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Identification of Novel Drug Targets in Pathogenic Aspergillus Fumigatus: An in Silico Approach

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Data Science and Analytics (REDSET 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1229))

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Abstract

Invasive aspergillosis due to fungus Aspergillus fumigatus is considered a major human disease infecting immunosuppressed patients. Screening of novel drug targets for this opportunistic pathogen is a need of the hour due to the constraints of antifungal remedies, reactions, drug resistance & toxicities, expense and drug-drug interactions. In order to overcome these limitations, novel antifungal drug targets are needed. Thus, to find putative drug targets, we explored combination of subtractive and comparative genomics approach in the current work Whole proteome of A. fumigatus is screened for homology analysis via target identification tool ‘TiDv2’. TiDv2 classifies proposed drug targets as new and virulent in less time and at low cost. Genes from homology analysis are compared with humans and gut flora to achieve non homology with them to attain broad spectrum drug target. Thereafter, druggability and virulence factor analysis is performed. The resultant dataset is prioritized for metabolic pathway analysis. In addition, functional annotation and subcellular localization is accomplished. The results reveal that 5 genes namely His6, FasA, PabaA, FtmA and erg6 might work as promising wide-spectrum drug targets for A. fumigatus. Hence, these genes may improve current curative failures in the medication of invasive aspergillosis. However, these possible drug targets should be verified to confirm before target based lead discovery.

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Correspondence to Chandra Shekhar Rai .

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Gupta, R., Rai, C.S. (2020). Identification of Novel Drug Targets in Pathogenic Aspergillus Fumigatus: An in Silico Approach. In: Batra, U., Roy, N., Panda, B. (eds) Data Science and Analytics. REDSET 2019. Communications in Computer and Information Science, vol 1229. Springer, Singapore. https://doi.org/10.1007/978-981-15-5827-6_13

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  • DOI: https://doi.org/10.1007/978-981-15-5827-6_13

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  • Print ISBN: 978-981-15-5826-9

  • Online ISBN: 978-981-15-5827-6

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