[2603.23583] ZeroFold: Protein-RNA Binding Affinity Predictions from Pre-Structural Embeddings

Quantitative Biology > Biomolecules arXiv:2603.23583 (q-bio) [Submitted on 24 Mar 2026] Title:ZeroFold: Protein-RNA Binding Affinity Predictions from Pre-Structural Embeddings Authors:Josef Hanke (1), Sebastian Pujalte Ojeda (1), Shengyu Zhang (1), Werngard Czechtizky (2), Leonardo De Maria (2), Michele Vendruscolo (1) ((1) Yusuf Hamied Department of Chemistry, University of Cambridge, UK (2) Medicinal Chemistry, Research and Early Development, Respiratory and Immunology, BioPharmaceuticals R and D, AstraZeneca, Sweden) View a PDF of the paper titled ZeroFold: Protein-RNA Binding Affinity Predictions from Pre-Structural Embeddings, by Josef Hanke (1) and 11 other authors View PDF Abstract:The accurate prediction of protein-RNA binding affinity remains an unsolved problem in structural biology, limiting opportunities in understanding gene regulation and designing RNA-targeting therapeutics. A central obstacle is the structural flexibility of RNA, as, unlike proteins, RNA molecules exist as dynamic conformational ensembles. Thus, committing to a single predicted structure discards information relevant to binding. Here, we show that this obstacle can be addressed by extracting pre-structural embeddings, which are intermediate representations from a biomolecular foundation model captured before the structure decoding step. Pre-structural embeddings implicitly encode conformational ensemble information without requiring predicted structures. We build ZeroFold, a transformer-bas...