Abstract

The development of small molecule allosteric modulators acting at G protein-coupled receptors (GPCRs) is becoming increasing attractive. Such compounds have advantages over traditional drugs acting at orthosteric sites on these receptors, in particular target specificity. However, the number and locations of druggable allosteric sites within most clinically relevant GPCRs are unknown. In the present study, we describe the development and application of a mixed-solvent molecular dynamics-based method for the identification of allosteric sites on GPCRs. The method employs small organic probes with drug-like qualities to identify druggable hotspots in multiple replicate short-timescale simulations. As proof of principle, we first applied the method retrospectively to a test set of five GPCRs Cannabinoid Receptor Type 1, C-C Chemokine Receptor Type 2, M2 Muscarinic Receptor, P2Y Purinoceptor 1, and Protease-Activated Receptor 2) with known allosteric sites in diverse locations. This resulted in the positive identification of the known allosteric sites on these receptors. We then applied to method to the mu-opioid receptor. Several allosteric modulators for this receptor are known, although the binding sites for these modulators are not known. The mixed-solvent molecular dynamics-based method revealed several potential allosteric sites on the mu-opioid receptor. Implementation of the mixed-solvent molecular dynamics-based method should aid future efforts in the structure-based drug design of drugs targeting allosteric sites on GPCRs.

Significance Statement Allosteric modulation of G-protein-couple-receptors (GPCRs) has the potential to provide more selective drugs. However, there are limited structures of GPCRs bound to allosteric modulators and obtaining such structures is problematic. Current computational methods utilize static structures and so may not identify hidden or cryptic sites. Here, we describe the use of small organic probes and molecular dynamics to identify druggable allosteric hotspots on GPCRs. The results reinforce the importance of protein dynamics in allosteric site identification.