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Evolving understanding of HIV-1 reverse transcriptase structure, function, inhibition, and resistance.

ABSTRACT: The essential role of reverse transcription in the HIV life cycle is illustrated by the fact that half of the ∼30 FDA-approved drugs for HIV treatment target HIV-1 reverse transcriptase (RT). Even though more than 160 structures of RT deposited in the Protein Data Bank (PDB) have revealed the molecular architecture of RT in great detail, some key states of RT function and inhibition remain still unknown. Recent structures of RT initiation complexes, RT poised for RNA hydrolysis, and RT with approved drugs and investigational compounds have provided a deeper understanding of RT function and inhibition, suggesting novel avenues for targeting this central enzyme of HIV.

SUBMITTER: Xavier Ruiz F

PROVIDER: S-EPMC7596924 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Evolving understanding of HIV-1 reverse transcriptase structure, function, inhibition, and resistance.

Xavier Ruiz Francesc F Arnold Eddy E

Current opinion in structural biology 20200111

The essential role of reverse transcription in the HIV life cycle is illustrated by the fact that half of the ∼30 FDA-approved drugs for HIV treatment target HIV-1 reverse transcriptase (RT). Even though more than 160 structures of RT deposited in the Protein Data Bank (PDB) have revealed the molecular architecture of RT in great detail, some key states of RT function and inhibition remain still unknown. Recent structures of RT initiation complexes, RT poised for RNA hydrolysis, and RT with appr ...[more]

PMID: 31935541

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Project description:BackgroundSuccessful management of chronic human immunodeficiency virus type 1 (HIV-1) infection with a cocktail of antiretroviral medications can be negatively affected by the presence of drug resistant mutations in the viral targets. These targets include the HIV-1 protease (PR) and reverse transcriptase (RT) proteins, for which a number of inhibitors are available on the market and routinely prescribed. Protein mutational patterns are associated with varying degrees of resistance to their respective inhibitors, with extremes that can range from continued susceptibility to cross-resistance across all drugs.ResultsHere we implement statistical learning algorithms to develop structure- and sequence-based models for systematically predicting the effects of mutations in the PR and RT proteins on resistance to each of eight and eleven inhibitors, respectively. Employing a four-body statistical potential, mutant proteins are represented as feature vectors whose components quantify relative environmental perturbations at amino acid residue positions in the respective target structures upon mutation. Two approaches are implemented in developing sequence-based models, based on use of either relative frequencies or counts of n-grams, to generate vectors for representing mutant proteins. To the best of our knowledge, this is the first reported study on structure- and sequence-based predictive models of HIV-1 PR and RT drug resistance developed by implementing a four-body statistical potential and n-grams, respectively, to generate mutant attribute vectors. Performance of the learning methods is evaluated on the basis of tenfold cross-validation, using previously assayed and publicly available in vitro data relating mutational patterns in the targets to quantified inhibitor susceptibility changes.ConclusionOverall performance results are competitive with those of a previously published study utilizing a sequence-based strategy, while our structure- and sequence-based models provide orthogonal and complementary prediction methodologies, respectively. In a novel application, we describe a technique for identifying every possible pair of RT inhibitors as either potentially effective together as part of a cocktail, or a combination that is to be avoided.

Dataset Information

Evolving understanding of HIV-1 reverse transcriptase structure, function, inhibition, and resistance.

Publications

Evolving understanding of HIV-1 reverse transcriptase structure, function, inhibition, and resistance.

Similar Datasets

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