The In Silico Characterization of a Salicylic Acid Analogue Coding Gene Clusters in Selected Strains.

BACKGROUND

The microbial genome sequences provide solid in silico framework for interpretation of their drug-like chemical scaffolds biosynthetic potentials. strains are metabolically versatile and producing therapeutically important natural products.

OBJECTIVES

The key objective of the present study was to mine the publically available data of strains genomes for putative drug-like metabolites identification.

MATERIALS AND METHODS

We implemented the computational biology resources of AntiSMASH and BAGEL3 for the secondary metabolites prediction from strains genome sequences. The predicted secondary metabolites were evaluated using drug discovery chemoinformatics resources, like Drugbank database search and molecular docking inspection.

RESULTS

The analyses unveiled a wide array of chemical scaffolds biosynthesis in different strains. Subsequently, the drug-like potential evaluation of these metabolites identified few strains, PT14, A5O6, and FW300-N2E3 that the biosynthetic gene clusters for salicylic acid-like metabolite biosynthesis. The molecular docking inspection of this metabolite against human cyclooxygenase and aldo-keto reductase targets revealed its feasible inhibitory potentials like other salicylate compounds.

CONCLUSION

The computational biology and drug discovery analyses identified different gene clusters in genomes coding for salicylic acid-like chemotypes biosynthesis. These gene clusters may worthy to target through metabolic engineering for the massive production of salicylates-like chemical scaffolds from microbial resources.