Selective probes and antagonists for G protein-coupled receptor LPAR1.

Abstract

The G protein-coupled receptors (GPCRs) constitute the largest class of signaling molecules in the human genome with diverse disease pathogenesis, yet many of receptors with unknown antagonists continue to remain. The complex biology and potential for drug discovery within this class provides strong incentives for chemical biology approaches that seek to develop small molecule probes. In addition to this, it will also help to facilitate the elucidation of mechanistic pathways and enable the specific manipulation of the individual receptors’ activity. We have initiated a small molecule antagonist that actively targets lysophosphatidic acid receptor (LPAR1), a clinically important target that is linked to several metabolic and inflammatory diseases including cancer, fibrosis, and rheumatoid arthritis. While numerous selective LPAR1 antagonists have been developed their clinical efficacy has only been evaluated in idiopathic pulmonary fibrosis. As a useful aid in the various efforts of identifying novel effective LPAR1 antagonists, diverse computational methods can serve as an important and valuable tool. In particular, the sequent in-silico approaches such as virtual screening, molecular docking, molecular dynamics simulation, and protein-ligand binding free energy are able to refine the accuracy of in-silico approaches of GPCR-antagonist complexes. In our study, we focused on trying to identify novel LPAR1 antagonists using the in-silico virtual screening of commercial databases on the human LPAR1 model. Various molecular modeling methodologies such as molecular docking and dynamics simulation, along with different drug likeness filtering criteria, were applied to select anti-LPAR1 antagonists as promising candidate molecules based on different known lead compounds. In-vitro binding assays of the selected molecules are expected to demonstrate activity within the nanomolar range of Ki or IC50. The current integrated computational and experimental methods used in this work can provide new insights for systematic hit identification for novel anti-LPAR1 agents.