报告地点：理化楼C416、腾讯会议ID：331 113 099
报告人：董昊
主办单位：化学化工学院
报告人简介：
董昊，教授、博士生导师，南京大学匡亚明学院副院长。其研究领域是发展多尺度的理论计算方法并结合机器学习方法，用以准确、高效的处理复杂体系。已发表论文55篇，其中以第一作者或（共同）通讯作者已在JACS、Angew Chem Int Ed、Nat Commun、PNAS、JPC A/B/Lett、JCTC等主流学术期刊发表论文38篇（含封面论文4篇）。已获批3项算法开发相关的计算机软件著作权，并先后入选南京大学登峰人才支持计划（B层次）、江苏特聘教授、江苏省优青等项目。
报告简介：
Conformational change of proteins, especially the transition between functional states, is generally associated with their biological processes. However, conformational transitions in proteins are usually not easy to be well characterized by experimental protocols, mainly because of their inadequate temporal and spatial resolution. Recently, we proposed an enhanced conformational sampling protocol within the framework of the feature space of protein structures, and developed a DAta-Driven Accelerated (DA2) sampling method and a two-ended DA2 (teDA2) sampling method: DA2 was designed to search new functional states of a biomolecule from a known structure [1], and teDA2 was designed to identify the possible paths between two available states of a biomolecule [2]. Both methods drive the conformational change of biomolecules in an adaptively updated feature space of biomolecular structures without introducing bias. We explored the possible closed conformation of N-terminal calmodulin (nCaM) from the open one. We further studied the conformational change of adenylate kinase (ADK) between the open and closed state structures, and fold-switching of RfaH protein from the all-α to the all-β states with different secondary structures using teDA2 [3], and obtained the detailed mechanism at the atomic level. As a reliable and efficient enhanced conformational sampling protocol, DA2 and teDA2 could be employed to study the dynamics between different functional states of a broad spectrum of proteins and biomolecular machines.
Reference:
[1] Dong etc., Adv. Theory Simul. 2019, 2, 1800171.
[2] Dong etc., J. Chem. Theory Comput. 2020, 16, 4631.
[3] Dong etc., J. Phys. Chem. B 2022, 126, 2979.
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