Keating Lab
@keating_lab
We use computational and experimental methods to study protein structure, function, and interactions at @MITBiology @MITBE
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A self-supervised approach aligning protein sequence and structure spaces enables efficient binder screening with only backbone structural information — a powerful asset for early-stage protein binder design. 🔗 go.aps.org/3UY7OVe
First twitter thread🧵and also my first BioRxiv preprint! I’m excited to finally release my undergrad work into the world: combining GNNs, Potts models, and Tertiary Motifs (TERMs) for protein design! See the preprint here: biorxiv.org/content/10.110… 1/
Our first keynote speaker: Dr. Amy Keating (@keating_lab). Interested in protein interaction specificity, Dr. Keating highlights the power of data-driven computational exploration of protein interactions. Dr. Keating was our student choice of #PEC2022 and we are ecstatc to host!
Fast, reliable, computational methods for designing protein-binding peptides would be immensely useful. As a first step, we show that tertiary structural motifs from the PDB can be used to reconstruct known peptide structures and generate new ones. doi.org/10.1002/pro.43… (1/9)
Scientists in @keating_lab designed a screening method to probe how short stretches of amino acids called SLiMs selectively bind to certain proteins, and distinguish between binding partners with similar structures. I covered this recent work for MIT News: bit.ly/3B4piEb
Excited to share our newest work! We describe a surprising mechanism behind how a short linear motif binding domain achieves interaction specificity. elifesciences.org/articles/70601
Review of data-driven protein design, including structure, sequences, and high-throughput functional datasets. Vincent Frappier @KeatingLab sciencedirect.com/science/articl…
Read about the amazing accomplishments of alum MIT biologist and president of The Protein Society, Prof. Amy Keating (PhD ’98 Houk/García-Garibay groups) bit.ly/3w0kA7O @houk1000 @GaribayLab @MITBiology @ProteinSociety
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