GPCR Mechanisms
Understanding activation, signalling, conformational dynamics and ligand recognition at molecular resolution.
Integrating molecular simulation, structural biology and artificial intelligence to understand receptor function and accelerate therapeutic discovery.
A research program connecting receptor biology, computation and translational drug discovery.
Understanding activation, signalling, conformational dynamics and ligand recognition at molecular resolution.
Developing computational and AI approaches for structure-based design, screening and molecular property prediction.
Connecting mechanistic insight with the design and development of novel therapeutic molecules.
Our recent work, which is entitled "Machine learning deciphered molecular mechanistics with accurate kinetic and thermodynamic prediction", has been published in ACS Journal of Chemical Theory and Computation as a cover strory. In this work, an integrated unsupervised dimension reduction model: uniform manifold approximation and projection (UMAP) with hierarchy density-based spatial clustering of applications with noise (HDBSCAN) is implemented, demonstrating robustness in preserving global and local data structures compared to traditional dimension reduction methods in the field of MD analysis area
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Dr. Shuguang Yuan was invited to the 2023 China Artificial Intelligence for Pharma R&D Conference as a keynote speaker. He gave a talk about "Advancing GPCR drug discovery in an ultimately efficient way". He was also the coordinator for both sections of AI drug discovery of small molecules and round table discussions.
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Prof. Renato Zenobi from ETHZ visited the lab of Prof. Yuan. Prof. Zenobi gave a talk about how to use mass spectroscopy to study the interactions between G protein-coupled receptors and their ligands. He also introduced the latest progresses and technology that developed in his lab.
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