Hierarchical Clustering and Target-Independent QSAR for Antileishmanial Oxazole and Oxadiazole Derivatives.

Int J Mol Sci

Laboratory of Medicinal and Computational Chemistry (LQMC), Center for Research and Innovation in Biodiversity and Drug Discovery (CIBFar), Institute of Physics of São Carlos, University of São Paulo (USP), Av. João Dagnone, n° 1100, São Carlos 13563-120, SP, Brazil.

Published: August 2022

Leishmaniasis is a neglected tropical disease that kills more than 20,000 people each year. The chemotherapy available for the treatment of the disease is limited, and novel approaches to discover novel drugs are urgently needed. Herein, 2D- and 4D-quantitative structure-activity relationship (QSAR) models were developed for a series of oxazole and oxadiazole derivatives that are active against , the causative agent of visceral leishmaniasis. A clustering strategy based on structural similarity was applied with molecular fingerprints to divide the complete set of compounds into two groups. Hierarchical clustering was followed by the development of 2D- ( = 0.90, pred = 0.82) and 4D-QSAR models ( = 0.80, pred = 0.64), which showed improved statistical robustness and predictive ability.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9408707PMC
http://dx.doi.org/10.3390/ijms23168898DOI Listing

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