Author

Sungwon Jung

Howard Hughes Medical InstituteORCID 0009-0007-6284-2106Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:protein folding & dynamics· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Kevan M. ShokatiD· 2 shared D. Matthew PeacockiD· 1 shared Gregory B. CraveniD· 1 shared Jack TauntoniD· 1 shared Joshua B. CombsiD· 1 shared Qinheng ZhengiD· 1 shared Sang M. Le· 1 shared Y Chen· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 22 mutual co-author links

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2 shared papersCancer Biology

Kevan M. ShokatORCID

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2 papers

Recent·Most cited

Cancer BiologyJournal of the American Chemical SocietyPeer-reviewedJul 9, 2026

Benzoxaboroles are structurally unique binders of eukaryotic translation initiation factor 4E

Joshua B. Combs, D. Matthew Peacock, Gregory B. Craven…·Kevan M. Shokat

The paper identifies benzoxaboroles as selective binders of eIF4E, revealing stereoselective interactions and structural insights into their binding mechanism.

DOI 10.1021/jacs.6c04291

proteomicsexperimental assay

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BioinformaticsIUBMB LifePeer-reviewedJun 1, 2026

Single-sequence deep learning delivers crystal-quality models of covalent K-Ras G12 hotspot complexes

Sungwon Jung, Qinheng Zheng, Kevan M. Shokat

The paper demonstrates that Chai-1, a deep learning tool, can accurately predict covalent K-Ras(G12C) complexes using single sequences without multiple sequence alignments.

1 citation

protein structuredeep learning

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