About

Research Directions

Exploring Protein-DNA Interactions Through Advanced Computational and Experimental Techniques

A creative representation of a DNA helix using flowers and leaves, symbolizing nature and biotechnology.
A creative representation of a DNA helix using flowers and leaves, symbolizing nature and biotechnology.

About Da Lab

At Da Lab, we integrates computational biophysics and experimental approaches to elucidate atomic-level mechanisms of biomolecular recognition, dynamics, and catalysis—with focus on protein-DNA/RNA interactions, immune recognition systems, and enzyme engineering—for therapeutic discovery and disease intervention.

Our findings have achieved atomic-level mechanistic insights into biomolecular recognition processes, leading to high-impact discoveries in transcription regulation, DNA repair, immune recognition, and viral entry mechanisms that enable rational drug design for cancer, HIV, and other diseases.

We are currently recruiting graduate students (including M.S./PhD students) in the field of computational chemistry/biophysics or related areas. The quota of PhD students is limited. Those who are interested please send the CV to: darlt@sjtu.edu.cn.

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Years of joining SJTU
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Happy Members
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Paper Publishing
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Student Graduation

Recent Publications

Founded with a vision to bridge computational and experimental research, Darlintai Lab has have achieved breakthroughs in understanding molecular recognition mechanisms—revealing enzyme substrate specificity for unnatural amino acid incorporation, discovering pressure-responsive transcription regulation in extremophiles, elucidating glycosylation site preference rules, and developing computational tools for decoding immune receptor interactions—advancing biocatalysis, extremophile biology, glycobiology, and immunotherapy design.

Year 2025

Structural Insights into the Substrate Recognition Mechanism of an ATP-Grasp Peptide-Ligase Producing Diverse Dipeptides Containing Unnatural Amino Acids. Ya-Qian Yan, Si-Yuan Li, Xiao-Na Wu, Ting Zhou, Jia-Xin Li, Shu-Xin Huang, Jian-Ting Zheng, Jun Xu, Lin-Tai Da*, and Min-Juan Xu*, ACS Catal. 2025, 15: 2550–2560

Year 2024

Comprehensive Investigations of MUC1 O Glycosylation Process Reveal Initial Site Preference by the Polypeptide GalNAc Transferases. Han Zhang, Kaiyuan Song, Yihan Liu, Fang Yang, Congcong Lu, Rumeng Wei, Zhijue Xu, Xia Zou, Liang Lin, Ting Shi, Lin-Tai Da*, and Yan Zhang*, ACS Catal. 2024, 14: 18365-18377.

Year 2024

Investigating TCR-pMHC interactions for TCRs without identified epitopes by constructing a computational pipeline. Kaiyuan Song, Honglin Xu, Yi Shi, Xin Zou*, Lin-Tai Da*, Jie Hao*, Int. J. Biol. Macromol. 2024, 282: 136502.

Meet Our Team

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Lin-Tai Da

Group Leader

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Si-Yuan Li

PhD Student

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Rui-Cheng Qi

PhD Student

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Han-Chen Zhu

PhD Student

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Wan-Xiang Yi
Master Student

Ready to Explore Breakthroughs Together?

Contact us today to discuss how we can collaborate and advance your research in Computational Biology.

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