Matthew Liu L&S Math & Physical Sciences
Deep structure-based models for protein evolution
Understanding how and why proteins evolve is vital to grasping the fundamental biological processes governing everything from disease treatment to evolutionary biology. Classical sequence-based models of protein evolution make unrealistic assumptions ignoring behavior like coevolution of amino acids, which limits their explanatory power. Capturing such complex interactions requires a deep understanding of protein structure and how sites interact. To do this, my project introduces the first structure-based model of its kind for protein evolution, adapting models from protein design to contribute to a novel literature on deep models of protein evolution. I plan to design and implement a graph-attention model to predict evolutionary transitions by combining 1D sequence information with 3D structure information like bonding angles and site-site interactions. I then hope to investigate its effectiveness in downstream applications like variant effect prediction and ancestral sequence reconstruction.