Professor
Molecular Physiology and Biophysics
Director Center of Applied AI in Protein Dynamics
Vanderbilt University
Title: Dawn of a new age in mechanistic structural biology of active transporters
Abstract: AlphaFold2 has revolutionized the field of protein structure prediction. Long considered the holy grail of the protein folding problem, the decoding of the sequence structure relationship emerged from the training of a deep learning neural network model on the wealth of protein sequences and high resolutions structures. Its performance notwithstanding, the success of AF2 belied a fundamental limitation. the perceived assumption that an input sequence is associated with a single structural model. The latter ignores the rugged conformational landscape of protein in the folded state. The meandering of proteins between conformations, driven by thermal energy, or the triggered large-scale conformational changes underpin biological function. We have methods to “coerce” AF2 to generate multiple conformations or protein ensembles. I will describe the nature of AF2 ensembles and present integrated approaches to iteratively test and refine these models.
Host: John Hunt
