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A systematic review: Application of in silico models for antimalarial drug discovery
Author(s) -
Anurak Cheoymang,
Na-Bangchang Kesara
Publication year - 2018
Publication title -
african journal of pharmacy and pharmacology
Language(s) - English
Resource type - Journals
ISSN - 1996-0816
DOI - 10.5897/ajpp2018.4904
Subject(s) - in silico , malaria , pharmacophore , plasmodium falciparum , computational biology , drug discovery , drug , adme , pharmacology , medicine , bioinformatics , biology , pathology , genetics , gene
Malaria remains the global public health problem due to the reemergence of drug resistance. There is an urgent need for development of new antimalarial candidates which are effective against resistant malaria parasite. This systematic review evaluates the published research studies that applied in silico modeling during the discovery process of antimalarial drugs. Literature searches were conducted using PubMed, EBSCO, EMBASE, and Web of Science to identify the relevant articles using the search terms “Malaria” “In silico model”, “Computer-based drug design”, “Antimalarial drug”, and “Drug discovery”. Only the articles published in English between 2008 and May 2015 were included in the analysis.  A total of 17 relevant articles met the search criteria. Most articles are studies specific to Plasmodium falciparum targets; 3 and 1 articles, respectively involve target for P. vivax and liver stage of Plasmodium. Both structure-based and ligand-based approaches were applied to obtain lead antimalarial candidates. Two articles also assessed absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Confirmation of activity of the candidate leads by in vitro and/or in vivo assays were reported in some studies. Homology modelling, molecular docking, 2D- or 3D-QSAR and pharmacophore modeling are commonly applied methods. One study used de novo synthesis for lead identification and one study applied phylogenetic analysis for target identification/validation.     Key words: Plasmodium, malaria, antimalarial drug, drug discovery, in silico modeling, computer-based drug design, systematic review.

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