A Transferable and Robust Computational Framework for Class A GPCR Activation Free Energies

Abstract

Abstract The activation of G-protein coupled receptors is involved in many bio-medically important cellular pathways. However, capturing it with molecular simulations is far from trivial as it requires capturing both local and global motions. We recently achieved this goal in a specific receptor (the β 1-adrenergic receptor, or ADRB1) by combining a multiple replica enhanced sampling approach with tailored collective variables. While that approach can be applied to other receptors, it would require a tedious and error-prone choice and refinement of the collective variables, and in particular of the main path-like variable. Herein, we introduce an effective and stream-lined evolved strategy for defining the CVs that reduces user intervention while still achieving a robust free energy convergence. We apply it to two apo-GPCRs of pharmacological relevance, ADRB1 and the µ -opioid receptor. In the first case we show that the reconstructed free energies agree with those obtained with the previous tailored approach, while for the µ -opioid receptor activation we gain novel biological insights. The proposed method can be easily applied to other class A GPCRs, paving the avenue to the systematic elucidation of the activation mechanisms of many crucial drug targets. TOC Graphic

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