In Silico Screening and Evolution of Promising Novel Anti-Virulents Against Salmonella ATPase
DOI:
https://doi.org/10.47611/jsrhs.v13i1.6252Keywords:
computational chemistry, molecular screening, docking, Salmonella, AutoGrow4Abstract
Current treatments for bacterial infections are under threat by the growth of antibiotic resistance in many different pathogens. Of these pathogens, Salmonella is a particularly widespread microbe, infecting over a million people annually as the leading source of food-borne diseases. One potential solution for antibiotic-resistant Salmonella is virulence inhibition of the bacteria’s T3SS injection system, which has been shown to destroy Salmonella’s proliferative abilities. Here, we identify fourteen compounds, primarily novel ligands, that exhibit high in-vitro potential as Salmonella inhibitors by attacking the ATPase InvC protein vital for T3SS injection–an enzyme that has not been previously evaluated for small-molecule inhibition. We also present a statistical analysis of AutoGrow4, a virtual structure-based molecular design tool that evolves ligands to better suit a target protein using Autodock Vina binding affinity calculations. Together, these create an entirely open-source workflow towards computational identification and evaluation of novel chemical treatments.
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