文献类型：期刊文献

英文题名：Assisting and accelerating NMR assignment with restrained structure prediction

作者：Liu, Sirui[1];Chu, Haotian[2];Xie, Yuhao[1];Wu, Fangming[3];Mu, Fangjing[1];Wei, Jiachen[1];Ni, Ningxi[2];Wang, Chenghao[2];Zhang, Jun[1];Chen, Mengyun[2];Li, Junbin[2];Yu, Fan[2];Fu, Hui[4];Wang, Shenlin[5];Tian, Changlin[3,6];Wang, Zidong[2];Gao, Yi Qin[1,4,7]

机构：[1]Changping Lab, Beijing, Peoples R China;[2]Huawei Technol Co Ltd, Hangzhou, Peoples R China;[3]Chinese Acad Sci, Hefei Inst Phys Sci, High Magnet Field Lab, Hefei, Anhui, Peoples R China;[4]Peking Univ, Coll Chem & Mol Engn, New Cornerstone Sci Lab, Beijing Natl Lab Mol Sci, Beijing, Peoples R China;[5]East China Univ Sci & Technol ECUST, State Key Lab Bioreactor Engn, Shanghai, Peoples R China;[6]Univ Sci & Technol China, Sch Life Sci, Hefei Natl Lab Phys Sci Microscale, Hefei, Peoples R China;[7]Peking Univ, Biomed Pioneering Innovat Ctr BIOPIC, Beijing, Peoples R China

年份：2025

卷号：8

期号：1

外文期刊名：COMMUNICATIONS BIOLOGY

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001532048000004)】；

基金：The authors thank Yupeng Huang for helpful discussions on data processing, and would like to extend our gratitude to Yuanpeng Janet Huang, the author of RPF, for his patience and guidance on how to use dpsimple. This work was supported by the National Science and Technology Major Project (2022ZD0115001 to S.L., Z.W., and Y.Q.G.), the National Natural Science Foundation of China (No. 92353304, and No. T2495221 to Y.Q.G., No. 22274050 to S.W. and 21825703 to C.T.), New Cornerstone Science Foundation (NCI202305 to Y.Q.G.), the Shanghai Science and Technology Commission (contract number: 23J21900300 and 24HC2810700 to S.W.), the Fundamental Research Funds for the Central Universities (to S.W.), the Strategic Priority Research Program of Chinese Academy of Sciences (XDB37000000 to C.T.), and Collaborative Innovation Program of Hefei Science Center, CAS (2022HSC-CIP011 to F.W.). We thank the staff members of the NMR Spectroscopy System (https://cstr.cn/31125.02.SHMFF.SM3.NMR) at the Steady High Magnetic Field Facility, CAS (https://cstr.cn/31125.02.SHMFF), for providing technical support and assistance in data collection and analysis.

语种：英文

摘要：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-domain and few-MSA proteins. The FAAST pipeline for NMR NOESY analysis reduces the time consumption to hours and yields high quality structure ensemble. Both methods show high consistency between predicted structures and restraints, provided or iteratively assigned. This strategy can be expanded to other types of sparse experimental information in structure prediction.