In Silico Studies Most Employed in the Discovery of New Antimicrobial Agents

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.

An Overview of Biological and Computational Methods for Designing Mechanism-Informed Anti-biofilm Agents

“…Of more recent interest are machine learning and QSAR methods, a suite of techniques enabling efficient screening and selection of agents in specific contexts, such as peptides targeting E. coli biofilms. These modeling frameworks have been reviewed previously (Tamay-Cach et al, 2016;Cardoso et al, 2019), largely by describing their general use in discovering antimicrobials. Furthermore, these two methods may be complementary, since virtual screens may generate compounds that can then be used to train machine learning models.…”

Specific inhibitors of urokinase plasminogen activator for treatment of cancers; In silico approach

“…Thus, for successful targeted anticancer therapy, it is imperative to find specific uPA inhibitors, and at the same time protect normal function of other serine proteases of analogous structures, such as tPA. As the number of protein structures determined experimentally by X-ray crystallography and nuclear magnetic resonance spectroscopy is growing, computational methods are ever more used as a tool in targeted drug discovery (28)(29)(30)(31)(32). Among them, AutoDock Vina molecular docking (MD) methodology that predicts binding of small molecules to a target protein using a Monte Carlo sampling technique and scoring function, is gaining popularity due to its considerable improvement in prediction accuracy and docking time (33)(34)(35)(36)(37)(38).…”

The study of the prooxidant-antioxidant equilibrium in the kidney tissue and blood on the background of ceruloplasmin administration under the conditions of acute kidney injury

“…One of the promising areas of AKI treatment are the antioxidants that inhibit free radical processes and prevent the destruction of cell membranes within the pathological processes. The pathogenesis of AKI is related with the peroxidation of lipids [8,11,12,14], leading to imbalance among prooxidants and antioxidants, hence to the development of oxidative stress.…”

“…The formation of reactive oxygen species (ROS) in the organism can change the structure of DNA, leading to modification of proteins and lipids, activation of stress-induced transcription factors and production of pro-inflammatory and anti-inflammatory cytokines [8,11]. The antioxidant defense mechanism of the organism encompasses enzymatic and nonenzymatic antioxidant, that can deactivate the free radicals [1][2][3][4].…”