Identification of New Potential Inhibitors of Quorum Sensing through a Specialized Multi-Level Computational Approach

Molecules. 2021 Apr 29;26(9):2600. doi: 10.3390/molecules26092600.

Abstract

Biofilms are aggregates of microorganisms anchored to a surface and embedded in a self-produced matrix of extracellular polymeric substances and have been associated with 80% of all bacterial infections in humans. Because bacteria in biofilms are less amenable to antibiotic treatment, biofilms have been associated with developing antibiotic resistance, a problem that urges developing new therapeutic options and approaches. Interfering with quorum-sensing (QS), an important process of cell-to-cell communication by bacteria in biofilms is a promising strategy to inhibit biofilm formation and development. Here we describe and apply an in silico computational protocol for identifying novel potential inhibitors of quorum-sensing, using CviR-the quorum-sensing receptor from Chromobacterium violaceum-as a model target. This in silico approach combines protein-ligand docking (with 7 different docking programs/scoring functions), receptor-based virtual screening, molecular dynamic simulations, and free energy calculations. Particular emphasis was dedicated to optimizing the discrimination ability between active/inactive molecules in virtual screening tests using a target-specific training set. Overall, the optimized protocol was used to evaluate 66,461 molecules, including those on the ZINC/FDA-Approved database and to the Mu.Ta.Lig Virtual Chemotheca. Multiple promising compounds were identified, yielding good prospects for future experimental validation and for drug repurposing towards QS inhibition.

Keywords: Chromobacterium violaceum; CviR; MM/GBSA; MM/PBSA; biofilms; molecular docking; molecular dynamics simulations; quorum-sensing; virtual screening.

MeSH terms

  • Anti-Bacterial Agents / chemistry*
  • Anti-Bacterial Agents / pharmacology*
  • Bacterial Proteins / antagonists & inhibitors
  • Bacterial Proteins / chemistry
  • Binding Sites
  • Biofilms / drug effects*
  • Drug Discovery* / methods
  • Humans
  • Ligands
  • Models, Molecular*
  • Molecular Docking Simulation
  • Molecular Dynamics Simulation
  • Molecular Structure
  • Protein Binding
  • Quorum Sensing / drug effects*
  • Structure-Activity Relationship

Substances

  • Anti-Bacterial Agents
  • Bacterial Proteins
  • Ligands