Pan-genomics, drug candidate mining and ADMET profiling of natural product inhibitors screened against Yersinia pseudotuberculosis

Abstract

Yersinia pseudotuberculosis belongs to the family Enterobacteriaceae and is responsible for scarlatinoid fever, food poisoning, post-infectious complications like erythema nodosum/reactive arthritis as well as pseudoappendicitis in children. Genome sequences of the 23 whole genomes from NCBI were utilized for conducting the pan-genomic analysis. Essential proteins from the core region were obtained and drug targets were identified using a hierarchal in silico approach. Among these, multidrug resistance protein sub-unit mdtC was chosen for further analysis. This protein unit confers resistance to antibiotics upon forming a tripartite complex with units A and B in Escherichia coli. Details of the function have not yet been elucidated experimentally in Yersinia spp. Computational structure modeling and validation were followed by screening against phytochemical libraries of traditional Indian (Ayurveda), North African, and traditional Chinese flora using Molecular Operating Environment software version 2019.0102. ADMET profiling and descriptor study of best docked compounds was studied. Since phytotherapy is the best resort to antibiotic resistance so these compounds should be tested experimentally to further validate the results. The obtained information could aid wet-lab scientists to work on the scaffold of screened drug-like compounds from natural resources. This could be useful in our quest for antibiotic-resistant therapy against Y. pseudotuberculosis.