Assisting and accelerating NMR assignment with restrained structure prediction.

ABSTRACT: Accurate dynamic protein structures are essential for drug design. NMR experiments can detect protein structures and potential dynamics, but the spectrum assignment and structure determination requires expertise and is time-consuming, while deep-learning-based structure predictions may be inconsistent with experimental observations. A symbiosis between experiments and AI methods is therefore essential for solving such problems. Here, we developed a Restraint Assisted Structure Predictor (RASP) model and an iterative Folding Assisted peak ASsignmenT (FAAST) pipeline directly leveraging experimental information to improve the AI-assisted structure prediction and facilitate experimental data analysis in an integrative way. The RASP model improves structure prediction, especially for multi-dom

SUBMITTER: Liu S 

PROVIDER: S-EPMC12274491 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature