Talk / Overview
Proteins play a crucial role in every form of life. The function of proteins is largely determined by their 3D structure and the way they interact with other molecules. Understanding the mechanisms that govern protein structure and their interactions with other molecules is a holy grail of biology that also paves the path to ground-breaking new applications in biotechnology and medicine. Over the past three decades, large amounts of structural data on proteins has been made available to the wide-scientific community. This has created opportunities for machine learning (ML) approaches to improve our ability to better understand the governing principles of these molecules, as well as to develop computational approaches for the design of novel proteins and small molecules drugs. The three-dimensional structures of proteins and molecular objects are a natural fit for Geometric Deep Learning (GDL). In this talk I will showcase ML frameworks for protein representation which we have leveraged for the decoding of protein functional features and for the design of novel artificial proteins.