{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T01:48:26Z","timestamp":1768096106124,"version":"3.49.0"},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"16","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2003,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Many experts worldwide have highlighted the potential of RNA molecules as drug targets for the chemotherapeutic treatment of a range of diseases. In particular, the molecular pockets of RNA in the HIV-1 packaging region have been postulated as promising sites for antiviral action. The discovery of simpler methods to accurately represent drug\u2013RNA interactions could therefore become an interesting and rapid way to generate models that are complementary to docking-based systems.<\/jats:p>\n               <jats:p>Results: The entropies of a vibrational Markov chain have been introduced here as physically meaningful descriptors for the local drug\u2013nucleic acid complexes. A study of the interaction of the antibiotic Paromomycin with the packaging region of the RNA present in type-1 HIV has been carried out as an illustrative example of this approach. A linear discriminant function gave rise to excellent discrimination among 80.13% of interacting\/non-interacting sites. More specifically, the model classified 36\/45 nucleotides (80.0%) that interacted with paromomycin and, in addition, 85\/106 (80.2%) footprinted (non-interacting) sites from the RNA viral sequence were recognized. The model showed a high Matthews\u2019 regression coefficient (C = 0.64). The Jackknife method was also used to assess the stability and predictability of the model by leaving out adenines, C, G, or U. Matthews\u2019 coefficients and overall accuracies for these approaches were between 0.55 and 0.68 and 75.8 and 82.7, respectively. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the aforementioned antibiotic (R2 = 0.83,Q2 = 0.825). These kinds of models may play an important role either in the discovery of new anti-HIV compounds or in the elucidation of their mode of action.<\/jats:p>\n               <jats:p>Availability: On request from the corresponding author (humbertogd@cbq.uclv.edu.cu or humbertogd@navegalia.com)<\/jats:p>","DOI":"10.1093\/bioinformatics\/btg285","type":"journal-article","created":{"date-parts":[[2003,11,2]],"date-time":"2003-11-02T18:17:59Z","timestamp":1067797079000},"page":"2079-2087","source":"Crossref","is-referenced-by-count":55,"title":["Markovian negentropies in bioinformatics. 1. A picture of footprints after the interaction of the HIV-1 \u03a8-RNA packaging region with drugs"],"prefix":"10.1093","volume":"19","author":[{"given":"Humberto Gonz\u00e1lez","family":"D\u00edaz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronal","family":"Ramos de Armas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Reinaldo","family":"Molina","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2003,11,1]]},"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/19\/16\/2079\/48904720\/bioinformatics_19_16_2079.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/19\/16\/2079\/48904720\/bioinformatics_19_16_2079.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T17:58:04Z","timestamp":1674669484000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/19\/16\/2079\/242417"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,11,1]]},"references-count":0,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2003,11,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btg285","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2003,11,1]]},"published":{"date-parts":[[2003,11,1]]}}}