title: Predicting anti-HIV-1 activity of 6-arylbenzonitriles: computational approach using superaugmented eccentric connectivity topochemical indices.
abstract: Highly discriminating adjacency-cum-distance based topochemical indices termed as superaugmented eccentric connectivity topochemical indices for quantitative structure-activity and structure-property relationships (QSAR/QSPR) have been conceptualized in the present study. These indices were found to exhibit high sensitivity towards the presence and relative position of heteroatom(s), exceptionally high discriminating power and negligible degeneracy for all possible structures of five vertices containing one heteroatom. Utility of these indices was investigated for development of models for prediction of anti-human immunodeficiency virus (HIV)-1 activity using a data set comprising 81 differently substituted 6-arylbenzonitriles. The values of the superaugmented eccentric connectivity topochemical indices of all the analogues comprising the data set were computed using an in-house computer program. The resultant data was analyzed and suitable models were developed after identification of the active ranges. Subsequently, a biological activity was assigned to each analogue using these models which was then compared with the reported anti-HIV-1 activity. The accuracy of prediction was found to be approximately 81% for all the three topochemical models. High sensitivity towards presence and relative position of heteroatom(s), exceptionally high discriminating power amalgamated with low degeneracy offer proposed topochemical indices vast potential for isomer discrimination, similarity/dissimilarity, drug design, quantitative structure-activity/structure-property relationships, lead optimization and combinatorial library design.
authors.affiliation: Faculty of Pharmaceutical Sciences, MD University, Rohtak 124 001, India.
authors.forename: Harish
authors.initials: H
authors.lastname: Dureja
authors.forename: Sunil
authors.initials: S
authors.lastname: Gupta
authors.forename: A K
authors.initials: AK
authors.lastname: Madan
mesh_terms: D019380:Anti-HIV Agents / Q000737:chemistry* / Q000494:pharmacology; D019295:Computational Biology; D015195:Drug Design; D008956:Models, Chemical; D008958:Models, Molecular; D009570:Nitriles / Q000737:chemistry / Q000494:pharmacology*; D013329:Structure-Activity Relationship
chemical_list: D019380:Anti-HIV Agents; D009570:Nitriles