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恶性疟原虫的计算机比较基因组学分析,用于鉴定推定的必需基因和治疗候选物。

In silico comparative genomics analysis of Plasmodium falciparum for the identification of putative essential genes and therapeutic candidates.

作者信息

Rout Subhashree, Warhurst David Charles, Suar Mrutyunjay, Mahapatra Rajani Kanta

机构信息

School of Biotechnology, KIIT University, Bhubaneswar 751024, Orissa, India.

Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.

出版信息

J Microbiol Methods. 2015 Feb;109:1-8. doi: 10.1016/j.mimet.2014.11.016. Epub 2014 Dec 5.

Abstract

A sequence of computational methods was used for predicting novel drug targets against drug resistant malaria parasite Plasmodium falciparum. Comparative genomics, orthologous protein analysis among same and other malaria parasites and protein-protein interaction study provide us new insights into determining the essential genes and novel therapeutic candidates. Among the predicted list of 21 essential proteins from unique pathways, 11 proteins were prioritized as anti-malarial drug targets. As a case study, we built homology models of two uncharacterized proteins using MODELLER v9.13 software from possible templates. Functional annotation of these proteins was done by the InterPro databases and from ProBiS server by comparison of predicted binding site residues. The model has been subjected to in silico docking study with screened potent lead compounds from the ZINC database by Dock Blaster software using AutoDock 4. Results from this study facilitate the selection of proteins and putative inhibitors for entry into drug design production pipelines.

摘要

一系列计算方法被用于预测针对耐药疟原虫恶性疟原虫的新型药物靶点。比较基因组学、同一及其他疟原虫之间的直系同源蛋白分析以及蛋白质-蛋白质相互作用研究为我们确定必需基因和新型治疗候选物提供了新的见解。在来自独特途径的预测的21种必需蛋白列表中,11种蛋白被优先列为抗疟药物靶点。作为一个案例研究,我们使用MODELLER v9.13软件从可能的模板构建了两种未表征蛋白的同源模型。这些蛋白的功能注释通过InterPro数据库以及通过比较预测的结合位点残基从ProBiS服务器完成。该模型已通过Dock Blaster软件使用AutoDock 4与从ZINC数据库筛选的有效先导化合物进行了计算机模拟对接研究。这项研究的结果有助于选择进入药物设计生产流程的蛋白质和推定抑制剂。

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