Ligand-based virtual screening and in silico design of new antimalarial compounds using nonstochastic and stochastic total and atom-type quadratic maps

Yovani Marrero-Ponce, Maité Iyarreta-Veitía, Alina Montero-Torres, Carlos Romero-Zaldivar, Carlos A. Brandt, Priscilla E. Ávila, Karin Kirchgatter, Yanetsy Machado

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86 Citas (Scopus)

Resumen

A simple linear discriminant-based quantitative structure-activity relationship (QSAR) models were developed for the classification and prediction of antimalarial activity using some of the topological molecular computer design-computer aided 'rational' drug design (TOMOCOMD-CARDD) fingerprints. A database of 1562 organic chemicals having great structural variability, 597 of them antimalarial agents and 965 compounds having other clinical uses, was analyzed. This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. It was concluded that the approach described seems to be a promising QSAR tool for the molecular discovery of classes of antimalarial drugs.

Idioma originalInglés
Páginas (desde-hasta)1082-1100
Número de páginas19
PublicaciónJournal of Chemical Information and Modeling
Volumen45
N.º4
DOI
EstadoPublicada - 2005
Publicado de forma externa

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