Model Performance Series
June 2026
Astra AI on GPCRs
GPCRs are the most-drugged protein family in medicine — and among the hardest to characterize computationally. This report shows how the Astra suite reads them from sequence alone: function, topology, PTM sites, binding pockets, and thermostability.
Çağlar Bozkurt, Aniruddh Goteti · Orbion GmbH · Benchmarked on 2,615 GPCRs
What We Found
Three Results That Matter
Each section of the whitepaper reports the headline performance for one prediction area, its known weaknesses, and where we recommend it for production use.
0.97 AUROC on Transmembrane Topology
Per-residue predictions agree with UniProt annotations across the GPCR subfamilies, from the class-A rhodopsin-like receptors through the adhesion and frizzled classes.
F1 Up to 0.94 on PTM Sites
Modification sites are flagged across 39 classes, with two operating points for precision or recall. Strongest on disulfide bonds and N-linked glycosylation.
82% Directional Accuracy on Mutations
On thermostabilizing mutations the model calls the direction of effect right most of the time — enough to filter destabilizers before they reach the bench.
Every number above is reproduced in the whitepaper against public references — Swiss-Prot annotation, PDB co-crystal contacts, and curated experimental thermal-shift data. We report where the models are weak as plainly as where they are strong.