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Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors.

ABSTRACT: Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

SUBMITTER: Santos LH

PROVIDER: S-EPMC4660614 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors.

Santos Lucianna Helene LH Ferreira Rafaela Salgado RS Caffarena Ernesto Raúl ER

Memorias do Instituto Oswaldo Cruz 20151101 7

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successf ...[more]

PMID: 26560977

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Project description:The development of antiviral drug resistance is an important problem in the treatment of human immunodeficiency virus type 1 (HIV-1) infection. Potent antiretroviral therapy is currently used for treatment, and typically consists of at least two reverse transcriptase (RT) inhibitors. We have previously reported that both drugs and drug-resistant RT mutants can increase virus mutation frequencies. To further assess the contributions of nucleoside RT inhibitors (NRTIs), nonnucleoside RT inhibitors (NNRTIs), and drug-resistant RTs to HIV mutagenesis, a new high-throughput assay system was developed. This assay system was designed to specifically detect frameshift mutations in the luciferase gene in a single virus replication cycle. New drug-resistant RTs were identified that significantly altered virus mutation frequencies. Consistent with our previous observations of NRTIs, abacavir, stavudine, and zalcitabine increased HIV-1 mutation frequencies, supporting the general hypothesis that the NRTIs currently used in antiviral drug therapy increase virus mutation frequencies. Interestingly, similar observations were made with NNRTIs. This is the first report to show that NNRTIs can influence virus mutation frequencies. NNRTI combinations, NRTI-NNRTI combinations, and combinations of drug and drug-resistant RTs led to significant changes in the virus mutation frequencies compared to virus replication of drug-resistant virus in the absence of drug or wild-type virus in the presence of drug. This indicates that combinations of RT drugs or drugs and drug-resistant virus created during the evolution of drug resistance can act together to increase HIV-1 mutation frequencies, which would have important implications for drug therapy regimens. Finally, the influence of drug-resistant RT mutants from CRF01_AE viruses on HIV-1 mutation frequencies was analyzed and it was found that only a highly drug resistant RT led to altered virus mutation frequencies. The results further suggest that high-level drug-resistant RT can significantly influence virus mutation frequencies. A structural model that explains the mutation frequency data is discussed.

Dataset Information

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors.

Publications

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors.

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