Predictive Global Models of Cruzain Inhibitors with Large Chemical Coverage
José Guadalupe Rosas-Jiménez, Marco A. García‐Revilla, Abraham Madariaga‐Mazón, Karina Martínez‐Mayorga
Abstract
coefficients of 0.725 and 0.766. The applicability domain is quantitatively defined, according to QSAR good practices, using the leverage and similarity methods. The models described in this work are readily available in a Python script for the discovery of novel cruzain inhibitors.
Topics & Concepts
Quantitative structure–activity relationshipLeverage (statistics)BenznidazoleCysteine proteaseComputational biologyComputer scienceMachine learningBiologyTrypanosoma cruziProteaseEnzymeParasite hostingWorld Wide WebBiochemistryTrypanosoma species research and implicationsSynthesis and Biological EvaluationResearch on Leishmaniasis Studies