On the afternoon of April 18, 2024, the 5th seminar of the “AI for Ecology and Environment” Academic Week was held in Conference Room 119 of the School of Environment (SOE), Tsinghua University. This event is a part of a series of academic activities organized in celebration of the SOE’s 40th anniversary. Researcher Wang Zheng, head of research on AI for Science of Alibaba Cloud Apsara Lab, was invited to give a speech on “AI-Driven Drug Discovery: Exploration and Application of AI for Science”. In his speech, Wang went into details about the application of AI in drug discovery and demonstrated the latest progress in optimizing drug screening and molecular docking through AI technologies. Faculties and students from the School of Environment, School of Medicine, and School of Information Science & Technology actively participated in the event. It was presided over by Associate Researcher Li Nan, Associate Director of the Center of AI for Ecology and Environment.
Wang Zheng at Seminar
Wang started with a review of the history of the development of artificial intelligence, from early artificial neurons and the Turing Test to deep learning and recent developments of large models such as GPT and BERT. During his report, Wang mainly focused on the application of AI in drug discovery, including AI-based molecular screening, mechanism analysis of drug effects, as well as design and optimization of new drug molecules. In particular, he demonstrated how potential drug molecules can be identified from ultra-large molecular libraries using virtual screening and molecular docking technologies. He also shared the structure and experimental results of his team’s pre-trained model in the field of small molecules and protein.
Looking ahead, Wang pointed out that although AI technology has shown great potential in drug discovery, many challenges remain to be tackled. Future research needs to focus on improving the interpretability of algorithms and models, and enhancing the combination of experimental data and computational models. In addition, Wang urged efforts to explore more modally unified basic general intelligent models based on current unified basic molecular models.
Wang Zheng reviews the history of the development of AI technology.
In the summary of the seminar, Li Nan pointed out that the importance of interdisciplinary collaboration in future research for breaking the limitations of existing generative AI technologies. The event ended with lively discussions between faculties and students. Participants are all full of anticipation towards the future of AI making drug discovery more automated and intelligent.
Li Nan at the Seminar.
Event venue
