiretroviral combination treatment regimens. Using a large collection of clinical isolates, we characterized patterns of cross-resistance among all NRTIs. Drugs were grouped by the effect of the M184V mutation: susceptibility to group 1 drugs (zidovudine, stavudine, tenofovir, and adefovir) increased when M184V was present, whereas susceptibility to group 2 drugs (didanosine, zalcitabine, abacavir, and lamivudine) decreased. Significant cross-resistance was observed among all NRTIs and was most notable when samples with or without M184V were analyzed separately. An increasing number of thymidine-analogue mutations (TAMs) was associated with a progressive reduction in drug susceptibility for all NRTIs. The modulating effect of M184I/V on drug susceptibility was present regardless of the number of TAMs. The broad range of susceptibility observed for viruses containing the same number of TAMs indicates that the genetic correlates of NRTI resistance remain to be fully elucidated.
Anti-HIV Agents↗
Improving lopinavir genotype algorithm through phenotype correlations: novel mutation patterns and amprenavir cross-resistance.
BACKGROUND: Current genotypic algorithms suggest that the HIV-1 protease inhibitors (PI) lopinavir (LPV) and amprenavir (APV) have distinct resistance profiles. However, phenotypic data indicate that cross-resistance is more common than expected. METHODS: Protease genotype (GT) and phenotype (PT) from 1418 patient viruses with reduced PI susceptibility and/or resistance-associated mutations (training data) were analyzed. Samples were classified as LPV resistant by GT (GT-R) if six or more LPV mutations were present, and by PT (PT-R) if the 50% inhibitory concentration (IC(50)) fold-change (FC) was over 10. RESULTS: There were 182 samples (13%) that were GT-S but PT-R for LPV. A comparison of the mutation prevalence in PT-R/GT-S samples with that in PT-S/GT-S samples identified mutations associated with LPV PT-R. Several previously defined LPV mutations were found to have a stronger than average effect (e.g., M46I/L, I54V/T, V82A/F), and new variants at known positions (e.g., I54A/M/S, V82S) were identified. Other mutations, including known APV resistance mutations, were found to contribute to reduced LPV susceptibility. A new LPV genotypic interpretation algorithm was constructed that improved overall genotypic/phenotypic concordance from 80% to 91%. The algorithm demonstrated a concordance rate of 90% when tested on 523 new samples. Cross-resistance between APV and LPV was greater in samples with primary APV resistance mutations than in those lacking them. CONCLUSIONS: The current LPV mutation score does not fully account for many resistant viruses. Consequently, cross-resistance between LPV and APV is underappreciated. Phenotypic results from large and diverse patient virus populations should be used to guide the development of more accurate GT interpretation algorithms.
Algorithms↗