题 目:New methods for RNA computational biology
Curators’ Distinguished Professor of Biophysics, Biochemistry, and Data Science & Informatics at the University of Missouri-Columbia.
时 间: 5月17日（周一）上午9:00-10:00
地 点: Online (Zoom会议)
会议号：627 9242 4126
Ribonucleic acid (RNA) molecules play spectacularly versatile roles in living cells. Emerging biomedical advances such as precision medicine and synthetic biology point to RNA as the central regulator and information carrier. We are interested in predicting RNA structure, stability, and kinetics from the nucleotide sequence, and the design of molecules for therapeutic applications. For example, given the limited availability of crystal/NMR structures, how to build the native fold from the sequence? For a given RNA target, how to predict RNA-small molecule interactions and identify small molecules as potential drugs? Using physical and chemical principles, we recently developed IsRNA for RNA 3D structure prediction and RLDock for RNA-small molecule interactions. I will describe these new approaches and the proof of principles in RNA 3D structure prediction and in predicting RNA-small molecule binding.
Shi-Jie Chen is a Curators’ Distinguished Professor of Biophysics, Biochemistry, and Data Science & Informatics at the University of Missouri-Columbia. Chen received a B.S. degree from Zhejiang University. Through T.D. Lee's CUSPEA program, he entered the graduate school of the University of California, San Diego where he received a PhD in Physics with Daniel Dubin. He did postdoctoral research with Ken Dill at the University of California, San Francisco. He was elected a Fellow of the American Physical Society (APS) in 2013 and a Fellow of the American Association for the Advancement of Science (AAAS) in 2018. He is a Founding Council Member of the International Society of RNA Nanotechnology and Nanomedicine and an Advisory Board member for Clinical and Translational Medicine. He serves as an Associate Editor for PLoS Computational Biology and other scientific journals. Chen studies computational biology of RNA folding and therapeutics. He is known for his work on RNA structure prediction, modeling of RNA folding stability, kinetics, and metal ion effects, and computational design of RNA-targeted drugs, RNA aptamer, RNA-based nanomedicine, and CRISPR gene editing systems.