The microorganism Staphylococcus aureus is a gram-positive spherical bacteria present in the healthy human body, commonly found in the nostrils and skin. It is responsible for a number of infections such as inflammation in the follicles, contribution to the onset of acne, inflammation in the meninges, cardiovascular inflammation, lung inflammation and others. Benzoic compounds are widely used as drug prototypes for various diseases such as cancer, degenerative diseases, microbiological infections and inflammation, and viral infections. This work aims to propose new benzoic in silico bioactives to combat Staphylococcus aureus. To do this, a series of benzoic acid derivatives were submitted to a prediction model of biological activity developed in the KNIME Analytics Platform 3.6, where the molecules that showed activity in the model were imported into OSIRIS DataWarrior 4.7.3 to predict the risks of cytotoxicity, the calculation of the Lipinski rule violations and the absorption rate (% ABS). For the molecules approved by the virtual screening already commented, the calculation of the energies of interaction between receptor and binder by molecular docking and the analysis of the interactions with the residues of amino acids were carried out, comparing with the interactions of the drugs used as control in this research. As conclusion of this work it was possible to propose bioactive molecules against S. aureus based on the obtained computational data.