Bai Lab(Drug Design Lab)
Creating an efficient drug design framework by combining state-of-the-art computational methods with chemical biology technologies.
Research in the Bai Group aims to create an efficient drug design framework by combining state-of-the-art computational drug design methods with chemical biology technologies.
We are particularly interested in developing new computational biology and drug design methods by introducing artificial intelligence algorithms, such as protein-protein interaction prediction, peptide design, molecular degrader design, and selective covalent inhibitor design. Using these methods, we explore the molecular mechanisms involved in the development of serious diseases, such as cancer, infectious diseases, and metabolic diseases, and develop therapeutic agents accordingly.
To date, we have developed a number of computational drug design programs, most of which are freely available on our website for academic use. Using these methods, we have successfully designed several highly bioactive compounds or peptides. Some of them are being studied in detail in preclinical phases.
Key Research Areas
Protein–Protein Interaction Prediction
Deep learning methods to predict and characterize PPIs, enabling rational design of peptide and small-molecule modulators.
Molecular Degrader Design
AI-driven design of PROTACs and molecular glues for targeted protein degradation in cancer and other diseases.
Drug–Target Affinity Prediction
Deep learning models for accurate binding affinity prediction, enabling large-scale virtual screening and drug repurposing.
Selective Covalent Inhibitor Design
Computational methods for designing selective covalent inhibitors targeting disease-relevant proteins.
Fang Bai, Ph.D.
Principal InvestigatorAssociate Professor, School of Life Science and Technology; Research Professor, Shanghai Institute for Advanced Immunochemical Studies; Visiting Professor, School of Information Science and Technology, ShanghaiTech University.
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Acknowledgement
The Bai Lab is supported by the National Natural Science Foundation of China, the Ministry of Science and Technology, the Shanghai Science and Technology Commission, the Shanghai Science and Technology Development Funds, and the Start-up Package of ShanghaiTech University. Most computational drug design programs developed in our lab are freely available for academic use.