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Sophia Tan
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NSF GRFP - Computational Protein Design
Open Date: 2018-01-01
Close Date: 2023-01-01
Articles (8)
Year:
2026
Year:
2026
Year:
2026
Year:
2025
The de novo design of small molecule–binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase–1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule–binding proteins with tuned interaction energies is feasible entirely from computation.
Year:
2024
Year:
2024
Year:
2024
Year:
2023
Collaborators (9)
Nick Paras
Professor
University of California, San Francisco
Carlo Condello
Assistant Professor
University of California, San Francisco
Hyunjun Yang
Assistant Professor
Brandeis University
William F. DeGrado
Professor
University of California
Samuel Mann
Assistant Professor
University of California, Riverside
Gregory Merz
Adjunct Assistant Professor
University of California, San Francisco
Nicholas Polizzi
Independent Investigator
Harvard Medical School
Hyunil Jo
Adjunct Professor
University of California, San Francisco
Jesús Valdiviezo
Broad Institute
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