LBD@PKU

Tanglab@PKU

Laboratory of Biomolecular Dynamics College of Chemistry and Molecular Engineering & Center for Life Sciences Peking University

Tanglab@PKU

Laboratory of Biomolecular Dynamics College of Chemistry and Molecular Engineering & Center for Life Sciences Peking University

Tanglab@PKU

Laboratory of Biomolecular Dynamics College of Chemistry and Molecular Engineering & Center for Life Sciences Peking University

Introduction

Tanglab introduction to research direction

Prof. Chun Tang's research group is part of the College of Chemistry and Molecular Engineering, PKU-THU Joint Center for Life Sciences, Center for Quantitative Biology at Peking University, and the National Research Center for Molecular Sciences in Beijing. The group is dedicated to exploring the dynamic world of biomacromolecules. It innovatively integrates multidimensional multi-nuclear magnetic resonance spectroscopy, light/chemical crosslinking mass spectrometry analysis, along with artificial intelligence and molecular dynamics simulations to study the structural dynamics of biomacromolecules and the mechanisms by which they are regulated by environmental and chemical modifications. Recently, the team has made significant progress in areas such as the reaction specificity of diazirine photo-crosslinking (Nat. Commun. 2024,15, 6060), subunit interaction dynamics in a large RNA methylation complex (Cell Res. 2022, 32, 1124), the driving force of liquid-liquid phase separation (Phys. Rev. Lett. 2023, 130, 118101), and the structure of RNA-driven phase-separation systems (JACS 2022, 144, 4716). These studies not only offer new insights into the dynamic behaviors of biomacromolecules but also provide potential targets for the diagnosis and treatment of related diseases.

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2008Established time

50+Lab Alumni

80+Publications

Scientific research achievements

Tanglab introduction to representative achievements

In-situ cross-linking mass spectrometry reveals compartment-specific proteasomal interactions and structural heterogeneity

Lili Zhao, Runtao Zhao, Zhou Gong, Fuxiang Liang, Nan Zhao, Bowen Zhong, Maili Liu, Yukui Zhang, Qun Zhao,* Lihua Zhang,* Chun Tang,* (2025), Nat Commun 15(1), 10725. https://doi.org/10.1038/s41467-025-65752-6.

Structural Dynamics of SARS-CoV-2 NSP4 C-terminal Domain and Implications for Viral Processing

Lingshen Meng, Shangxiang Ye, Kai Pei, Chun Tang,* (2025), Journal of Molecular Biology 437(21), 169372. https://doi.org/10.1016/j.jmb.2025.169372

How post-translational modifications impact protein dynamics and stability—experimental and theoretical investigations

Yuhao Li, Hailong Chen, Chun Tang,* (2025), SCIENTIA SINICA Chimica 55(4), 937-948. https://doi.org/10.1360/SSC-2025-0016

Elevated Ubiquitin Phosphorylation by PINK1 Contributes to Proteasomal Impairment and Promotes Neurodegeneration

Cong Chen, Tong-Yao Gao, Hua-Wei Yi, Yi Zhang, Tong Wang, Zhi-Lin Lou, Tao-Feng Wei, Yun-Bi Lu, Ting-Ting Li, Chun Tang,* Wei-Ping Zhang,* (2025), eLife 14, RP103945. https://doi.org/10.7554/eLife.103945.4

Coarse-Grained Simulation Study of the Association of Selected Dipeptides

Mateusz Lesniewski, Emilia Iłowska, Justyna Sawicka, Zihan Li, Chun Tang,* Adam Liwo,* (2024), J. Phys. Chem. B 128, 12403-12415. https://doi.org/10.1021/acs.jpcb.4c06305

Dissecting diazirine photo-reaction mechanism for protein residue-specific cross-linking and distance mapping

Yida Jiang, Xinghe Zhang, Honggang Nie, Jianxiong Fan, Shuangshuang Di, Hui Fu, Xiu Zhang, Lijuan Wang, Chun Tang,* (2024), Nat Commun 15(1), 6060 . https://doi.org/10.1038/s41467-024-50315-y

Connecting Protein Millisecond Conformational Dynamics to Protein Thermal Stability

Xue-Ni Hou, Bin Song, Chang Zhao, Wen-Ting Chu, Mei-Xia Ruan, Xu Dong, Ling-Shen Meng, Zhou Gong, Yu-Xiang Weng, Jie Zheng*, Jin Wang*, Chun Tang*, (2024), JACS Au. https://doi.org/10.1021/jacsau.4c00649

ATP promotes protein coacervation through conformational compaction

Yueling Zhu, Shiyan Lin, Lingshen Meng, Min Sun, Maili Liu, Jingyuan Li,* Chun Tang,* Zhou Gong,* (2024)，Journal of Molecular Cell Biology, mjae038. https://doi.org/10.1093/jmcb/mjae038

Assessment of Two Restraint Potentials for Coarse-Grained Chemical-Cross-Link-Assisted Modeling of Protein Structures

Mateusz Leśniewski, Maciej Pyrka, Cezary Czaplewski, Nguyen Truong Co, Yida Jiang, Zhou Gong, Chun Tang, Adam Liwo,* (2024), J.Chem.Inf.Model.64,4,13771393. https://doi.org/10.1021/acs.jcim.3c01890.

Single-Molecule Force Spectroscopy Reveals Cation-π Interactions in Aqueous Media Are Highly Affected by Cation Dehydration

Weishuai Di, Kai Xue, Jun Cai, Zhenshu Zhu, Zihan Li, Hui Fu, Hai Lei, Wenbing Hu, Chun Tang, Wei Wang, and Yi Cao, (2023), Phys. Rev. Lett. 130, 118101. https://doi.org/10.1103/PhysRevLett.130.118101

Small-Molecule Inhibition of Androgen Receptor Dimerization as a Strategy against Prostate Cancer

Weitao Fu, Hao Yang, Chenxian Hu, Jianing Liao, Zhou Gong, Minkui Zhang, Shuai Yang, Shangxiang Ye, Yixuan Lei, Rong Sheng, Zhiguo Zhang, Xiaojun Yao, Chun Tang*, Dan Li*, and Tingjun Hou*, (2023), ACS Cent. Sci. https://doi.org/10.1021/acscentsci.2c01548

Effects of Mass Change on Liquid–Liquid Phase Separation of the RNA-Binding Protein Fused in Sarcoma

Weiqian Dong, Chun Tang, Wen-Ting Chu, Erkang Wang, Jin Wang,(2023),Biomolecules. Mar 30;13(4):625. doi: 10.3390/biom13040625.

Fast cross-linking by DOPA2 promotes the capturing of a stereospecific protein complex over nonspecific encounter complexes

Wang Jian-Hua, Gong Zhou, Dong Xu, Liu Shu-Qun, Tang Yu-Liang, Lei Xiaoguang, Tang Chun, Dong Meng-Qiu, (2022),. Biophysics Reports. https://doi.org/10.52601/bpr.2022.220014

AI-empowered integrative structural charac terization of m6A methyltransferase complex

Xuhui Yan, Kai Pei, Zeyuan Guan, Feiqing Liu, Junjun Yan, Xiaohuan Jin, Qiang Wang, Mengjun Hou, Chun Tang & Ping Yin, (2022) Cell Research . https://doi.org/10.1038/s41422-022-00741-8

Characterization of protein unfolding by fast cross-linking mass spectrometry using di-ortho-phthalaldehyde cross-linkers

Jian-Hua Wang, Yu-Liang Tang, Zhou Gong, Rohit Jain, Fan Xiao, Yu Zhou, Dan Tan, Qiang Li, Niu Huang, Shu-Qun Liu, Keqiong Ye, Chun Tang, Meng-Qiu Dong, and Xiaoguang Lei, (2022), Nat Commun 13, 1468. https://doi.org/10.1038/s41467-022-28879-4

Nucleobase Clustering Contributes to the Formation and Hollowing of Repeat-Expansion RNA Condensate

Yingxue Ma, Haozheng Li, Zhou Gong, Shuai Yang, Ping Wang, and Chun Tang, (2022), J. Am. Chem. Soc. https://doi.org/10.1021/jacs.1c12085

Preferential Interactions of a Crowder Protein with the Specific Binding Site of a Native Protein Complex

Xu Dong, Ling-Yun Qin, Zhou Gong, Sanbo Qin, Huan-Xiang Zhou, and Chun Tang, (2022). J. Phys. Chem. Lett.: 792–800. https://doi.org/10.1021/acs.jpclett.1c03794

Recent Developments in Data-Assisted Modeling of Flexible Proteins

Czaplewski, C., et al. (2021). Frontiers in Molecular Biosciences 8(1306). https://doi.org/10.3389/fmolb.2021.765562

Discovery of a Novel Androgen Receptor Antagonist Manifesting Evidence to Disrupt the Dimerization of the Ligand-Binding Domain via Attenuating the Hydrogen-Bonding Network Between the Two Monomers

Fu, W., et al. (2021). Journal of Medicinal Chemistry 64(23): 17221-17238. https://doi.org/10.1021/acs.jmedchem.1c01287

Pseudopotentials for coarse-grained cross-link-assisted modeling of protein structures

Mateusz Kogut, Zhou Gong, Chun Tang, Adam Liwo. (2021). Journal of Computational Chemistry 42 (29), 2054-2067 https://doi.org/10.1002/jcc.26736

Kinetic Constraints in the Specific Interaction between Phosphorylated Ubiquitin and Proteasomal Shuttle Factors

Qin LY, Gong Z, Liu K, Dong X and Tang C. (2021) . Biomolecules, 10.3390/biom11071008

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices

Lerner E, Barth A, Hendrix J, Ambrose B, Birkedal V, Blanchard SC, Börner R,Chung HS, Cordes T, Craggs TD, Deniz AA, Diao JJ, Fei JY, Gonzalez RL, Gopich IV, Ha T, Hanke CA, Haran G, Hatzakis NS, Hohng SC, Hong SC, Hugel T, Ingargiola A, Joo C, Kapanidis AN, Kim HD, Laurence T, Lee NK, Lee TH, Lemke EA, Margeat E, Michaelis J, Michalet X, Myong S, Nettels D, Peulen TO, Ploetz E, Razvag Y, Robb NC, Schuler B, Soleimaninejad H, Tang C, Vafabakhsh R, Lamb DC, Seidel CA, Weiss S. (2021) . eLife 2021;10:e60416

Tightening the crosslinking distance restraints for better resolution of protein structure and dynamics

Gong Z, Ye SX and Tang C. (2020) . Structure, 28:1160-1167

FLIM-FRET based structural characterization of a class-A GPCR dimer in the cell membrane

Yang J, Gong Z, Lu YB, Xu CJ, Wei TF, Yang MS, Zhan TW, Yang YH, Lin L, Liu JF, Tang C and Zhang WP. (2020) . J Mol Biol, 432:4596-4611

Hierarchical conformational dynamics confers thermal adaptability to preQ1 RNA riboswitches

Gong Z, Yang S, Dong X, Yang QF, Zhu YL, Xiao Y, Tang C. (2020) .J Mol Biol, 432:4523-4543

The conformational preference of chemical crosslinkers determins the crosslinking probability of reactive protein residues

Gong Z, Ye SX, Nie ZF and Tang C. (2020) . J Phy Chem B, 123:4446-4453

Integrating Non-NMR Distance Restraints to Augment NMR Depiction of Protein Structure and Dynamics

Tang C and Gong Z. (2020) . J Mol Biol, 432:2913-2929

How phosphorylation by PINK1 remodels the ubiquitin system, a perspective from structure and dynamics

Tang C and Zhang WP. (2020) . Biochemistry, 59:26-33

Gaining Molecular Insights

We investigate the conformational dynamics of proteins and other biologically important molecules, learning how are they influenced by chemical modifications and environmental factors critical to their function.

Novel Analytical Techniques

We develop innovative analytical techniques, focusing onnuclear magnetic resonance (NMR) and crosslinking combined with mass spectrometry (XL-MS). We also designadvanced probes and develop computational methods tointerpret the resulting data effectively.

Integrative Computational Methods

We develop novel computational methods with the use ofmachine learning. Our approach improves the assignmentof different conformational states and enables effectiveintegration of diverse experimental data, while allowing usto make optimal use of both experimental insights andknowledge-based inferences

Team Strengths

Reasons for choosing us

Unlock Your Full Potential

We are committed to cultivating researchers with independent thinking, innovative spirit, and collaborative mindset. Our established academic reputation and international influence will open doors for your career development, creating a broader landscape for your future.

Achieve Your Aspirations

Engage in impactful research projects with international influence, tackle challenging scientific problems, and generate groundbreaking original findings that advance the field. Every day here is an opportunity to make breakthroughs and ignite your creative spark.

Pioneer the Frontiers of Science

We integrate traditional biophysical methods with emerging technologies like artificial intelligence and computational modeling, providing comprehensive and unique research training. You will have the opportunity to develop and apply cutting-edge research tools, drive innovative studies, and push the boundaries of life science.

Unravel the Mysteries of Life

Immerse yourself in a world-leading group of biomolecular dynamics research. Utilize cutting-edge experimental techniques like NMR, single-molecule fluorescence, and high-resolution mass spectrometry, coupled with powerful computational resources, to uncover the secrets of life at the molecular level.

Renowned Professor for Achieving Research Aspirations

Professor Tang is an internationally recognized scholar in the field of biomolecular dynamics, with extensive research experience and profound academic achievements. He not only demonstrates exceptional leadership in technological innovation but also remains dedicated to the growth and career development of his students and trainees.

Cutting-edge Research Platform for Groundbreaking Discoveries

Our laboratory is equipped with state-of-the-art experimental facilities, including Nuclear Magnetic Resonance (NMR), single-molecule fluorescence, and high-resolution mass spectrometry. Coupled with powerful data analysis and computational resources, we are on a solid footing for cutting-edge scientific exploration.

Collaborative and Supportive Environment for Unleashing Potential

We foster an open, collaborative, and driven research environment where every member thrives. The mentor, Prof. Tang, provides close guidance, encourages innovation, and prioritizes cultivating independent research skills. Within this supportive atmosphere, everyone learns and grows together, fostering mutual progress, no matter where you are in your research journey, this is fertile ground for rapid growth.

Interdisciplinary Research for Broadened Horizons

Our lab employs a problem-driven approach to research, seamlessly integrating knowledge of chemistry, physics, biology, and computational science. We transcend the limitations of single techniques or methodologies, embracing interdisciplinary collaboration to gain deeper insights into the molecular essence of life.

members

Tanglab introduction to the members

The Tang Chun Research Group is dedicated to exploring the dynamic world of biomacromolecules. It innovatively integrates techniques such as multidimensional and multi-nuclear NMR spectroscopy, photochemical/crosslinking mass spectrometry, as well as artificial intelligence and molecular dynamics simulations, to deeply investigate the structural dynamics of biomacromolecules and the mechanisms by which they are regulated by environmental factors and chemical modifications.

Chun Tang(唐淳)

Email: Tang_Chun@pku.edu.cn Tel: +86-10-6275-8440 Office: A530 Chemistry Building URL: http://tanglab.pku.edu.cn/

Haocheng Tang(唐浩程）

I am Haocheng Tang. I earned my Bachelor of Science degree in Chemistry from Peking University in 2024, where I completed my undergraduate thesis research in the Tang Laboratory. I subsequently obtained my Master of Science degree in Pharmaceutical Sciences from the University of Pittsburgh in 2026. I am incoming to pursue a PhD in Computer Science, with a continued focus on large language models and AI for Science.

Shuchen Zhong(钟书辰)

I'm Shuchen Zhong. I received my Bachelor's degree from Peking University and now I am currently studying as a phd student under the supervision of Prof Tang and Prof Luhua Lai. My recent research focuses on drug development on novel targets and mechanims of allosteric ligands.

Li Zhang(张黎)

My name is Zhang Li. I earned my Master's degree from Yanbian University. I am delighted to join the Tang Lab for my Ph.D. My research focuses on elucidating nucleic acid structures using NMR spectroscopy and investigating the phase separation of biomolecular condensate.

Zhu Liu(刘主)

刘主原组内博士现任职于华中农业大学生命科学技术学院，学科：无线电物理物理化学生物化学与分子生物学

Xinhua Gu(顾新华)

顾新华，博士万物并作管理咨询有限公司董事长百万粉丝科普自媒体博主@大分子实验室主理人南京野生植物综合利用研究院客座教授

Liyuan Wang(王李原)

I am Wang Liyuan, a Gemini girl who loves taking photos, citywalk, and playing table tennis. I recived Ph.D. from Yanbian University in the group of Prof.Li Donghao. It’s honored to join the Tang Lab and start my postdoctoral research on chemical cross-linking mass spectrometry.

Yida Jiang(江意达)

我是唐老师2021级博士研究生江意达，目前从事光交联的相关研究，并负责一部分实验室内的仪器和运维工作。业余期间，我喜欢策略类的游戏和骑行摄影。我的个人主页是http://jiangyida.top。

Yuhao Li(李煜昊)

I’m Yuhao Li . I obtained my Bachelor’s degree from Peking University at 2022. And now I am continuing my career in PKU CCME and studying from my PhD in Tang lab. It’s a great pleasure to do my research in such a passionate and fun team.

Jianxiong fan(范健雄)

Hi, I’m Fan Jianxiong. Majored in applied chemistry, I graduated from East China University of Science and Technology in 2023. It’s my honor to be a member of Tang Lab.

Runtao Zhao(赵润涛)

Hi, I am Zhao Runtao, graduated from Peking University and currently working on my PhD at Tanglab.

news information

Tanglab introduction to the news

唐淳课题组合作开发应用细胞内交联质谱技术，表征蛋白质机器原位结构动态

2025年11月28日，北京大学化学与分子工程学院、北大-清华生命科学联合中心唐淳教授团队与中国科学院大连化学物理研究所张丽华团队，在Nature Communications 上发表题为《In-situ Cross-Linking Mass Spectrometry Reveals Compartment-Specific Proteasomal Interactions and Structural Heterogeneity》的研究论文，首次利用原位交联质谱技术，在完整细胞环境中系统解析了人源26S蛋白酶体在不同亚细胞区室（细胞核与细胞质）的构成差异、互作网络与结构动态特征。

唐淳课题组揭示路易体痴呆发病新机制

近日，北京大学化学与分子工程学院唐淳教授团队与浙江大学基础医学院张纬萍副教授团队、北京大学第六医院国家精神疾病医学中心王华丽教授团队，在国际权威期刊《Alzheimer’s & Dementia》合作发表最新研究论文，题为 “PINK1 deficiency permits the development of Lewy body dementia with coexisting Aβ pathology”。该研究系统地揭示了PTEN诱导激酶1（PINK1）在调控DLB病理中的关键作用。

Tanglab每周五Coffe Time：欢乐交流的咖啡派对

每周五下午两点，是Tanglab的Coffe Time！这是一个轻松愉快的时光，大家可以在这里尽情享受香浓的咖啡，放松心情，畅所欲言。

美国科学院院士Martin Gruebele受唐淳教授邀请访问北京大学

美国科学院院士Martin Gruebele教授于2025年4月访问北京大学，受唐淳教授邀在化学学院进行学术交流。他首先发表了关于纳米材料与生物分子相互作用的报告，探讨了纳米技术的应用。随后，与博士生江意达进行了100公里的骑行活动，增进了学术与文化交流。最后，他进行了关于量子信息领域最新研究的报告，进一步推动了量子计算的前沿探索。

王华丽/王立明/沈汉明点评 eLife︱张纬萍/唐淳团队揭示磷酸化泛素抑制蛋白酶体降解通路促进神经元退行性变化的作用机制

泛素（Ubiquitin）是真核细胞中高度保守的蛋白质，通过共价修饰底物蛋白质（被称为泛素化修饰）、非共价与靶蛋白结合，参与几乎所有细胞生命活动，其调控异常与神经退行性疾病、肿瘤等疾病密切相关。在中枢神经系统，泛素依赖的蛋白酶体降解系统（Ubiquitin-dependent proteasomal system，UPS）对于维持神经元蛋白质稳态至关重要，UPS降解活性进行性下降即是神经元退行性变化的主要特点，也是促进神经元退行性变化进展的重要原因。大量研究显示，在衰老及相关的神经退行性疾病发生发展过程中，由于蛋白酶体组成单元的表达下降、ATP水平下降、Ab聚集等各种诱因，可导致蛋白酶体活性下降、蛋白质聚集，进而损伤神经元。然而，在神经退行性变化过程中，UPS活性为何持续进行性下降，了解较少。此外，泛素的Ser65位点能够被PINK1（PTEN-induced kinase 1）磷酸化，有研究发现在老年和帕金森病患者，脑内神经元磷酸化泛素显著增加，但对磷酸化泛素的生物学作用，除参与线粒体自噬外，研究甚少。

生命中心成功举办2024国际学术研讨会

大会主持人：唐淳教授，祁海教授 2024年11月13日至14日，生命中心国际学术研讨会在清华大学蒙民伟楼多功能厅成功举行。本次学术盛会由生命中心PI祁海教授、唐淳教授主持，邀请到了7位生医药领域享有盛誉的顶尖科学家为大家带来一系列精彩绝伦的学术报告。

安全知识小课堂之快板话安全

赵润涛同学通过快板的方式，生动的讲述实验室安全知识。

喜报：TANGLAB江意达同学获得国家奖学金并获批国自然青年学生基础研究项目

热烈祝贺我校2021级博士研究生江意达同学荣获2023-2024年度国家奖学金，并成功获批国家自然科学基金青年学生基础研究项目专项资助！

TangLab香八拉徒步春游

4月12日，春风和煦，阳光明媚，山间的薄霾并未阻挡春游的脚步，Tanglab成员沿香八拉徒步路线，开展了一次强健体魄，增进情谊的团建活动。

过来人经常讲给赶路人的几个故事

唐老师有一块牌匾，写的是“天道酬勤”，他跟我讲，他去国外求学时就背着去的。在武汉的那十年，他高悬在办公室的门框上，我在那块牌匾下学习和成长