Back to search

Article

Fine-tuning protein language models on human spatial constraint improves variant effect prediction by reducing wild-type sequence bias

2025-10-16

Abstract excerpt

Protein language models (PLMs) achieve state-of-the-art performance in predicting effects of missense variants, yet they do not explicitly consider variation within the human population. Here, we introduce Hu man S patial C onstraint (HuSC), a framework for quantifying intraspecies constraint on missense variants that integrates population-scale human genetic variation with 3D protein structures. We then fine-t...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
63870c83-4cfb-57fb-90b9-f834207a134c
DOI
10.1101/2025.10.15.682722
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Fine-tuning protein language models on human spatial constraint improves variant effect prediction by reducing wild-type sequence biasDOI 10.1101/2025.10.15.682722
Select a neighboring publication to make it the new centre.