Author

Pengkang Guo

École Polytechnique Fédérale de Lausanne

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:graph neural network· 1 Research Focus:protein design· 1 Assay:protein sequence· 1

Frequent Co-Authors

Bruno E. CorreiaiD· 1 shared Charlie Huh· 1 shared Daniel ProbstiD· 1 shared Jihang Chen· 1 shared Jing‐Ke WengiD· 1 shared Pierre VandergheynstiD· 1 shared Seonghwan SeoiD· 1 shared Songlin Jiang· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

Bruno E. CorreiaORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 2, 2026

Elucidating enzyme-substrate specificity through co-folding foundation model

Xiwei Cheng, Seonghwan Seo, Charlie Huh…·Wengong Jin

This paper introduces Boltz2ESI, a framework predicting enzyme-substrate interactions using a foundation model, outperforming existing methods by capturing active-site plasticity and evolutionary context.

DOI 10.64898/2026.07.30.741672

protein structureprotein sequence

𝕏 PostBluesky

BioinformaticsbioRxivPreprintFeb 4, 2025

Boosting protein graph representations through static-dynamic fusion

Pengkang Guo, Bruno E. Correia, Pierre Vandergheynst, Daniel Probst

The paper introduces a graph representation that combines static and dynamic protein data, improving performance in three tasks related to protein-ligand interactions.

3 citations

protein structuregraph neural network

𝕏 PostBluesky