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bioRxiv · 10.64898/2025.12.05.692536

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

Aureli, S.·Piasentin, N.·Frohlking, T.·Rizzi, V.·Gervasio, F. L.
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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 {beta}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 {micro}-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 {micro}-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 O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/692536v1_ufig1.gif" ALT="Figure 1"> View larger version (6K): org.highwire.dtl.DTLVardef@9fae49org.highwire.dtl.DTLVardef@16b5288org.highwire.dtl.DTLVardef@f79af1org.highwire.dtl.DTLVardef@1dd71d8_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Aureli, S., Piasentin, N., Frohlking, T., Rizzi, V., Gervasio, F. L.. 2025-12-09. A Transferable and Robust Computational Framework for Class A GPCR Activation Free Energies. https://doi.org/10.64898/2025.12.05.692536

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