title: Classification of active and weakly active ST inhibitors of HIV-1 integrase using a support vector machine.
abstract: Using a support vector machine (SVM), two computational models were built to predict whether a compound is an active or weakly active strand transfer (ST) inhibitor based on a dataset of 1257 ST inhibitors of HIV-1 integrase. The model built with MACCS fingerprints gave a prediction accuracy of 91.82% and a Matthews Correlation Coeffiient (MCC) of 0.73 on test set, and the model built with 40 MOE descriptors gave a prediction accuracy of 93.64% and an MCC of 0.79 on test set. Some molecular properties such as electrostatic properties, van der Waals surface area, hydrogen bond properties and the number of fluorine atoms are important factors influencing the interactions between the inhibitor and the integrase. Some scaffolds like β-diketo acid and its derivatives, naphthyridine carboxamide or the isosteric of it and pyrimidionones may play crucial rule to the activity of the HIV-1 integrase inhibitors.
authors.affiliation: State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, P.O. Box 53, Beijing University of Chemical Technology, 15 BeiSanHuan East Road, Beijing 100029, PR China. yanax@mail.buct.edu.cn
authors.forename: Aixia
authors.initials: A
authors.lastname: Yan
authors.forename: Shouyi
authors.initials: S
authors.lastname: Xuan
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Hu
mesh_terms: D020650:Combinatorial Chemistry Techniques; D062126:Databases, Chemical; D019427:HIV Integrase / Q000378:metabolism*; D019428:HIV Integrase Inhibitors / Q000138:chemical synthesis / Q000737:chemistry / Q000145:classification* / Q000494:pharmacology*; D015497:HIV-1 / Q000187:drug effects / Q000201:enzymology; D015394:Molecular Structure; D060388:Support Vector Machine
chemical_list: D019428:HIV Integrase Inhibitors; D019427:HIV Integrase