Computational Discovery of Antimicrobial Enzymes from Environmental Microbiota

In contemporary society, the escalation of antibiotic-resistant microorganisms not onlyengenders key industries but also poses significant challenges across various parts, including healthcare,agriculture, and poultry [۱]–[۳] To address this issue, it is imperative to identify novel antimicrobialagents that can overcome resistance. One of the potential candidates for finding these agents isbiomolecules in harsh microbiome environments, where microbial societies vie for the dominance andacquisition of potent antimicrobial attributes. Many enzymes encoded by the genomes ofmicroorganisms have been shown to possess antimicrobial properties. In this study, we investigated themetagenome of the tannery waste environment using computational methods and identifiedantimicrobial enzymes in this environment. To this end, metagenomic samples were analyzed usingapproaches including assembly, gene prediction, enzyme prediction, and ۳D structure prediction todiscover new antibiotics that are effective in antibiotic resistance. All contigs were analyzed using theMetarenz [۴] software to predict the presence of enzybiotics. Metarenz is a tool for identifying targetenzymes in assembled contigs. ۳D structures of some candidates were predicted using the Alphafold۲[۵] and TMalighn [۶] tools. The resulting metagenomic sequences were further investigated using theNCBI CDD database.

کلیدواژه ها:

Antimicrobial ، Metagenomics ، Microbiota ، Computational ، Enzymes Discovery