scholarly journals High-Throughput Virtual Screening, Molecular Dynamics Simulation, and Enzyme Kinetics Identified ZINC84525623 as a Potential Inhibitor of NDM-1

2019 ◽  
Vol 20 (4) ◽  
pp. 819 ◽  
Author(s):  
Md Rehman ◽  
Mohamed AlAjmi ◽  
Afzal Hussain ◽  
Gulam Rather ◽  
Meraj Khan

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.


Author(s):  
Simon A. Bray ◽  
Tharindu Senapathi ◽  
Christopher B. Barnett ◽  
Björn A. Grüning

This paper is a tutorial developed for the data analysis platform Galaxy. The purpose of Galaxy is to make high-throughput computational data analysis, such as molecular dynamics, a structured, reproducible and transparent process. In this tutorial we focus on 3 questions: How are protein-ligand systems parameterized for molecular dynamics simulation? What kind of analysis can be carried out on molecular trajectories? How can high-throughput MD be used to study multiple ligands? After finishing you will have learned about force-fields and MD parameterization, how to conduct MD simulation and analysis for a protein-ligand system, and understand how different molecular interactions contribute to the binding affinity of ligands to the Hsp90 protein.



2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Simon A. Bray ◽  
Tharindu Senapathi ◽  
Christopher B. Barnett ◽  
Björn A. Grüning

Abstract This paper is a tutorial developed for the data analysis platform Galaxy. The purpose of Galaxy is to make high-throughput computational data analysis, such as molecular dynamics, a structured, reproducible and transparent process. In this tutorial we focus on 3 questions: How are protein-ligand systems parameterized for molecular dynamics simulation? What kind of analysis can be carried out on molecular trajectories? How can high-throughput MD be used to study multiple ligands? After finishing you will have learned about force-fields and MD parameterization, how to conduct MD simulation and analysis for a protein-ligand system, and understand how different molecular interactions contribute to the binding affinity of ligands to the Hsp90 protein.



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