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Sophia Tan

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University of California, San Francisco
Country flagUnited States

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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

UNITED STATES
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Carlo Condello

Assistant Professor

University of California, San Francisco

UNITED STATES
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Hyunjun Yang

Assistant Professor

Brandeis University

UNITED STATES
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William F. DeGrado

Professor

University of California

UNITED STATES
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Samuel Mann

Assistant Professor

University of California, Riverside

UNITED STATES
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Gregory Merz

Adjunct Assistant Professor

University of California, San Francisco

UNITED STATES
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Nicholas Polizzi

Independent Investigator

Harvard Medical School

UNITED STATES
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Hyunil Jo

Adjunct Professor

University of California, San Francisco

UNITED STATES
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Jesús Valdiviezo

Broad Institute

UNITED STATES
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