INAB: identify nucleic acid binding domain via cross-modal protein language models and multiscale computation.

ABSTRACT: Protein-nucleic acid interactions play a crucial role in biological processes, including gene regulation and editing. Accurately identifying nucleic acid-binding domains in proteins is essential to unravel these interactions, yet traditional experimental methods like X-ray crystallography remain costly and time-intensive. Computational approaches have thus emerged as indispensable tools to complement wet-lab techniques. Here, we introduce a framework for nucleic acid-binding domain prediction by integrating cross-modal protein language models with a multiscale computational architecture. The proposed method leverages a structurally annotated benchmark dataset, which quantifies binding likelihood through hierarchical, proximity-based labels derived from experimental complexes. Evaluations d

SUBMITTER: Zhang J 

PROVIDER: S-EPMC12477684 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature