Author

Yibing Wu

University of California, San Francisco

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Biology Disciplines

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Biochemistry· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein design· 2 Assay:protein sequence· 2 Research Focus:drug response / drug discovery· 1 Approach:large language model· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

William F. DeGradoiD· 2 shared A. Katherine HatstatiD· 1 shared Hyunil JoiD· 1 shared Julia M. ShifmaniD· 1 shared Nam Hyeong KimiD· 1 shared Sagara N.S. Gurusinghe· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 9 mutual co-author links

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2 shared papersBiochemistry

William F. DeGradoORCID

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2 papers

Recent·Most cited

De novo design of ligand binding proteins using large language models alone

Nam Hyeong Kim, A. Katherine Hatstat, Hyunil Jo, Yibing Wu, William F. DeGrado

This paper demonstrates that large language models can generate de novo protein sequences that bind specific ligands without copying existing sequences, with a 25% hit rate in experimental validation.

bioRxiv · Sep 3, 2026 · PreprintBiochemistry

ProBASS: a language model with sequence and structural features for predicting the effect of mutations on binding affinity

Sagara N.S. Gurusinghe, Yibing Wu, William F. DeGrado, Julia M. Shifman

ProBASS predicts mutation effects on PPI binding affinity using sequence and structural features from ESM2 and ESM-IF1, achieving high correlation with experimental data.

Bioinformatics · May 1, 2025Peer-reviewedBioinformatics