arXiv:2610.33804v1 Announce Type: new
Abstract: Intrinsically disordered proteins (IDPs) carry out their functions through heterogeneous conformational ensembles that reflect their dynamics, yet most protein function prediction methods rely on sequence or a single static structure. To this end, we introduce DynaReason-Pro, the first framework to jointly predict GO terms from conformational ensembles and generate natural-language functional rationales. We evaluate DynaReason-Pro on a curated IDP benchmark from the Protein Ensemble Database (PED), with sequence- and structure-cluster-disjoint splits to prevent data leakage. Variability-stratified evaluation shows the clearest gains in the high-conformational-variability regime.
Abstract: Intrinsically disordered proteins (IDPs) carry out their functions through heterogeneous conformational ensembles that reflect their dynamics, yet most protein function prediction methods rely on sequence or a single static structure. To this end, we introduce DynaReason-Pro, the first framework to jointly predict GO terms from conformational ensembles and generate natural-language functional rationales. We evaluate DynaReason-Pro on a curated IDP benchmark from the Protein Ensemble Database (PED), with sequence- and structure-cluster-disjoint splits to prevent data leakage. Variability-stratified evaluation shows the clearest gains in the high-conformational-variability regime.
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Beyond Static Structures: Linking Protein Dynamics to Function via DynaReason-Pro