{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["8(1)"],"submitter":["Liu S"],"pubmed_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"],"journal":["Communications biology"],"pagination":["1067"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12274491"],"repository":["biostudies-literature"],"pubmed_title":["Assisting and accelerating NMR assignment with restrained structure prediction."],"pmcid":["PMC12274491"],"pubmed_authors":["Li J","Xie Y","Zhang J","Wang C","Chen M","Yu F","Tian C","Mu F","Liu S","Ni N","Wu F","Gao YQ","Fu H","Wang S","Chu H","Wei J","Wang Z"],"additional_accession":[]},"is_claimable":false,"name":"Assisting and accelerating NMR assignment with restrained structure prediction.","description":"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","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jul","modification":"2026-03-18T14:16:06.377Z","creation":"2025-08-23T03:09:03.399Z"},"accession":"S-EPMC12274491","cross_references":{"pubmed":["40681704"],"doi":["10.1038/s42003-025-08466-1"]}}