微软亚洲研究院王童研究组，利用AI2BMD对蛋白质分子动力学进行了Ab initio表征。该研究于2024年11月6日发表于国际学术期刊《自然》杂志。

研究人员表示，生物分子动力学模拟是生命科学研究的基础，其实用性取决于准确性和效率。经典分子动力学模拟速度快，但缺乏化学精度。量子化学方法（如密度泛函理论）可以达到化学精度，但无法扩展到大型生物分子的应用上。

研究人员建立了一种基于人工智能的ab initio生物分子动力学系统（AI2BMD），它可以高效地模拟具有ab initio精度的全原子大型生物分子。AI2BMD采用蛋白质破碎方案和机器学习力场 ，对超过10000个原子的各种蛋白质进行能量和力计算，从而达到所需的ab initio精确度。

与密度泛函理论相比，它将计算时间缩短了几个数量级。通过几百纳秒的动力学模拟，AI2BMD展示了其高效揭示肽和蛋白质空间构象的能力，得出了与核磁共振实验相匹配的精确3J耦合，并展示了蛋白质的折叠和展开过程。

此外，AI2BMD还能对蛋白质折叠进行精确的自由能计算，其估算的热力学性质与实验结果非常吻合。AI2BMD有可能补充湿性实验室实验，检测生物活性的动态过程，并完成目前无法进行的生物医学研究。

附：英文原文

Title: Ab initio characterization of protein molecular dynamics with AI2BMD

Author: Wang, Tong, He, Xinheng, Li, Mingyu, Li, Yatao, Bi, Ran, Wang, Yusong, Cheng, Chaoran, Shen, Xiangzhen, Meng, Jiawei, Zhang, He, Liu, Haiguang, Wang, Zun, Li, Shaoning, Shao, Bin, Liu, Tie-Yan

Issue&Volume: 2024-11-06

Abstract: Biomolecular dynamics simulation is a fundamental technology for life sciences research, and its usefulness depends on its accuracy and efficiency1,2,3. Classical molecular dynamics simulation is fast but lacks chemical accuracy4,5. Quantum chemistry methods such as density functional theory can reach chemical accuracy but cannot scale to support large biomolecules6. Here we introduce an artificial intelligence-based ab initio biomolecular dynamics system (AI2BMD) that can efficiently simulate full-atom large biomolecules with ab initio accuracy. AI2BMD uses a protein fragmentation scheme and a machine learning force field7 to achieve generalizable ab initio accuracy for energy and force calculations for various proteins comprising more than 10,000 atoms. Compared to density functional theory, it reduces the computational time by several orders of magnitude. With several hundred nanoseconds of dynamics simulations, AI2BMD demonstrated its ability to efficiently explore the conformational space of peptides and proteins, deriving accurate 3J couplings that match nuclear magnetic resonance experiments, and showing protein folding and unfolding processes. Furthermore, AI2BMD enables precise free-energy calculations for protein folding, and the estimated thermodynamic properties are well aligned with experiments. AI2BMD could potentially complement wet-lab experiments, detect the dynamic processes of bioactivities and enable biomedical research that is impossible to conduct at present.

DOI: 10.1038/s41586-024-08127-z

Source: https://www.nature.com/articles/s41586-024-08127-z