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Targeting and Ultrabroad Insight Into Molecular Basis of Resistance-Nodulation-Cell Division Efflux Pumps Publisher Pubmed



Seyedhosseini Ghaheh H1 ; Damavandi MS2 ; Sadeghi P2, 3 ; Massah AR4 ; Asl TH5 ; Salarijazi A3 ; Hejazi SH5
Authors
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Authors Affiliations
  1. 1. Department of Pharmaceutical Biotechnology, School of Pharmacy and Pharmaceutical Sciences, Isfahan University of Medical Sciences, Isfahan, Iran
  2. 2. Department of Microbiology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
  3. 3. Department of Drug Development and Innovation, Behban Pharmed Lotus, Tehran, Iran
  4. 4. Department of Chemistry, Shahreza Branch, Islamic Azad University, P.O. Box 311-86145, Shahreza, Isfahan, Iran
  5. 5. Skin Diseases and Leishmaniasis Research Center, Department of Parasitology and Mycology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Scientific Reports Published:2022


Abstract

Resistance-nodulation-cell devision (RND) efflux pump variants have attracted a great deal of attention for efflux of many antibiotic classes, which leads to multidrug-resistant bacteria. The present study aimed to discover the interaction between the RND efflux pumps and antibiotics, find the conserved and hot spot residues, and use this information to target the most frequent RND efflux pumps. Protein sequence and 3D conformational alignments, pharmacophore modeling, molecular docking, and molecular dynamics simulation were used in the first level for discovering the function of the residues in interaction with antibiotics. In the second level, pharmacophore-based screening, structural-based screening, multistep docking, GRID MIF, pharmacokinetic modeling, fragment molecular orbital, and MD simulation were utilized alongside the former level information to find the most proper inhibitors. Five conserved residues, containing Ala209, Tyr404, Leu415, Asp416, and Ala417, as well as their counterparts in other OMPs were evaluated as the crucial conserved residues. MD simulation confirmed that a number of these residues had a key role in the performance of the efflux antibiotics; therefore, some of them were hot spot residues. Fourteen ligands were selected, four of which interacted with all the crucial conserved residues. NPC100251 was the fittest OMP inhibitor after pharmacokinetic computations. The second-level MD simulation and FMO supported the efficacy of the NPC100251. It was exhibited that perhaps OMPs worked as the intelligent and programable protein. NPC100251 was the strongest OMPs inhibitor, and may be a potential therapeutic candidate for MDR infections. © 2022, The Author(s).
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