LysR-type transcription factor RovM is an important target of Yersinia pseudotuberculosis drug discovery and the discovery of antibacterial is considered one of the greatest medical achievements of all time. In this research work, a combination of three docking tools with different algorithms was applied in Salicylidene acylhydrazides derivatives intended toward gram-negative bacterium Yersinia pseudotuberculosis to evaluate their binding interactions.
The analysis of the molecular docking results obtained from the 3-docking software system succeeded in screening twelve fascinating compounds with higher restrictive concentrations having a decent affinity to LysR-type transcription factor RovM macromolecule. Then the Lipinski’s and Veber’s rule properties were calculated to spot the drug-likeness properties of the investigated candidate compounds. To anticipate the toxicity of the predicted candidate chemicals, in-silico toxicity tests were conducted. Furthermore, golden triangle and drug scores were performed, the investigated compounds which fall within the golden triangle indicate that these compounds would not have clearance problems. 5 of the 12 hits drugs pass the golden triangle screening step. These selected drugs undergo a drug score test which only compound 17 passed. To validate the stability, 1 ns molecular dynamic simulations were done on the highest-ranking drug score compound 17 / 3onm complexes. These findings point to interesting avenues for the development of new compounds that are more effective against Yersinia pseudotuberculosis.
Yersinia pseudotuberculosis Salicylidene acylhydrazides Docking ADMET golden triangle and MD simulations.
Primary Language | English |
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Subjects | Chemical Engineering |
Journal Section | Research Article |
Authors | |
Publication Date | June 15, 2022 |
Submission Date | October 2, 2021 |
Published in Issue | Year 2022 |
Journal Full Title: Turkish Computational and Theoretical Chemistry
Journal Abbreviated Title: Turkish Comp Theo Chem (TC&TC)