Amy E. Keating

Amy E. Keating

Jay A. Stein (1968) Professor of Biology; Professor of Biological Engineering; Department Head

Amy E. Keating determines how proteins make specific interactions with one another and designs new, synthetic protein-protein interactions.





Building 68 - Koch Biology Building


Keith Murray



Assistant Phone


  • PhD, 1998, University of California, Los Angeles
  • SB, 1992, Physics, Harvard University

Research Summary

Our goal is to understand, at a high level of detail, how the interaction properties of proteins are encoded in their sequences and structures. We investigate protein-protein interactions by integrating data from high throughput assays, structural modeling, and bioinformatics with biochemical and biophysical experiments. Much of our work focuses on α-helical coiled-coil proteins, Bcl-2 apoptosis-regulating proteins, and protein domains that bind to short linear motifs.

Recent Publications

  1. Elaboration of the Homer1 recognition landscape reveals incomplete divergence of paralogous EVH1 domains. Singer, A, Ramos, A, Keating, AE. 2024. Protein Sci 33, e5094.
    doi: 10.1002/pro.5094PMID:38989636
  2. High-throughput computational discovery of inhibitory protein fragments with AlphaFold. Savinov, A, Swanson, S, Keating, AE, Li, GW. 2023. bioRxiv , .
    doi: 10.1101/2023.12.19.572389PMID:38187731
  3. Marginal specificity in protein interactions constrains evolution of a paralogous family. Ghose, DA, Przydzial, KE, Mahoney, EM, Keating, AE, Laub, MT. 2023. Proc Natl Acad Sci U S A 120, e2221163120.
    doi: 10.1073/pnas.2221163120PMID:37098061
  4. Peptides from human BNIP5 and PXT1 and non-native binders of pro-apoptotic BAK can directly activate or inhibit BAK-mediated membrane permeabilization. Aguilar, F, Yu, S, Grant, RA, Swanson, S, Ghose, D, Su, BG, Sarosiek, KA, Keating, AE. 2023. Structure 31, 265-281.e7.
    doi: 10.1016/j.str.2023.01.001PMID:36706751
  5. Neural network-derived Potts models for structure-based protein design using backbone atomic coordinates and tertiary motifs. Li, AJ, Lu, M, Desta, I, Sundar, V, Grigoryan, G, Keating, AE. 2023. Protein Sci 32, e4554.
    doi: 10.1002/pro.4554PMID:36564857
  6. Tertiary motifs as building blocks for the design of protein-binding peptides. Swanson, S, Sivaraman, V, Grigoryan, G, Keating, AE. 2022. Protein Sci 31, e4322.
    doi: 10.1002/pro.4322PMID:35634780
  7. Native proline-rich motifs exploit sequence context to target actin-remodeling Ena/VASP protein ENAH. Hwang, T, Parker, SS, Hill, SM, Grant, RA, Ilunga, MW, Sivaraman, V, Mouneimne, G, Keating, AE. 2022. Elife 11, .
    doi: 10.7554/eLife.70680PMID:35076015
  8. A distributed residue network permits conformational binding specificity in a conserved family of actin remodelers. Hwang, T, Parker, SS, Hill, SM, Ilunga, MW, Grant, RA, Mouneimne, G, Keating, AE. 2021. Elife 10, .
    doi: 10.7554/eLife.70601PMID:34854809
  9. Spatial Multiplexing of Fluorescent Reporters for Imaging Signaling Network Dynamics. Linghu, C, Johnson, SL, Valdes, PA, Shemesh, OA, Park, WM, Park, D, Piatkevich, KD, Wassie, AT, Liu, Y, An, B et al.. 2020. Cell 183, 1682-1698.e24.
    doi: 10.1016/j.cell.2020.10.035PMID:33232692
  10. Precision Calcium Imaging of Dense Neural Populations via a Cell-Body-Targeted Calcium Indicator. Shemesh, OA, Linghu, C, Piatkevich, KD, Goodwin, D, Celiker, OT, Gritton, HJ, Romano, MF, Gao, R, Yu, CJ, Tseng, HA et al.. 2020. Neuron 107, 470-486.e11.
    doi: 10.1016/j.neuron.2020.05.029PMID:32592656
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