Expanding the Universe of Functional Proteins by Computational Design
Speaker
Bruno Correia
École Polytechnique Fédérale de Lausanne (EPFL)
Time
Venue
Online
Meeting Info
Abstract
Finely orchestrated protein activities are at the heart of the most fundamental cellular processes. The rational and structure-based design of novel functional proteins holds the promise to revolutionize many important aspects in biology, medicine and biotechnology. Computational protein design has led the way in rational protein engineering, however many of the designed proteins have been solely focused on structural accuracy and are completely impaired of function.
I will present my group’s efforts on the development of novel computational approaches to predict and design protein function. Specifically, I will describe a new methodological framework to learn surface patterns displayed in protein structures that can be used to decipher their interactions with other molecules. I will also present a computational strategy to explore de novo protein topologies, aiming to solve prevalent problems in protein design that relate to the lack of optimal structural templates for the design of function. By expanding beyond the known protein structural space, our approaches present new paradigms for the rational design of functional proteins. I will showcase important applications for our computationally designed proteins in the domains of vaccine design, T cell-based therapies, biosensors and synthetic biology.
Ultimately, I anticipate that our research will lead to further improvements in the understanding of protein function and design.
Bio
Throughout my PhD and postdoctoral studies I was trained in world-renowned laboratories and institutions in the United States of America (University of Washington and The Scripps Research Institute). Very early in my scientific career I found out my fascination about protein structure and function. My PhD studies evolved in the direction of immunogen design and vaccine engineering which sparked my interest in the many needs and opportunities in vaccinology and translational research. My efforts resulted in an enlightening piece of work where for the first time, computationally designed immunogens elicited potent neutralizing antibodies. During my postdoctoral studies I joined a chemical biology laboratory at the Scripps Research Institute. In this stage I developed novel chemoproteomics methods for the identification of protein-small molecule interaction sites in complex proteomes. In March 2015, I joined the École Polytechnique Fédérale de Lausanne (EPFL) – Switzerland as a tenure track assistant professor. The focus of my research group is to develop computational tools for protein design with particular emphasis in applying these strategies to immunoengineering (e.g. vaccine and cancer immunotherapy). The activities in my laboratory focus on computational design methods development and experimental characterization of the designed proteins. Our laboratory has been awarded with 2 prestigious research grants from the European Research Council. I have been awarded the Protein Society Young Investigator award, the Latsis foundation award and the Prize in Translational Medical Research from the Fondation Leenaards. This year I was selected to be a fellow at the Radcliffe Institute for advanced studies at the University of Harvard. Lastly, I have been awarded the prize for best teacher of Life sciences in 2019.
Sponsor
Institute of Natural Sciences, Shanghai Jiao Tong University
Shanghai National Center for Applied Mathematics (SJTU Center)
Ministry of Education Key Lab in Scientific and Engineering Computing
This talk is also in PKU-SJTU Joint AI Seminar (PSJAS), and Cross-Disciplinary AI Colloquia of PKU IAI.
PSJAS (PKU-SJTU Joint AI Seminar), jointly hosted by the Institute for Artificial Intelligence, Peking University and the Institute of Natural Sciences, Shanghai Jiao Tong University, is an outstanding lecture series that brings top scientists in Graph Neural Networks and Geometric Deep Learning.
