title: Computational models on quantitative prediction of bioactivity of HIV-1 integrase 3' processing inhibitors.
abstract: In this study, four computational quantitative structure-activity relationship (QSAR) models were built to predict the bioactivity of 3' processing (3'P) inhibitors of HIV-1 integrase. Some 453 inhibitors whose bioactivity values were detected by the radiolabelling method were collected. The molecular structures were represented with MOE descriptors. In total, 21 descriptors were selected for modelling. All inhibitors were divided into a training set and a test set with two methods: (1) by a Kohonen's self-organizing map (SOM); (2) by a random selection. For every training set and test set, a multilinear regression (MLR) analysis and a support vector machine (SVM) were used to establish models, respectively. For the training/test set divided by SOM, the correlation coefficients (r) were over 0.84, and for the training/test set split randomly, the r values were over 0.86. Some molecular properties such as hydrogen bond donor capacity, atomic partial charge properties, molecular refractivity, the number of aromatic bonds and molecular surface area, volume and shape properties played important roles for inhibiting 3' processing step of HIV-1 integrase.
authors.affiliation: a State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering , Beijing University of Chemical Technology , Beijing , China.
authors.forename: Y
authors.initials: Y
authors.lastname: Kong
authors.forename: S
authors.initials: S
authors.lastname: Xuan
authors.forename: A
authors.initials: A
authors.lastname: Yan
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D019427:HIV Integrase / Q000737:chemistry* / Q000378:metabolism; D019428:HIV Integrase Inhibitors / Q000737:chemistry* / Q000378:metabolism; D015497:HIV-1 / Q000201:enzymology*; D006801:Humans; D008956:Models, Chemical; D015394:Molecular Structure; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D060388:Support Vector Machine
chemical_list: D019428:HIV Integrase Inhibitors; D019427:HIV Integrase; C514801:p31 integrase protein, Human immunodeficiency virus 1
keywords: HIV-1 integrase 3’P inhibitors (HIV-1 IN3’PIs); mutilinear regression (MLR); quantitative structure–activity relationship (QSAR); self-organizing map (SOM); support vector machine (SVM)