Abstract

The present review summarizes the methods most used in drug search and design, which may help to keep pace with the growing antibiotic resistance among pathogens. The rate of reduction in the effectiveness of many antimicrobial medications, caused by this resistance, is faster than new drug development, thereby creating a worldwide public health threat. Among the scientific community, the urgency of finding new drugs is peaking interest in the use of in silico studies to explore the interaction of compounds with target receptors. With this approach, small molecules (designed or retrieved from data bases) are tested with computer-aided molecular simulation to explore their efficacy. That is, ligand-protein complexes are constructed and evaluated via virtual screening (VS), molecular dynamics (MD), and docking simulations with the data from the physical, chemical and pharmacological properties of such molecules. Additionally, the application of quantitative structure-activity relationship (QSAR), multi-target quantitative structure-activity relationship (mt- QSAR), and multi-tasking quantitative structure-biological effect (mtk-QSBER) can be enhanced by principal component analysis and systematic workflows. These types of studies aid in selecting a group of promising molecules with high potency and selectivity as well as low toxicity, thus making in vitro and in vivo (animal model) testing more efficient. Since knowledge of the receptor topography and receptor-ligand interactions has yielded promising compounds and effective drugs, there is now no doubt that the use of in silico tools can lead to more rapid validation of new potential drugs for preclinical studies and clinical trials.

Keywords: Antimicrobial agents, Docking simulation, Molecular dynamics simulations, mt-QSAR, mtk-QSBER, QSAR, Virtual screening.