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PLM-eXplain: Divide and Conquer the Protein Embedding Space

Title: PLM-eXplain: Divide and Conquer the Protein Embedding Space
Authors: van Eck, Jan; Gogishvili, Dea; Silva, Wilson; Abeln, Sanne; Sub AI Technology for Life; Sub Biology AI Technology For Life
Publication Year: 2026
Subject Terms: Statistics and Probability; Biochemistry; Molecular Biology; Computer Science Applications; Computational Theory and Mathematics; Computational Mathematics
Description: MOTIVATION: Protein language models (PLMs) have revolutionized computational biology through their ability to generate powerful sequence representations for diverse prediction tasks. However, their black-box nature limits biological interpretation and translation to actionable insights. Bridging this gap requires approaches that maintain predictive performance while providing interpretable explanations of model behaviour. RESULTS: We present PLM-eXplain (PLM-X), an explainable adapter layer that bridges this gap by factoring PLM embeddings into two complementary components: an interpretable subspace based on established biochemical features, and a residual subspace that retains predictive, non-interpretable information. Using embeddings from ESM2 and ProtBert, PLM-X incorporates well-established properties, including secondary structure and hydropathy, while maintaining high predictive performance. We demonstrate the effectiveness of our approach across three biologically relevant classification tasks: extracellular vesicle association, transmembrane helix prediction, and aggregation propensity prediction. PLM-X enables biological interpretation of model decisions without sacrificing accuracy, offering a generalizable solution for enhancing PLM interpretability across various downstream applications. AVAILABILITY AND IMPLEMENTATION: Source code and models are available at https://github.com/AIT4LIFE-UU/PLM-eXplain/.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
ISSN: 1367-4803
Relation: https://dspace.library.uu.nl/handle/1874/480132
Availability: https://dspace.library.uu.nl/handle/1874/480132
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.CDD87F7B
Database: BASE