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

## TL;DR

This paper introduces a new computational method to study GPCR activation, making it easier and more reliable for various receptors.

## Contribution

The novel contribution is a streamlined strategy for defining collective variables in molecular simulations of GPCRs.

## Key findings

- The new method achieves robust free energy convergence with reduced user intervention.
- It was successfully applied to ADRB1 and the μ-opioid receptor, yielding consistent and novel insights.
- The approach is transferable to other class A GPCRs, enabling systematic activation mechanism studies.

## Abstract

The activation of
G-protein coupled receptors is involved
in many
biomedically 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 β1-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 streamlined evolved
strategy for defining 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 way for the systematic elucidation of the activation mechanisms
of many crucial drug targets.