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The role of phenylalanine-119 of the reverse transcriptase of mouse mammary tumour virus in DNA synthesis, ribose selection and drug resistance.

ABSTRACT: Phe-119 in the reverse transcriptase (RT) of mouse mammary tumour virus (MMTV) is homologous with Tyr-115 in HIV type 1 (HIV-1) RT and to Phe-155 in murine leukaemia virus (MLV) RT. By mutating these residues in HIV-1 and MLV RTs (which are strict DNA polymerases) the enzymes were shown to function also as RNA polymerases. Owing to the uniqueness of MMTV as a type B retrovirus, we have generated a Phe-119-Val mutant of MMTV RT to study the involvement of this residue in affecting the catalytic features of this RT. The data presented here show that the mutant MMTV RT can incorporate both deoxyribonucleosides and ribonucleosides while copying either RNA or DNA. In addition, this mutant RT shows resistance to nucleoside analogues and an enhanced fidelity of DNA synthesis; all relative to the wild-type enzyme. The Phe-119-Val mutant is also different from the wild-type enzyme in its preference for most template primers tested and in its ability to synthesize DNA under non-processive and processive conditions. Overall, it is likely that the aromatic side chain of Phe-119 is located at the dNTP-binding site of MMTV RT and thus might be part of a putative "steric gate" that prevents the incorporation of nucleoside triphosphates. Since the only three-dimensional structures of RTs published so far are those of HIV-1 and MLV, it is likely that MMTV RT folds quite similarly to these RTs.

SUBMITTER: Entin-Meer M

PROVIDER: S-EPMC1222887 | biostudies-other | 2002 Oct

REPOSITORIES: biostudies-other

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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.

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The role of phenylalanine-119 of the reverse transcriptase of mouse mammary tumour virus in DNA synthesis, ribose selection and drug resistance.

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