Prediction of Functional Types of Ligands for G Protein-Coupled Receptors with Dynamically Discriminable States Embedded in Low Dimension

Abstract

In principle, the differential dynamics of a protein perturbed by various ligands should be able to reflect ligands’ different functions. However, in the field of G protein-coupled receptor (GPCR), the phenomenon of conformational heterogeneity, i.e., the sharing of conformations traversed by differently liganded receptors, poses a challenge for delineating ligand’s action on perturbing protein dynamics. In a previous work, we have conduct multiple molecular dynamics (MD) simulations of the agonists- and antagonists-bound human A_2A adenosine receptor (A_2AAR) starting from an intermediate state conformation to maximize the sensitivity of ligand-perturbed dynamics. Conformational heterogeneity can be visualized directly by the Markov state model (MSM) analysis, which is a two-stage procedure first by performing clustering based on conformational similarity to form microstates and then kinetic lumping based on state inter-convertibility to aggregate microstates into macrostates. To delineate the geometric properties of these macrostates, we embedded them onto the low dimensional space constructed with a non-linear dimensionality reduction scheme. While the crystal structures of the G-protein coupled receptor in different states (fully active, intermediate, inactive) can be projected onto divisible regions in the first two dimensions of the isomap embedding, conformations from three “purer” states (agonist-enriched, apo-enriched, antagonist-enriched) cannot be very clearly separated with this two-dimensional embedding. Dimensionality higher than two may still be needed to specify dynamically discriminable states even with nonlinear dimensionality reduction techniques.