药学前沿大讲堂654讲
Deep learning-driven prediction of metal-based anticancer complexes
报告人简介:
Dr Maria (Masha) Babak obtained her M.Sc. in chemistry from Higher Chemical College of the Russian Academy of Sciences (2010) in Moscow, where she worked on transition metal organometallic chemistry, mentored by Prof. Dmitry S. Perekalin. She completed her Ph.D in bioinorganic chemistry at the University of Vienna (2014), mentored by Prof. Bernhard K. Keppler and Prof. Christian G. Hartinger. In 2015-2020 Dr Babak worked as a postdoctoral research fellow at National University of Singapore, mentored by Prof. Wee Han Ang, where she developed a true passion for drug discovery and drug target identification. In 2019 Dr Babak joined the High Impact Cancer Research Program at Harvard Medical School in Boston. In November 2020, she was appointed as an assistant professor at City University of Hong Kong. Dr Babak is a board member of the Institute of Cancer and Crisis, which aims to mitigate the impact of crisis on cancer patients.Prof. Babak’s research interests lie at the interface of chemistry, biology and medicine and focus on the discovery and preclinical development of anticancer drugs for resistant and aggressive cancers with limited treatment options, e.g. malignant pleural mesothelioma or brain metastases. This work is organized into three cutting-edge directions. The first direction focuses on developing novel immunogenic cell death (ICD) inducers (Babak and Ang et al. Angew. Chem. Int. Ed., 2021; JACS, 2024; JACS, 2025). These agents are specifically designed to not only kill cancer cells but also to activate the patient's own immune system against the tumor. The second direction explores the bidirectional relationship between anticancer drugs and the host microbiome (Babak et al., PNAS, 2025). The third direction leverages AI-assisted metal-based drug discovery (Chemrxiv, 2025). The research group of Prof. Babak developed the first deep learning model for the de novo prediction of metal-based anticancer complexes.


