BIOCHEMICAL INTERPRETATION OF THE SYNERGISTIC EFFECT OF BIOLOGICALLY ACTIVE SUBSTANCES IN RELATION TO ANTIMICROBIAL AGENTS BY COMPUTER CHEMISTRY METHODS

Abstract

Due to the widespread resistance of microorganisms to existing drugs, the need for the search and development of new antibacterial forms is extremely high. The use of complexes of natural compounds, characterized by a wide variety, and antibiotics can make it possible to obtain antimicrobial agents of a diverse chemical structure and mechanism of action, and ensure the emergence of new effective medicines.There is a large amount of evidence that biologically active substances (BAS) of plant extracts can improve the work of some antimicrobials, their effect is: the ability to disrupt the structure of the bacterial plasma membrane, causing the formation of pores and leakage of internal contents; changes in electric charge and polarity; increased permeability, change in fluidity and other phenomena responsible for antibacterial activity. Synthesis of antibacterial compounds based on chemical modification of antimicrobial agents by natural complexes is one of the promising methods in the fight against antibiotic resistance. In this work, the synergistic effect of biologically active substances (BAS) of medicinal plants in relation to antimicrobial agents, ceftazidime and fosfomycin was investigated using computer chemistry methods. The variаnt of the effect of BAS on both the antibiotic and penicillin-binding proteins or beta-lactamases as part of a complex with an antibiotic was evaluated, as a result of which protein inhibition, its conformational rearrangement, or a decrease in the required minimum concentration of the antibiotic could occur. Ceftazidime and fosfomycin were chosen as the studied antibacterial drugs. The ligands were 8 molecules (BAS) with antimicrobial properties, such as: allicin, gallic acid, dihydroquercitin, rutin, atropine, tannin, thymol and saponin. 2 proteins from the RCSB Protein Data Bank database belonging to two different classes of enzymes were selected as binding models. At the first stage, the molecules of the studied substances were optimized in a small approximation HF/3-21+G and the thermodynamic problem was calculated. The second stage was a configuration search, after which molecular docking took place, binding of the studied substances (ligands) with protein molecules in the AutoDock 4.2.6 program. As a result, it was possible to obtain several binding sites, the probability of which would be the greatest.