Molecular mechanisms of HIV-1 resistance to nucleoside reverse transcriptase inhibitors (NRTIs)

Sluis‐Cremer, Nicolas; Arion, Dominique; Parniak, Michael A.

doi:10.1007/pl00000626

Cited by 103 publications

(92 citation statements)

References 65 publications

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“…Therefore, we cannot investigate its structural basis of resistant mutations by using MD simulations and free energy decompositions. To date, three biochemical mechanisms of NRTI drug resistance have been uncovered or proposed (3,17). These different resistance mechanisms seem to correlate with different sets of mutations in RT (17), but further biochemical investigations are needed to confirm which mechanism corresponds to which independent mutation set (SI Text).…”

Section: Resultsmentioning

confidence: 99%

“…To date, three biochemical mechanisms of NRTI drug resistance have been uncovered or proposed (3,17). These different resistance mechanisms seem to correlate with different sets of mutations in RT (17), but further biochemical investigations are needed to confirm which mechanism corresponds to which independent mutation set (SI Text). Unlike NRTIs, NNRTIs bind to a hydrophobic pocket in RT close to the active site and their binding can block the catalytic activity of RT.…”

Section: Resultsmentioning

confidence: 99%

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Detecting and understanding combinatorial mutation patterns responsible for HIV drug resistance

Zhang

Hou

Wang

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

108

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We propose a systematic approach for a better understanding of how HIV viruses employ various combinations of mutations to resist drug treatments, which is critical to developing new drugs and optimizing the use of existing drugs. By probabilistically modeling mutations in the HIV-1 protease or reverse transcriptase (RT) isolated from drug-treated patients, we present a statistical procedure that first detects mutation combinations associated with drug resistance and then infers detailed interaction structures of these mutations. The molecular basis of our statistical predictions is further studied by using molecular dynamics simulations and free energy calculations. We have demonstrated the usefulness of this systematic procedure on three HIV drugs, (Indinavir, Zidovudine, and Nevirapine), discovered unique interaction features between viral mutations induced by these drugs, and revealed the structural basis of such interactions.Bayesian model selection | free energy calculation | Markov chain Monte Carlo | molecular dynamics | mutation interactions H IV drug-resistance, which is caused by mutations of viral proteins that disrupt the drugs' binding but do not affect the viral survival, is a major hurdle that hinders a successful treatment of AIDS (1, 2). Due to the high rate and low fidelity of HIV replication, resistant strains quickly become dominant in a viral population under the selection pressure of a drug. By sequencing viral strains in the treated-patient isolates, genotypic data have been accumulated for the drugs targeting two viral enzymes, protease and reverse transcriptase, that are essential to the virus's replication. Because each mutation of the viral protein is not equally important for drug resistance, the observed, complicated mutation patterns are difficult to interpret (3, 4) and are limited in helping physicians design the best therapeutic regimen for a patient (5) (Fig. 1A).In past decades, many statistical learning methods (3, 4, 67-8) have been employed to help predict phenotypes from genotypes. There are also rule-based systems that infer drug-resistance levels from sequence information such as the Stanford University HIV Drug Resistance Database (Stanford HIVdb). However, these methods provide little insight on the genetic and molecular basis of drug resistance and often give inconsistent results when analyzing the same input mutation data (4, 6).In the present study, we investigated the problem of mutation interactions of the HIV induced by a certain drug treatment. Using a unique probabilistic model, we first detect resistant mutation combinations (9) and infer the interaction dependence structure of these combinations. Then, we use molecular dynamics (MD) simulations to reveal the molecular basis of how these mutations interact with each other to interfere with the drugs' binding. We have shown that our procedure is applicable to different antiretroviral drugs treating different types of HIV infection by analyzing the sequence mutations induced by three different drug treatments: a...

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Detecting and understanding combinatorial mutation patterns responsible for HIV drug resistance

Zhang

Hou

Wang

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

108

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“…Two kinetically distinct mechanisms of HIV-1 resistance to NRTI have been described previously (6,30). One mechanism involves selective decreases in NRTI-TP versus normal dNTP incorporation during viral DNA synthesis.…”

Section: Resultsmentioning

confidence: 99%

Molecular Mechanism by Which the K70E Mutation in Human Immunodeficiency Virus Type 1 Reverse Transcriptase Confers Resistance to Nucleoside Reverse Transcriptase Inhibitors

Sluis‐Cremer

Sheen

Zelina

et al. 2007

Antimicrob Agents Chemother

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The K70E mutation in human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) has become more prevalent in clinical samples, particularly in isolates derived from patients for whom triple-nucleoside regimens that include tenofovir (TNV), abacavir, and lamivudine (3TC) failed. To elucidate the molecular mechanism by which this mutation confers resistance to these nucleoside RT inhibitors (NRTI), we conducted detailed biochemical analyses comparing wild-type (WT), K70E, and K65R HIV-1 RT. Pre-steady-state kinetic experiments demonstrate that the K70E mutation in HIV-1 RT allows the enzyme to discriminate between the natural deoxynucleoside triphosphate substrate and the NRTI triphosphate (NRTI-TP). Compared to the WT enzyme, K70E RT showed 2.1-, 2.3-, and 3.5-foldhigher levels of resistance toward TNV-diphosphate, carbovir-TP, and 3TC-TP, respectively. By comparison, K65R RT demonstrated 12.4-, 12.0-, and 13.1-fold-higher levels of resistance, respectively, toward the same analogs. NRTI-TP discrimination by the K70E (and K65R) mutation was primarily due to decreased rates of NRTI-TP incorporation and not to changes in analog binding affinity. The K65R and K70E mutations also profoundly impaired the ability of RT to excise 3 -azido-2 ,3 -dideoxythymidine monophosphate (AZT-MP) and other NRTI-MP from the 3 end of a chain-terminated primer. When introduced into an enzyme with the thymidine analog mutations (TAMs) M41L, L210W, and T215Y, the K70E mutation inhibited ATP-mediated excision of AZT-MP. Taken together, these findings indicate that the K70E mutation, like the K65R mutation, reduces susceptibility to NRTI by selectively decreasing NRTI-TP incorporation and is antagonistic to TAM-mediated nucleotide excision.

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“…To better understand how p53 proteins orchestrate the cellular response to HIV infection, it may be essential to examine the location and extent of p53 binding to viral nucleic acids and to damaged cellular DNA and the interaction of p53 with other proteins in virus-infected cells. It was suggested that it is biologically beneficial for the virus to harbor a low-fidelity RT for purposes such as allowing the virus to evade the immune system of the host, as well as drugs aimed against the virus (Mansky and Temin, 1995;Sluis-Cremer et al, 2000). Hence, a question arises regarding whether the presence of exonuclease activity in cytoplasm is of interest for the virus.…”

Section: Discussionmentioning

confidence: 99%

P53 in cytoplasm may enhance the accuracy of DNA synthesis by human immunodeficiency virus type 1 reverse transcriptase

et al. 2004

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The tumor suppressor protein p53 displays 3 0 -5 0 exonuclease activity and can provide a proofreading function for DNA polymerases. Reverse transcriptase (RT) of human immunodeficiency virus (HIV)-1 is responsible for the conversion of the viral genomic ssRNA into the proviral DNA in the cytoplasm. The relatively low fidelity of HIV-1 RT was implicated as a dominant factor contributing to the genetic variability of the virus. The lack of intrinsic 3 0 -5 0 exonuclease activity, the formation of 3 0 -mispaired DNA and the subsequent extension of this DNA were shown to be determinants for the low fidelity of HIV-1 RT. It was of interest to analyse whether the cytoplasmic proteins may affect the accuracy of DNA synthesis by RT. We investigated the fidelity of DNA synthesis by HIV-1 RT with and without exonucleolytic proofreading provided by cytoplasmic fraction of LCC2 cells expressing high level of wild-type functional p53. Two basic features related to fidelity of DNA synthesis were studied: the misinsertion and mispair extension. The misincorporation of noncomplementary deoxynucleotides into nascent DNA and subsequent mispair extension by HIV-1 RT were substantially decreased in the presence of cytoplasmic fraction of LCC2 cells with both RNA/DNA and DNA/DNA template-primers with the same target sequence. The mispair extension frequencies obtained with the HIV-1 RT in the presence of cytoplasmic fraction of LCC2 cells were significantly lower (about 2.8-15-fold) than those detected with the purified enzyme. In addition, the productive interaction between polymerization (by HIV-1 RT) and exonuclease (by p53 in cytoplasm) activities was observed; p53 preferentially hydrolyses mispaired 3 0 -termini, permitting subsequent extension of the correctly paired 3 0 -terminus by HIV-1 RT. The data suggest that p53 in cytoplasm may affect the accuracy of DNA replication and the mutation spectra of HIV-1 RT by acting as an external proofreader. Furthermore, the decrease in error-prone DNA synthesis with RT in the presence of external exonuclease, provided by cytoplasmic p53, may partially account for lower mutation rate of HIV-1 observed in vivo.

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Molecular mechanisms of HIV-1 resistance to nucleoside reverse transcriptase inhibitors (NRTIs)

Cited by 103 publications

References 65 publications

Detecting and understanding combinatorial mutation patterns responsible for HIV drug resistance

Detecting and understanding combinatorial mutation patterns responsible for HIV drug resistance

Molecular Mechanism by Which the K70E Mutation in Human Immunodeficiency Virus Type 1 Reverse Transcriptase Confers Resistance to Nucleoside Reverse Transcriptase Inhibitors

P53 in cytoplasm may enhance the accuracy of DNA synthesis by human immunodeficiency virus type 1 reverse transcriptase

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