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通过全面的计算分析探索念珠菌属物种的可成药性蛋白质组。

Exploring the druggable proteome of Candida species through comprehensive computational analysis.

机构信息

Biomedical Informatics Centre, ICMR-National Institute for Research in Reproductive Health, Mumbai 400012, Maharashtra, India.

Department of Bioinformatics, Guru Nanak Khalsa College, Nathalal Parekh Marg, Matunga, Mumbai 400019, Maharashtra, India.

出版信息

Genomics. 2021 Mar;113(2):728-739. doi: 10.1016/j.ygeno.2020.12.040. Epub 2021 Jan 20.

Abstract

Candida albicans and non-albicans Candida spp. are major cause of systemic mycoses. Antifungal drugs such as azoles and polyenes are not efficient to successfully eradicate Candida infection owing to their fungistatic nature or low bioavailability. Here, we have adopted a comprehensive computational workflow for identification, prioritization and validation of targets from proteomes of Candida albicans and Candida tropicalis. The protocol involves identification of essential drug-target candidates using subtractive genomics, protein-protein interaction network properties and systems biology based methods. The essentiality of the novel metabolic and non-metabolic targets was established by performing in silico gene knockouts, under aerobic as well as anaerobic conditions, and in vitro drug inhibition assays respectively. Deletion of twelve genes that are involved in amino acid, secondary metabolite, and carbon metabolism showed zero growth in metabolic model under simulated conditions. The algorithm, used in this study, can be downloaded from http://pbit.bicnirrh.res.in/offline.php and executed locally.

摘要

白色念珠菌和非白色念珠菌属念珠菌是全身性真菌病的主要病因。由于唑类和多烯类等抗真菌药物具有抑菌作用或生物利用度低,因此无法有效地成功消除念珠菌感染。在这里,我们采用了一种全面的计算工作流程,用于鉴定、优先排序和验证白色念珠菌和热带念珠菌蛋白质组中的靶标。该方案涉及使用消减基因组学、蛋白质-蛋白质相互作用网络特性和基于系统生物学的方法来识别必需的药物靶标候选物。通过在有氧和无氧条件下进行计算机基因敲除以及体外药物抑制试验,分别确定了新型代谢和非代谢靶标的必要性。在模拟条件下,氨基酸、次生代谢物和碳代谢涉及的 12 个基因的缺失导致代谢模型中无生长。本研究中使用的算法可从 http://pbit.bicnirrh.res.in/offline.php 下载并在本地执行。

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