Deep Learning in Structural Biology and Protein Design: How, Where, and Why

Chloe Hsu (UC Berkeley)
Deep Learning Theory Workshop and Summer School

Tutorial: Deep Learning Applications in Structural Biology and Protein Engineering

Abstract: There are about 20,000 different proteins in each one of us, humans. These proteins carry out a diverse set of functions to keep us all alive and healthy. Recently, deep learning has been increasingly used to both 1) help us visualize and gain insights into naturally existing proteins and 2) design novel proteins for therapeutic and environmental applications. In this talk, we will take a deep dive into the inner workings of AlphaFold2 and other emerging deep learning methods in structural biology and protein design. We will also examine the assumptions on biological data distributions and discuss hypotheses for the crucial ingredients of successful deep learning applications.

[bhavyahshree]

Amazing! It was so insightful for me to hear your talk as a high schooler currently (trying!) to use machine learning in her own protein design project!

[brandoncharles]

I'm considering whether to do a PhD in Computational & Data-Driven Structural Approaches to Drug Discovery, and this proves very useful in providing a background of the field of structural biology as it stands currently.