Predictive classification models and targets identification for betulin derivatives as Leishmania donovani inhibitors

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Zhang , Y , Xhaard , H & Ghemtio , L 2018 , ' Predictive classification models and targets identification for betulin derivatives as Leishmania donovani inhibitors ' , Journal of Cheminformatics , vol. 10 , 40 . https://doi.org/10.1186/s13321-018-0291-x

Title: Predictive classification models and targets identification for betulin derivatives as Leishmania donovani inhibitors
Author: Zhang, Yuezhou; Xhaard, Henri; Ghemtio, Leo
Contributor: University of Helsinki, Faculty of Pharmacy
University of Helsinki, Faculty of Pharmacy
University of Helsinki, Faculty of Pharmacy
Date: 2018-08-17
Language: eng
Number of pages: 16
Belongs to series: Journal of Cheminformatics
ISSN: 1758-2946
URI: http://hdl.handle.net/10138/241219
Abstract: Betulin derivatives have been proven effective in vitro against Leishmania donovani amastigotes, which cause visceral leishmaniasis. Identifying the molecular targets and molecular mechanisms underlying their action is a currently an unmet challenge. In the present study, we tackle this problem using computational methods to establish properties essential for activity as well as to screen betulin derivatives against potential targets. Recursive partitioning classification methods were explored to develop predictive models for 58 diverse betulin derivatives inhibitors of L. donovani amastigotes. The established models were validated on a testing set, showing excellent performance. Molecular fingerprints FCFP_6 and ALogP were extracted as the physicochemical properties most extensively involved in separating inhibitors from non-inhibitors. The potential targets of betulin derivatives inhibitors were predicted by in silico target fishing using structure-based pharmacophore searching and compound-pharmacophore-targetpathway network analysis, first on PDB and then among L. donovani homologs using a PSI-BLAST search. The essential identified proteins are all related to protein kinase family. Previous research already suggested members of the cyclin-dependent kinase family and MAP kinases as Leishmania potential drug targets. The PSI-BLAST search suggests two L. donovani proteins to be especially attractive as putative betulin target, heat shock protein 83 and membrane transporter D1.
Subject: Leishmania donovani inhibitors
Betulin derivatives
Predictive modeling
Classification models
Recursive partitioning
In silico target prediction
Structure-based pharmacophore
Network analysis
ACID-DERIVATIVES
IN-VITRO
ANTILEISHMANIAL ACTIVITY
VISCERAL LEISHMANIASIS
ANTIMALARIAL ACTIVITY
ANTIVIRAL ACTIVITY
APOPTOSIS
DISCOVERY
VIVO
MOLECULES
116 Chemical sciences
317 Pharmacy
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