Abstract Protein dynamics are fundamental to protein function and encode complex biomolecular mechanisms. Although Markov state models have made it possible to capture long-timescale protein conformational changes, many systems are still beyond their reach. In this lecture, the speaker will explore how incorporating dynamics memory (i.e., non-Markovian effects) into machine learning models can significantly reduce the computational cost of predicting long-time dynamics in these complex systems with high accuracy. First, the speaker will introduce the integrative-generalized master equation (IGME) method, which encodes non-Markovian dynamics through time-integrated memory kernels. Using IGME, his research team predicts multiple protein-protein interactions (PPIs) between KRAS and VHL, establishing a new workflow for PROTAC linker design in targeted protein degradation. One of the predictions matches well with the co-crystal structure, while these non-canonical PPIs remain challenging for AlphaFold3 to predict. Next, the speaker will present MEMnets, a deep-learning approach for identifying the slow collective variables (CVs) of protein dynamics. Unlike conventional deep learning models like VAMPnets, which assume Markovian dynamics, MEMnets builds on IGME theory with a novel loss function that minimizes the time integration of memory kernels. His research team demonstrates that MEMnets-derived CVs elucidate the molecular mechanisms behind the loading gate opening of bacterial RNA Polymerase (RNAP), revealing a transiently open cryptic pocket that binds the antibiotic Myx. Finally, the speaker will introduce the TS-DART method, which automatically identifies transition states (TS) across multiple free energy barriers in biomolecular systems. Inspired by Trustworthy AI, TS-DART detects TS as out-of-distribution data in a hyperspherical latent space. Using TS-DART, his research team successfully shows how antibiotic binding shifts the transition state, inhibiting bacterial RNAP elongation.   About the Speaker Prof. HUANG Xuhui obtained his Ph.D. from Columbia University in 2006 with Prof. Bruce BERNE. He did his postdoc research at Stanford University with Profs. Michael LEVITT and Vijay PANDE. He was an Assistant, Associate and Full Professor at The Hong Kong University of Science and Technology (HKUST) between 2010 and Summer 2021. Since Fall 2021, Prof. Huang took up the position of the Hirschfelder Endowed Chair Professor in Theoretical Chemistry, and Director of Theoretical Chemistry Institute at University of Wisconsin-Madison. He has received numerous awards, including the Theory & Computation Award for Mid-Career Scientists from Biophysical Society in 2023, Pople Medal from the Asia-Pacific Association of Theoretical and Computational Chemists in 2021, American Chemical Society OpenEye Outstanding Junior Faculty Award in 2014, and Hong Kong Research Grant Council Early Career Award in 2013. He is a founding member of The Hong Kong Young Academy of Sciences (YASHK) and a Fellow of The Royal Society of Chemistry (FRSC). His group pioneered in elucidating the dynamics of protein conformational changes by developing statistical-mechanics-based methods and machine learning tools.   For Attendees' Attention Seating is on a first come, first served basis.

INTRODUCTION The Molecular Frontiers Symposium, organized by the globally renowned Molecular Frontiers Foundation - founded by the Royal Swedish Academy of Sciences is recognized as one of the most influential scientific organizations worldwide. For the first time in the organization’s history, the Foundation's annual flagship symposium will be held in Greater China, hosted at The Hong Kong University of Science and Technology. With the theme "Frontiers of New Knowledge in Science", the Symposium will bring together more than 30 top molecular scientists from around the globe, including 4 Nobel Prize laureates, with the aim of advancing cutting-edge molecular science research and facilitating interaction between scientific elites and the public.   ABOUT THE PROGRAM The 3-day symposium consists of more than 20 inspirational lectures by esteemed international speakers on the topic of molecules. Click here for the full program with speakers’ and sessions details.    Speakers / Performers: Stefan Hell Max Planck Institute Nobel Prize in Chemistry laureate in 2014. German expert in optical microscopy at the Max Planck Institute.  Tim Hunt The Royal Society Nobel Prize in Physiology or Medicine laureate in 2001. Fellow of the Royal Society, British biologist, expert in cancer and cell cycle research.  K. Barry Sharpless The Scripps Research Institute American chemist at The Scripps Research Institute, inventor of click chemistry reactions; awarded the Nobel Prize in Chemistry in 2001 for his work in chiral catalytic oxidation reactions; and again received the Nobel Prize in Chemistry in 2022 for the development of click chemistry and bioorthogonal chemistry. Sir Gregory Winter University of Cambridge Nobel Prize in Chemistry laureate in 2018. Professor at the University of Cambridge, Fellow of the Royal Society, expert in the field of antibody engineering, harnessing protein engineering techniques to develop biopharmaceuticals,  Nancy Ip The Hong Kong University of Science and Technology A distinguished neuroscientist and Member of the Chinese Academy of Sciences, the US National Academy of Sciences, the American Academy of Arts and Sciences, the World Academy of Sciences, the Chinese Academy of Medical Sciences, and the Hong Kong Academy of Sciences.   Full list of speakers and more information: click here   ENQUIRY Email: mfshk2024@ust.hk Seating: On a first come, first reserved basis.

Abstract After introducing some basic notions in the representation theory of classical Lie groups, the speaker will explain three results in this theory: the multiplicity one theorem for classical groups, the conservation relation for local theta correspondence, and the non-vanishing hypothesis at infinity for Rankin-Selberg convolutions. Some relevant or consequent results will also be explained. About the Speaker Prof. SUN Binyong received his bachelor's degree in Mathematics from Zhejiang University in 1999 and his doctorate in Mathematics from the Hong Kong University of Science and Technology in 2004. After a short postdoctoral experience at the ETH Zurich, he returned to China in 2005 and worked at the Academy of Mathematics and Systems Science of the Chinese Academy of Sciences. In 2020, he joined the Institute for Advanced Study in Mathematics at Zhejiang University as a permanent member and is currently a Professor there. Prof. Sun’s research interests include representation theory of Lie groups and the theory of automorphic forms. By proving some long-standing conjectures, he has established several deep and fundamental results for representations of classical groups. Prof. Sun was an invited speaker at the International Congress of Mathematicians in 2022. He received the Tan Kah Kee Young Scientist Award in 2014, the Outstanding Youth Science and Technology Talent Award in 2016, and the State Natural Science Award (second class) in 2018. In 2019, he was elected as a Member of the Chinese Academy of Sciences. He was awarded the 2024 Future Science Prize in Mathematics and Computer Science for his remarkable contributions to the representation theory of Lie groups. For Attendees' Attention Seating is on a first come, first served basis.