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Dry selection and wet evaluation for the rational discovery of new anthelmintics

AutorMarrero-Ponce, Yovani; González Castañeda, Yeniel; Vivas-Reyes, R.; Vergara, F. M.; Arán, Vicente J. ; Castillo-Garit, J. A.; Pérez-Giménez, F.; Torrens, Francisco; Le-Thi-Thu, H; Pham-The, H.; Montenegro, Yolanda V.; Ibarra-Velarde, Froylán
Palabras claveLDA-based QSAR model
Non-stochastic and stochastic atom-based bilinear indices
Free and open source software
QuBiLs-MAS module
Computational creening
Lead generation
Anthelmintic activity
Fecha de publicación2017
EditorTaylor & Francis
CitaciónMolecular Physics 115: 2300-2313 (2017)
ResumenHelminths infections remain a major problem in medical and public health. In this report, atom-based 2D bilinear indices, a TOMOCOMD-CARDD (QuBiLs-MAS module) molecular descriptor family and linear discriminant analysis (LDA) were used to find models that differentiate among anthelmintic and non-anthelmintic compounds. Two classification models obtained by using non-stochastic and stochastic 2D bilinear indices, classified correctly 86.64% and 84.66%, respectively, in the training set. Equation 1(2) correctly classified 141(135) out of 165 [85.45%(81.82%)] compounds in external validation set. Another LDA models were performed in order to get the most likely mechanism of action of anthelmintics. The model shows an accuracy of 86.84% in the training set and 94.44% in the external prediction set. Finally, we carry out an experiment to predict the biological profile of our ‘in-house’ collections of indole, indazole, quinoxaline and cinnoline derivatives (∼200 compounds). Subsequently, we selected a group of nine of the theoretically most active structures. Then, these chemicals were tested in an invitro assay and one good candidate (VA5-5c) as fasciolicide compound (100% of reduction at concentrations of 50 and 10 mg/L) was discovered.
Identificadoresdoi: 10.1080/00268976.2017.1296194
issn: 0026-8976
e-issn: 1362-3028
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