The calcitonin receptor-like receptor (CLR) is a class B GPCR with an extracellular domain that binds to peptide ligands in the calcitonin family and controls a wide range of downstream cellular processes.  CLR is an obligate heterodimer that can only engage calcitonin peptides (including calcitonin, amylin, calcitonin gene-related peptides  and , adrenomedullin and adrenomedullin 2/intermedin) when in conjunction with binding partners called RAMPs, which also modulate CLR ligand selectivity. These receptors are of significant clinical interest for a variety of pathologies, including heart disease, migraine and type I and II diabetes. Atomic details of peptide recognition of CLR-RAMP complexes are important to rationalize existing results and to design new compounds that can target class B GPCRs. Although atomic interactions in high probability bound states can be characterized experimentally, the interactions occurring along binding and unbinding pathways that determine kinetics are much more challenging to observe.  Using a weighted ensemble based enhanced sampling method called REVO (“Reweighting ensembles by variation optimization”) we generate unbinding ensembles for a series of CLR-RAMP-peptide complexes.  REVO has been previously shown to surmount very large free energy barriers without applying biasing forces or pre-supposing details of reaction pathways.  REVO trajectory fragments can then be combined into holistic maps of the free energy landscape, showing how different stable states are connected, and the most probable mechanisms of unbinding.  Analysis of this data reveals how changes in the sequences of RAMP proteins affect the selectivity and kinetics of calcitonin-like peptide binding.

Atomistic insights into CLR-RAMP peptide binding using REVO weighted ensemble simulations

ACS Fall 2021

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