Antimicrobial resistance is most often regarded as a severe threat to human health and a significant public health concern, with numerous and complicated factors leading to its incidence and spread. The ferulic acid derivatives were selected from the reported work by Khatkar et al., (2015). 2D QSAR identified the nonlinear dependence of biological activity with Log P. In 2D QSAR studies, molecular descriptors include topological parameters like valence third-order molecular connectivity index (3 χ V ), valence first-order molecular connectivity index (1 χ V ), Kier's third-order alpha shape index (kα3 ) and Balaban, lipophilic parameter like log P, electronic parameters like Vamp Lumo and total dipole, govern the antibacterial activity of ferulic acid derivatives. The molecular docking technique predicts binding affinity, drug-receptor interaction, and orientation of drug molecules to the target site, and ADME predicts drug likeliness. Molecular docking studies signify that compounds 18, 15, 21, 32, and 30 have the best docking score against protein transcriptional regulation (PDB ID: 5X14). Based on QSAR, molecular docking, molecular dynamics simulation, and ADME studies were employed and show an excellent ADME profile by the Lipinski rule of five. The study suggests that compounds 18, 15, 21, 32, and 30 could be employed as lead structures for advanced research in antimicrobial resistance.