{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T11:52:36Z","timestamp":1773661956661,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,23]],"date-time":"2020-01-23T00:00:00Z","timestamp":1579737600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006769","name":"Russian Science Foundation","doi-asserted-by":"publisher","award":["19-75-10097"],"award-info":[{"award-number":["19-75-10097"]}],"id":[{"id":"10.13039\/501100006769","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Human Immunodeficiency Virus Type 1 (HIV-1) infection is associated with high mortality if no therapy is provided. Currently, the treatment of an HIV-1 positive patient requires that several drugs should be taken simultaneously. The resistance of the virus to an antiretroviral drug may lead to treatment failure. Our approach focuses on predicting the exposure of a particular viral variant to an antiretroviral drug or drug combination. It also aims at the prediction of drug treatment success or failure. We utilized nucleotide sequences of HIV-1 encoding protease and reverse transcriptase to perform such types of prediction. The PASS (Prediction of Activity Spectra for Substances) algorithm based on the naive Bayesian classifier was used to make a prediction. We calculated the probability of whether a sequence belonged (P1) or did not belong (P0) to the class associated with exposure of the viral sequence to the set of drugs that can be associated with resistance to the set of drugs. The accuracy calculated as the average Area Under the ROC (Receiver Operating Characteristic) Curve (AUC\/ROC) for classifying exposure of the sequence to the HIV-1 protease inhibitors was 0.81 (\u00b10.07), and for HIV-1 reverse transcriptase, it was 0.83 (\u00b10.07). To predict cases of treatment effectiveness or failure, we used P1 and P0 values, obtained in PASS, along with the binary vector constructed based on short nucleotide descriptors and the applied random forest classifier. Average AUC\/ROC prediction accuracy for the prediction of treatment effectiveness or failure for the combinations of HIV-1 protease inhibitors was 0.82 (\u00b10.06) and of HIV-1 reverse transcriptase was 0.76 (\u00b10.09).<\/jats:p>","DOI":"10.3390\/ijms21030748","type":"journal-article","created":{"date-parts":[[2020,1,23]],"date-time":"2020-01-23T10:36:02Z","timestamp":1579775762000},"page":"748","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["A Computational Approach for the Prediction of Treatment History and the Effectiveness or Failure of Antiretroviral Therapy"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3723-7832","authenticated-orcid":false,"given":"Olga","family":"Tarasova","sequence":"first","affiliation":[{"name":"Department of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nadezhda","family":"Biziukova","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7896-2379","authenticated-orcid":false,"given":"Dmitry","family":"Kireev","sequence":"additional","affiliation":[{"name":"Central Research Institute of Epidemiology, 111123 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1757-8004","authenticated-orcid":false,"given":"Alexey","family":"Lagunin","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia"},{"name":"Department of Bioinformatics, Pirogov Russian National Research Medical University, 117997 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sergey","family":"Ivanov","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia"},{"name":"Department of Bioinformatics, Pirogov Russian National Research Medical University, 117997 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dmitry","family":"Filimonov","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7937-2621","authenticated-orcid":false,"given":"Vladimir","family":"Poroikov","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Biomedical Chemistry, 119121 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Li, S., Gu, Y., and Xia, N. 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