A class A-trained GPCR activation-state classifier transfers to class B1, with attention mass in GLP-1R, GCGR and GIPR spiking at arginine 6.37x37, the TM6 member of the cytoplasmic polar network
Year: 2026
Type: preprint
Abstract: Receptor activation state is the structural variable that most GPCR drug discovery is implicitly trying to control. Using class A GPCR structures only, we trained the Receptor Class-Activation-Map Localizer (RCL), a classifier that distinguishes active from inactive GPCR structures, and evaluated it on class B1, a family it never saw. Pooled class B1 performance was AUROC 0.9532 (95% CI 0.9201 to 0.9863, n = 146). On GLP-1R, held out entirely, it reached AUROC 1.0000 across 43 structures (37 active, 6 inactive). Attention in GLP-1R concentrates at the cytoplasmic end of TM6, a region also named in the pre-registered specification. Against a permutation null, the intracellular third of that helix is enriched 6.78 to 11.30-fold, against 2.93 to 4.01-fold for the helix taken in full. Within that third a single position dominates. R348, generic number 6.37x37, carries the attention maximum in 42 of 43 GLP-1R structures, active and inactive alike and apo structures included, holding a median of 53.58 times the attention mass a uniform distribution would place on a single residue. The same position carries the maximum in 17 of 18 GCGR and 6 of 9 GIPR structures, where it is R346 and R338 respectively; it is an arginine in all three receptors. That position was independently mutated in GLP-1R and reported to modulate receptor activation a decade before this model existed. Before the model was trained we specified and committed a single pass criterion, that attention mass would concentrate in the cytoplasmic third. It was met: enrichment 2.07-fold at 6X18 and 1.94-fold at 6XOX, p < 0.0001 in both. This is a result about activation state rather than about pathway preference; no structure in training carried a pathway label. It recovers known activation biology at the level of a single residue: the position carrying the maximum is the TM6 member of the cytoplasmic polar network, a feature independently described as holding the receptor base closed and as breaking when the receptor couples to a G protein. That a model trained without positional supervision places its attention maximum on a characterized activation residue, in a receptor class it never saw, is what makes these maps a usable input into structure-aware biased-ligand discovery.
Source: ChemRxiv
Author: Stephen G. Odaibo
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7221757437