Identification of novel metallo-β-lactamases inhibitors using ligand-based pharmacophore modelling and
Mohammad Ezati1, Ali Ahmadi1, Esmaeil Behmard2
1Molecular Biology Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Abstract:
Metallo-β-lactamases (MBLs) are a group of enzymes that hydrolyze the most commonly used β-lactam-based antibiotics, leading to the development of multi-drug resistance. The three main clinically relevant groups of these enzymes are IMP, VIM, and NDM. This study aims to introduce potent novel overlapped candidates from a ZINC database retrieved from the 200,583-member natural library against the active sites of IMP-1, VIM-2, and NDM-1 through a straightforward computational workflow using virtual screening approaches. The screening pipeline started by assessing Lipinski's rule of five (RO5), drug-likeness, and pan-assay interference compounds (PAINS) which were used to generate a pharmacophore model using D-captopril as a standard inhibitor. The process was followed by the consensus docking protocol and molecular dynamic (MD) simulation combined with the molecular mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method to compute the total binding free energy and evaluate the binding characteristics. The absorption, distribution, metabolism, elimination, and toxicity (ADMET) profiles of the compounds were also analyzed, and the search space decreased to the final two inhibitory candidates for B1 subclass MBLs, which fulfilled all criteria for further experimental evaluation.Communicated by Ramaswamy H. Sarma.
Insights
This study identified two novel drug candidates to combat multi-drug resistant infections by inhibiting metallo-β-lactamases (MBLs), specifically IMP, VIM, and NDM enzymes, through computational screening.
Area of Science:
- Medicinal Chemistry
- Computational Biology
- Drug Discovery
Background:
- Metallo-β-lactamases (MBLs) confer resistance to crucial β-lactam antibiotics.
- IMP, VIM, and NDM are clinically significant MBL enzyme groups driving multi-drug resistance.
- Novel inhibitors are urgently needed to overcome MBL-mediated antibiotic resistance.
Purpose of the Study:
- To computationally identify novel inhibitors targeting IMP-1, VIM-2, and NDM-1 metallo-β-lactamases.
- To screen a large natural compound library for potential MBL inhibitors.
- To evaluate drug-likeness and binding characteristics of identified candidates.
Main Methods:
- Virtual screening of a 200,583-member natural library against MBL active sites.
- Application of Lipinski's Rule of Five (RO5) and PAINS filters.
- Pharmacophore modeling, consensus docking, molecular dynamics (MD), and MM-PBSA calculations.
- ADMET profiling for lead compound assessment.
Main Results:
- A computational workflow successfully filtered a large library down to promising candidates.
- Two potent, novel overlapped inhibitors were identified for B1 subclass MBLs.
- The selected candidates demonstrated favorable drug-likeness and binding characteristics.
Conclusions:
- The study successfully identified two novel drug candidates with potential to inhibit key metallo-β-lactamases.
- These compounds represent promising leads for experimental validation against multi-drug resistant bacteria.
- The computational workflow provides an efficient strategy for discovering novel antibiotic resistance inhibitors.
