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Review
. 2018 Apr 19;23(4):956.
doi: 10.3390/molecules23040956.

HIV Resistance Prediction to Reverse Transcriptase Inhibitors: Focus on Open Data

Affiliations
Review

HIV Resistance Prediction to Reverse Transcriptase Inhibitors: Focus on Open Data

Olga Tarasova et al. Molecules. .

Abstract

Research and development of new antiretroviral agents are in great demand due to issues with safety and efficacy of the antiretroviral drugs. HIV reverse transcriptase (RT) is an important target for HIV treatment. RT inhibitors targeting early stages of the virus-host interaction are of great interest for researchers. There are a lot of clinical and biochemical data on relationships between the occurring of the single point mutations and their combinations in the pol gene of HIV and resistance of the particular variants of HIV to nucleoside and non-nucleoside reverse transcriptase inhibitors. The experimental data stored in the databases of HIV sequences can be used for development of methods that are able to predict HIV resistance based on amino acid or nucleotide sequences. The data on HIV sequences resistance can be further used for (1) development of new antiretroviral agents with high potential for HIV inhibition and elimination and (2) optimization of antiretroviral therapy. In our communication, we focus on the data on the RT sequences and HIV resistance, which are available on the Internet. The experimental methods, which are applied to produce the data on HIV-1 resistance, the known data on their concordance, are also discussed.

Keywords: HIV; amino acid sequences; computational prediction; nucleotide sequences; open data; resistance; reverse transcriptase.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Distribution of the (a) HIV-1 nucleotide sequences depending on the sequence length (NCBI Nucleotide (GenBank) database); (b) HIV-1 amino acid sequences depending on the sequence length (NCBI Protein database).
Figure 2
Figure 2
The number of mixtures occurring in the major drug resistance positions in the initial data sets obtained using the Phenosense assay: (a) for main NRTI-associated mutations; (b) for main NNRTI-associated mutations.
Figure 3
Figure 3
The number of mixtures occurring in the major drug resistance positions in the initial data sets obtained using the Antivirogram assay: (a) for main NRTI-associated mutations; (b) for main NNRTI-associated mutations.
Figure 4
Figure 4
Distribution of amino acid residues occurring in the major drug resistance positions for the data set containing the drug susceptibility obtained using PhenoSense (Virologic™) assay (a) for NRTIs; (b) for NNRTIs.
Figure 5
Figure 5
Distribution of amino acid residues occurring in the major drug resistance positions for the data set containing the drug susceptibility obtained using Antivirogram (Virco™).assay (a) for NRTIs; (b) for NNRTIs.

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