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Computational Approaches to the Design of New Antimicrobials

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biophysics".

Deadline for manuscript submissions: closed (31 August 2019) | Viewed by 7069

Special Issue Editor

Special Issue Information

Dear Colleagues,

Antibiotic-resistant bacteria are a major cause of mortality and morbidity and the main threat in hospital and community acquired infections. Among the ways to address antibiotic resistance, the use of computer-designed new drugs and therapies appears to be the most innovative. The application of computational techniques in the field of medicinal chemistry has been validated by numerous recent successes. In microbiology, the availability of crystallographic structures of many pharmacologically relevant proteins makes the use of in silico simulations, an increasingly powerful methodology to fight multidrug resistant bacteria.

This is a multidisciplinary perspective that includes approaches from computational biology, chemistry and biophysics. The opportunity to capture all these views together in a Special Issue of the International Journal of Molecular Sciences seems particularly interesting to me. We wish to demonstrate the enormous potential of computation and virtual simulation for solving the problem of bacterial resistance.

Dr. Paulino Gómez-Puertas
Guest Editor

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Keywords

  • drug design
  • computational biology
  • computational chemistry
  • computational biophysics
  • antimicrobials
  • virtual screening
  • molecular dynamics
  • biophysical characterization
  • innovative methods

Published Papers (1 paper)

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Research

20 pages, 4708 KiB  
Article
High-Throughput Virtual Screening, Molecular Dynamics Simulation, and Enzyme Kinetics Identified ZINC84525623 as a Potential Inhibitor of NDM-1
by Md Tabish Rehman, Mohamed F AlAjmi, Afzal Hussain, Gulam Mohmad Rather and Meraj A Khan
Int. J. Mol. Sci. 2019, 20(4), 819; https://doi.org/10.3390/ijms20040819 - 14 Feb 2019
Cited by 56 | Viewed by 6521
Abstract
The bacteria expressing New Delhi Metallo-β-lactamase-1 (NDM-1) can hydrolyze all β-lactam antibiotics including carbapenems, causing multi-drug resistance. The worldwide emergence and dissemination of gene blaNDM-1 (produces NDM-1) in hospital and community settings, rising problems for public health. Indeed, there is an urgent [...] Read more.
The bacteria expressing New Delhi Metallo-β-lactamase-1 (NDM-1) can hydrolyze all β-lactam antibiotics including carbapenems, causing multi-drug resistance. The worldwide emergence and dissemination of gene blaNDM-1 (produces NDM-1) in hospital and community settings, rising problems for public health. Indeed, there is an urgent need for NDM-1 inhibitors to manage antibiotic resistance. Here, we have identified novel non-β-lactam ring-containing inhibitors of NDM-1 by applying a high-throughput virtual screening of lead-like subset of ZINC database. The screened compounds were followed for the molecular docking, the molecular dynamics simulation, and then enzyme kinetics assessment. The adopted screening procedure funnels out five novel inhibitors of NDM-1 including ZINC10936382, ZINC30479078, ZINC41493045, ZINC7424911, and ZINC84525623. The molecular mechanics-generalized born surface area and molecular dynamics (MD) simulation showed that ZINC84525623 formed the most stable complex with NDM-1. Furthermore, analyses of the binding pose after MD simulation revealed that ZINC84525623 formed two hydrogen bonds (electrostatic and hydrophobic interaction) with key amino acid residues of the NDM-1 active site. The docking binding free energy and docking binding constant for the ZINC84525623 and NDM-1 interaction were estimated to be −11.234 kcal/mol, and 1.74 × 108 M−1 respectively. Steady-state enzyme kinetics in the presence of ZINC84525623 show the decreased catalytic efficiency (i.e., kcat/Km) of NDM-1 on various antibiotics. The findings of this study would be helpful in identifying novel inhibitors against other β-lactamases from a pool of large databases. Furthermore, the identified inhibitor (ZINC84525623) could be developed as efficient drug candidates. Full article
(This article belongs to the Special Issue Computational Approaches to the Design of New Antimicrobials)
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