title: A support vector machine classification model for benzo[c]phenathridine analogues with toposiomerase-I inhibitory activity.
abstract: Benzo[c]phenanthridine (BCP) derivatives were identified as topoisomerase I (TOP-I) targeting agents with pronounced antitumor activity. In this study, a support vector machine model was performed on a series of 73 analogues to classify BCP derivatives according to TOP-I inhibitory activity. The best SVM model with total accuracy of 93% for training set was achieved using a set of 7 descriptors identified from a large set via a random forest algorithm. Overall accuracy of up to 87% and a Matthews coefficient correlation (MCC) of 0.71 were obtained after this SVM classifier was validated internally by a test set of 15 compounds. For two external test sets, 89% and 80% BCP compounds, respectively, were correctly predicted. The results indicated that our SVM model could be used as the filter for designing new BCP compounds with higher TOP-I inhibitory activity.
authors.affiliation: Department of Medicinal Chemistry, School of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang St., District 1, Ho Chi Minh City, Vietnam. thaikhacminh@uphcm.edu.vn
authors.forename: Khac-Minh
authors.initials: KM
authors.lastname: Thai
authors.forename: Thuy-Quyen
authors.initials: TQ
authors.lastname: Nguyen
authors.forename: Trieu-Du
authors.initials: TD
authors.lastname: Ngo
authors.forename: Thanh-Dao
authors.initials: TD
authors.lastname: Tran
authors.forename: Thi-Ngoc-Phuong
authors.initials: TN
authors.lastname: Huynh
mesh_terms: D008962:Models, Theoretical; D010616:Phenanthrenes / Q000737:chemistry* / Q000494:pharmacology*; D015203:Reproducibility of Results; D060388:Support Vector Machine; D059004:Topoisomerase I Inhibitors / Q000737:chemistry* / Q000494:pharmacology
chemical_list: D010616:Phenanthrenes; D059004:Topoisomerase I Inhibitors