Marvels of Artificial and Computational Intelligence in Life Sciences

Functional Prediction of Anti-methanogenic Targets from Methanobrevibacter Ruminantium M1 Operome

Author(s): M. Bharathi, S. Saranya, Senthil Kumar N. and P. Chellapandi * .

Pp: 228-243 (16)

DOI: 10.2174/9789815136807123010019

* (Excluding Mailing and Handling)

Abstract

Methanobrevibacter ruminantium M1 is one of the abundant methanogenic archaea found in ruminants, which is influential in livestock production by enteric methane emission. Several methane mitigation strategies have been employed to curtail enteric methane emissions, most of which have not been successful to date. Hence, it is imperative to discover new targets for the development of organism-specific vaccines and inhibitors of methanogenesis. In this study, we predicted the functions and characterized chemogenomic and vaccine proteins from their operomes using a combined bioinformatics approach. A precise function of 257 hypothetical proteins was assigned based on their sequence-structure-function relationships, as evidenced by the literature. We identified 12 virulence genes and 18 vaccinogenic proteins as reliable antigenic determinants. The predicted virulence proteins were found to promote the survival of this organism in the intestine of ruminant animals. The toll-like receptor, nudix hydrolase, pseudo murein-binding repeat protein, and phosphonoacetate hydrolase identified in this organism have shown more immunogenic and vaccinogenic characteristics. Therefore, the new virulence factors and vaccine candidates identified in this study would provide a quest for new anti-methanogenic drugs to mitigate the methane emitted in ruminant animals. 


Keywords: Hypothetical proteins, Immunoinformatics, Methanobrevibacter, Methanogenesis, Protein function, Vaccine.

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