SKM 2021 – wissenschaftliches Programm

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DY: Fachverband Dynamik und Statistische Physik

DY 17: Theory and Simulation (joint session CPP/DY)

DY 17.1: Hauptvortrag

Freitag, 1. Oktober 2021, 13:30–14:00, H3

Data-driven protein design and simulation — •Andrew Ferguson — University of Chicago, Chicago, IL, USA

Data-driven modeling and deep learning present powerful tools that are opening up new paradigms and opportunities in the understanding, discovery, and design of soft and biological materials. In this talk, I will first describe an approach integrating ideas from dynamical systems theory, nonlinear manifold learning, and deep learning to reconstruct protein folding funnels and molecular structures from one-dimensional time series in experimentally measurable observables obtainable by single molecule FRET. I will then describe our recent development and application of deep representational learning to expose the sequence-function relationship within homologous protein families and to use these principles for data-driven design of synthetic proteins with new and/or elevated function.