biostudies-literatureUnknown8(1)Liu SAccurate 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-domCommunications biology1067https://www.ebi.ac.uk/biostudies/studies/S-EPMC12274491biostudies-literatureAssisting and accelerating NMR assignment with restrained structure prediction.PMC12274491Li JXie YZhang JWang CChen MYu FTian CMu FLiu SNi NWu FGao YQFu HWang SChu HWei JWang ZfalseAssisting and accelerating NMR assignment with restrained structure prediction.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-dom2025-01-01T00:00:00Z2025 Jul2026-03-18T14:16:06.377Z2025-08-23T03:09:03.399ZS-EPMC122744914068170410.1038/s42003-025-08466-1