Identification of Potential Candidates with Antimicrobial Activity Against Antibiotic-Resistant Staphylococcus aureus Strains: A Hierarchical Bioinformatics Approach.

Antibiotic resistance among several bacteria is a warning sign that reinforces the need for research to identify new compounds that are effective against resistant strains. In this sense, bioinformatics stands out as an excellent tool for identifying drug candidates by using computational methodologies to detect compounds with potential biological activity. Two pivot compounds (QNZ and 0Y5) with biological activity against Staphylococcus aureus were selected. A virtual screening was performed in the MolPort database with a Tanimoto index of 0.5, resulting in 20,000 compounds, 10,000 compounds for each template. Then, methodologies were applied to calculate pharmacokinetic and toxicological parameters using Discovery Studio software; molecular docking via DockThor; lethal dose via ProTOX; lipophilicity, solubility, and Lipinski parameters via SwissADME; in silico prediction of bacterial activity via Way2Drug; theoretical synthetic accessibility via SwissADME and AMBIT-SA; and, finally, molecular dynamics simulations via AMBER 18. After the entire methodological process, 10 compounds were identified with potential results according to the criteria adopted in this study and with possible antimicrobial activity against resistant bacterial strains of S. aureus. Our theoretical findings suggest 10 potential candidates with possible antimicrobial activity against S. aureus and other genera and species of bacteria as these compounds presented excellent results using the proposed methodology. Certainly, more in vitro and in vivo study steps are necessary.