Accurate prediction of HIV-1 drug response from the reverse transcriptase and protease amino acid sequences using sparse models created by convex optimization

ABSTRACT Human foamy virus (HFV), a retrovirus of simian origin which occasionally infects humans, is the basis of retroviral vectors in development for gene therapy. Clinical considerations of how to treat patients developing an uncontrolled infection by either HFV or HFV-based vectors need to be raised. We determined the susceptibility of the HFV to dideoxynucleosides and found that only zidovudine was equally efficient against the replication of human immunodeficiency virus type 1 (HIV-1) and HFV. By contrast, zalcitabine (ddC), lamivudine (3TC), stavudine (d4T), and didanosine (ddI) were 3-, 3-, 30-, and 46-fold less efficient against HFV than against HIV-1, respectively. Some amino acid residues known to be involved in HIV-1 resistance to ddC, 3TC, d4T, and ddI were found at homologous positions of HFV reverse transcriptase (RT). These critical amino acids are located at the same positions in the three-dimensional structure of HIV-1 and HFV RT, suggesting that both enzymes share common patterns of inhibition.

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Effects of the Δ67 Complex of Mutations in Human Immunodeficiency Virus Type 1 Reverse Transcriptase on Nucleoside Analog Excision

Journal of Virology ◽

10.1128/jvi.78.18.9987-9997.2004 ◽

2004 ◽

Vol 78 (18) ◽

pp. 9987-9997 ◽

Cited By ~ 19

Author(s):

Paul L. Boyer ◽

Tomozumi Imamichi ◽

Stefan G. Sarafianos ◽

Edward Arnold ◽

Stephen H. Hughes

Keyword(s):

Human Immunodeficiency Virus ◽

Amino Acid ◽

Reverse Transcriptase ◽

Human Immunodeficiency Virus Type ◽

Virus Type ◽

Amino Acid Substitutions ◽

Wild Type ◽

Coding Region ◽

Immunodeficiency Virus ◽

Hiv 1

ABSTRACT Long-term use of combination therapy against human immunodeficiency virus type (HIV-1) provides strong selective pressure on the virus, and HIV-1 variants that are resistant to multiple inhibitors have been isolated. HIV-1 variants containing amino acid substitutions within the coding region of HIV-1 reverse transcriptase (RT), such as the 3′-azido-3′-deoxythymidine (AZT)-resistant variant AZT-R (M41L/D67N/K70R/T215Y/K219Q) and a variant containing an insertion in the fingers domain (S69SGR70/T215Y), are resistant to the nucleoside RT inhibitor (NRTI) AZT because of an increase in the level of excision of AZT monophosphate (AZTMP) from the primer. While rare, variants have also been isolated which contain deletions in the RT coding region. One such virus, described by Imamichi et al. (J. Virol 74:10958-10964, 2000; J. Virol. 74:1023-1028, 2000; J. Virol. 75:3988-3992, 2001), contains numerous amino acid substitutions and a deletion of codon 67, which we have designated the Δ67 complex of mutations. We have expressed and purified HIV-1 RT containing these mutations. We compared the polymerase and pyrophosphorolysis (excision) activity of an RT with the Δ67 complex of mutations to wild-type RT and the two other AZT-resistant variants described above. All of the AZT-resistant variants we tested excise AZTMP and 9-[2-(R)-(phosphonomethoxy)propyl]adenine (PMPA [tenofovir]) from the end of a primer more efficiently than wild-type RT. Although the variant RTs excised d4TMP less efficiently than AZTMP and PMPA, they were able to excise d4TMP more efficiently than wild-type RT. HIV-1 RT containing the Δ67 complex of mutations was not able to excise as broad a range of NRTIs as the fingers insertion variant SSGR/T215Y, but it was able to polymerize efficiently with low concentrations of deoxynucleoside triphosphates and seems to be able to excise AZTMP and PMPA at lower ATP concentrations than AZT-R or SSGR/T215Y, suggesting that a virus containing the Δ67 complex of mutations would replicate reasonably well in quiescent cells, even in the presence of AZT.

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Thymidine Analogue Excision and Discrimination Modulated by Mutational Complexes Including Single Amino Acid Deletions of Asp-67 or Thr-69 in HIV-1 Reverse Transcriptase

Journal of Biological Chemistry ◽

10.1074/jbc.m111.226100 ◽

2011 ◽

Vol 286 (23) ◽

pp. 20615-20624 ◽

Cited By ~ 12

Author(s):

Mónica Kisic ◽

Tania Matamoros ◽

María Nevot ◽

Jesús Mendieta ◽

Javier Martinez-Picado ◽

...

Keyword(s):

Amino Acid ◽

Reverse Transcriptase ◽

Single Amino Acid ◽

Thymidine Analogue ◽

Hiv 1

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S-1153 Inhibits Replication of Known Drug-Resistant Strains of Human Immunodeficiency Virus Type 1

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.42.6.1340 ◽

1998 ◽

Vol 42 (6) ◽

pp. 1340-1345 ◽

Cited By ~ 82

Author(s):

Tamio Fujiwara ◽

Akihiko Sato ◽

Mohamed El-Farrash ◽

Shigeru Miki ◽

Kenji Abe ◽

...

Keyword(s):

Human Immunodeficiency Virus ◽

Amino Acid ◽

Reverse Transcriptase ◽

Single Amino Acid ◽

Amino Acid Substitutions ◽

Reverse Transcriptase Inhibitors ◽

Human T Cell ◽

Immunodeficiency Virus ◽

Hiv 1

ABSTRACT S-1153 is a new imidazole compound that inhibits human immunodeficiency virus (HIV) type 1 (HIV-1) replication by acting as a nonnucleoside reverse transcriptase inhibitor (NNRTI). This compound inhibits replication of HIV-1 strains that are resistant to nucleoside and nonnucleoside reverse transcriptase inhibitors. S-1153 has a 50% effective concentration in the range of 0.3 to 7 ng/ml for strains with single amino acid substitutions that cause NNRTI resistance, including the Y181C mutant, and also has potent activity against clinical isolates. The emergence of S-1153-resistant variants is slower than that for nevirapine, and S-1153-resistant variants contained at least two amino acid substitutions, including F227L or L234I. S-1153-resistant variants are still sensitive to the nucleoside reverse transcriptase inhibitors zidovudine (AZT) and lamivudine. In a mouse and MT-4 (human T-cell line) in vivo HIV replication model, S-1153 and AZT administered orally showed a marked synergy for the inhibition of HIV-1 replication. S-1153 shows a significant accumulation in lymph nodes, where most HIV-1 infection is thought to occur. S-1153 may be an appropriate candidate for two- to three-drug combination therapy for HIV infection.

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Characterization of HIV-1 reverse transcriptase encoding mutations at the amino acid residues 161 and 208 involved in phosphonoformate resistance

Antiviral Research ◽

10.1016/0166-3542(95)94777-y ◽

1995 ◽

Vol 26 (3) ◽

pp. A268

Author(s):

E. Tramontano ◽

G. Piras ◽

E. Congeddu ◽

J. Mellors ◽

H. Bazmi ◽

...

Keyword(s):

Amino Acid ◽

Reverse Transcriptase ◽

Amino Acid Residues ◽

Hiv 1

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Impact of Drug Resistance-Associated Amino Acid Changes in HIV-1 Subtype C on Susceptibility to Newer Nonnucleoside Reverse Transcriptase Inhibitors

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.04215-14 ◽

2014 ◽

Vol 59 (2) ◽

pp. 960-971 ◽

Cited By ~ 34

Author(s):

Adriaan E. Basson ◽

Soo-Yon Rhee ◽

Chris M. Parry ◽

Ziad El-Khatib ◽

Salome Charalambous ◽

...

Keyword(s):

Amino Acid ◽

Reverse Transcriptase ◽

Resistance Testing ◽

Amino Acid Substitutions ◽

Subtype C ◽

Nnrti Resistance ◽

High Level ◽

Hiv 1 ◽

Phenotypic Susceptibility ◽

Level Resistance

ABSTRACTThe objective of this study was to assess the phenotypic susceptibility of HIV-1 subtype C isolates, with nonnucleoside reverse transcriptase inhibitor (NNRTI) resistance-associated amino acid changes, to newer NNRTIs. A panel of 52 site-directed mutants and 38 clinically derived HIV-1 subtype C clones was created, and the isolates were assessed for phenotypic susceptibility to etravirine (ETR), rilpivirine (RPV), efavirenz (EFV), and nevirapine (NVP) in anin vitrosingle-cycle phenotypic assay. The amino acid substitutions E138Q/R, Y181I/V, and M230L conferred high-level resistance to ETR, while K101P and Y181I/V conferred high-level resistance to RPV. Y181C, a major NNRTI resistance-associated amino acid substitution, caused decreased susceptibility to ETR and, to a lesser extent, RPV when combined with other mutations. These included N348I and T369I, amino acid changes in the connection domain that are not generally assessed during resistance testing. However, the prevalence of these genotypes among subtype C sequences was, in most cases, <1%. The more common EFV/NVP resistance-associated substitutions, such as K103N, V106M, and G190A, had no major impact on ETR or RPV susceptibility. The low-level resistance to RPV and ETR conferred by E138K was not significantly enhanced in the presence of M184V/I, unlike for EFV and NVP. Among patient samples, 97% were resistant to EFV and/or NVP, while only 24% and 16% were resistant to ETR and RPV, respectively. Overall, only a few, relatively rare NNRTI resistance-associated amino acid substitutions caused resistance to ETR and/or RPV in an HIV-1 subtype C background, suggesting that these newer NNRTIs would be effective in NVP/EFV-experienced HIV-1 subtype C-infected patients.

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Synthesis of Heterocyclic Thiourea Compounds with Amino Acid Side Chain as Nonnucleoside Inhibitors of HIV-1 Reverse Transcriptase.

ChemInform ◽

10.1002/chin.200646218 ◽

2006 ◽

Vol 37 (46) ◽

Author(s):

T. K. Venkatachalam ◽

F. M. Uckun

Keyword(s):

Amino Acid ◽

Reverse Transcriptase ◽

Side Chain ◽

Amino Acid Side Chain ◽

Nonnucleoside Inhibitors ◽

Hiv 1

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A Computational Approach for the Prediction of HIV Resistance Based on Amino Acid and Nucleotide Descriptors

Molecules ◽

10.3390/molecules23112751 ◽

2018 ◽

Vol 23 (11) ◽

pp. 2751 ◽

Cited By ~ 7

Author(s):

Olga Tarasova ◽

Nadezhda Biziukova ◽

Dmitry Filimonov ◽

Vladimir Poroikov

Keyword(s):

Machine Learning ◽

Amino Acid ◽

Reverse Transcriptase ◽

Open Data ◽

Antiretroviral Drugs ◽

Amino Acid Sequences ◽

Machine Learning Techniques ◽

Structure Property ◽

Hiv Reverse Transcriptase ◽

Hiv Resistance

The high variability of the human immunodeficiency virus (HIV) is an important cause of HIV resistance to reverse transcriptase and protease inhibitors. There are many variants of HIV type 1 (HIV-1) that can be used to model sequence-resistance relationships. Machine learning methods are widely and successfully used in new drug discovery. An emerging body of data regarding the interactions of small drug-like molecules with their protein targets provides the possibility of building models on “structure-property” relationships and analyzing the performance of various machine-learning techniques. In our research, we analyze several different types of descriptors in order to predict the resistance of HIV reverse transcriptase and protease to the marketed antiretroviral drugs using the Random Forest approach. First, we represented amino acid sequences as a set of short peptide fragments, which included several amino acid residues. Second, we represented nucleotide sequences as a set of fragments, which included several nucleotides. We compared these two approaches using open data from the Stanford HIV Drug Resistance Database. We have determined the factors that modulate the performance of prediction: in particular, we observed that the prediction performance was more sensitive to certain drugs than a type of the descriptor used.

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