Protein language models can learn homo-oligomer contacts from single sequences
anshulkundaje · x · 2026-07-22
A reposted discussion highlights a paper finding that protein language models trained only on individual sequences can implicitly learn interface contacts in homo-oligomeric assemblies.
As model scale increases, interface signals become more visible. The authors also note some PDB-labeled homo-oligomers do not show the expected signals, which led them to investigate when these contacts emerge—and when they are absent.
Related event: Protein Language Models Emerge Interface Signals from Single Sequences(2 posts)→
More from Research
- Datology webinar: Curation Studio matched top data baselines with under 20% compute — josh_wills · 2026-10-27
- KANLab: an interactive browser playground for Kolmogorov-Arnold Networks — Lukas Niehaus · 2026-10-27
- CMU's LLM2Cert synthesizes stability certificates verified via SMT and Lean — CarnegieMellonU · 2026-10-27
- NVIDIA open-sources FLORA, a robotics data engine ~125x cheaper than GPT-6 Astra — nvidia · 2026-10-27
- RSNA 2026 Deep Learning Labs return: eight hands-on AI classes over four days in Chicago — PRouzrokh · 2026-10-27
- Steering two orthogonal concept neurons makes a model compose "gnome" — Sauers_ · 2026-10-27