In Silico Development of Quorum-Sensing Inhibitors

Abstract

Quorum sensing (QS) is a chemical communication between bacteria, with which bacteria sense the population of their own species. Autoinducer-2 (AI-2) is a class of universal quorum-sensing molecules, which is used by both Gram-negative and Gram-positive bacteria. The inhibition of AI-2-mediated QS has various practical applications, including the prevention of the formation of biofilm in dental gums. In this work, we develop a computational protocol for developing AI-2 inhibitors. A challenging aspect of such an endeavor is that the receptor undergoes a large conformational change upon ligand binding. We combine several methods such as molecular docking with multiple conformations, molecular dynamics simulations, and molecular mechanics Poisson-Boltzmann computation, in order to estimate binding affinity of candidate molecules to a quorum-sensing receptor. We apply our method to rank the substances in a chemical library. We indeed find a molecule that has a higher affinity than previously known ligands, thus showing the feasibility of the protocol for the development of quorum-sensing inhibitors.