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Molecules 2018, 23(4), 956; https://doi.org/10.3390/molecules23040956

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

Institute of Biomedical Chemistry, 10 building 8, Pogodinskaya st., Moscow 119121, Russia
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Academic Editor: Athina Geronikaki
Received: 21 March 2018 / Revised: 16 April 2018 / Accepted: 17 April 2018 / Published: 19 April 2018
(This article belongs to the Special Issue Recent Trends on Enzymes Inhibitors and Activators in Drug Research)
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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. View Full-Text
Keywords: HIV; reverse transcriptase; resistance; computational prediction; amino acid sequences; nucleotide sequences; open data HIV; reverse transcriptase; resistance; computational prediction; amino acid sequences; nucleotide sequences; open data
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Tarasova, O.; Poroikov, V. HIV Resistance Prediction to Reverse Transcriptase Inhibitors: Focus on Open Data. Molecules 2018, 23, 956.

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