Mukherjee S, Kundu I, Askari M, Barai RS, Venkatesh KV, Idicula-Thomas S. Exploring the druggable proteome of Candida species through comprehensive computational analysis.
Genomics 2021;
113:728-739. [PMID:
33484798 DOI:
10.1016/j.ygeno.2020.12.040]
[Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 11/30/2020] [Accepted: 12/14/2020] [Indexed: 11/30/2022]
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.
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