Statistical Analysis of Protein-Ligand Interaction Patterns in Nuclear Receptor RORγ

The receptor ROR gamma belongs to the nuclear receptor superfamily that senses small signaling molecules and regulates at the gene transcription level. Since ROR gamma has a high basal activity and plays an important role in immune responses, inhibitors targeting this receptor have been a focus for many studies. The receptor-ligand interaction is complex, and often subtle differences in ligand structure can determine its role as an inverse agonist or an agonist. We examined more than 130 existing ROR gamma crystal structures that have the same receptor complexed with different ligands. We reported the features of receptor-ligand interaction patterns and the differences between agonist and inverse agonist binding. Specific changes in the contact interaction map are identified to distinguish active and inactive conformations. Further statistical analysis of the contact interaction patterns using principal component analysis reveals a dominant mode which separates allosteric binding vs. canonical binding and a second mode which may indicate active vs. inactive structures. We also studied the nature of constitutive activity by performing a 100-ns computer simulation of apo ROR gamma. Using constitutively active nuclear receptor CAR as a comparison, we identified a group of conserved contacts that have similar contact strength between the two receptors. These conserved contact interactions, especially a couple key contacts in H11-H12 interaction, can be considered essential to the constitutive activity of ROR gamma. These protein-ligand and internal protein contact interactions can be useful in the development of new drugs that direct receptor activity.

Automated summary

This study examines the receptor-ligand interaction patterns of the ROR gamma receptor and identifies key contacts essential to its constitutive activity. By analyzing crystal structures and performing computer simulations, the differences between agonist and inverse agonist binding are revealed. These findings have implications for the development of new drugs.