Undergraduate Research & Scholarships

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.

Message To Sponsor

Thank you so much for your support on my project! Your contribution means a lot to me and helps me make important strides in my journey as a student and researcher. I appreciate your generosity and belief in my work.
Profile image of Matthew Liu
Major: Applied Mathematics, Computer Science, Statistics
Mentor: Yun Song
Sponsor: Anselm MPS
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