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
- A 20-part breakdown of what actually powers an AI agent — goyalshaliniuk · 2026-07-22
- Nature suggests whole-gene editing is possible, and AI may help rebuild the principles — nathanbenaich · 2026-07-22
- ForeAgent predicts agent success before execution and cuts convergence time 6× — jiqizhixin · 2026-07-22
- Podcast maps the open-model race across Kimi, Qwen, GLM and Chinese labs — natolambert · 2026-07-22
- GPT-5.6 Sol nails a one-shot answer in a new FDR-BH one-sided test result — lihua_lei_stat · 2026-07-22
- Training an Agent Class 2 adds distillation resources, slides, and recording — SergioPaniego · 2026-07-22