Prospective Virtual Screening in a Sparse Data Scenario: Design of Small‐Molecule TLR2 Antagonists

Abstract

Toll-like receptors (TLRs) are critical signaling molecules with roles in various severe clinical conditions such as sepsis and rheumatoid arthritis, and have therefore been advocated as promising drug targets for the treatment of these diseases. The aim of this study was to discover small-molecule antagonists of TLR2 by computer-aided drug design. This goal poses several challenges due to the lack of available data on TLR2 modulators. To overcome these hurdles we developed a combined structure- and ligand-based virtual screening approach. First, we calculated molecular interaction fields of the TLR2 binding site to derive a structure-based 3D pharmacophore, which was then used for virtual screening. We then performed a two-step shape- and feature-based similarity search using known TLR2 ligands as query structures. A selection of virtual screening hits was biologically tested in a cell-based assay for TLR2 signaling inhibition, leading to the identification of several compounds with antagonistic activity (IC50 values) in the low-micromolar range.