Author

Simon K. S. Chu

Nvidia (United States)ORCID 0009-0009-8405-8544Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:protein sequence· 2 Approach:deep learning· 1 Approach:large language model· 1 Research Focus:protein design· 1 Research Focus:protein folding & dynamics· 1 Approach:transformer / foundation model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Justin B. SiegeliD· 2 shared Alexander J. KehliD· 1 shared Jennifer Lee· 1 shared Jose Henrique PereiraiD· 1 shared Kush Narang· 1 shared Michael GigliD· 1 shared Patrick M. ShihiD· 1 shared Paul D. AdamsiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 29 mutual co-author links

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2 shared papersBiochemistry

Justin B. SiegelORCID

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2 papers

Recent·Most cited

BiochemistrybioRxivPreprintSep 9, 2026

De novo Rubisco design with protein language models

Alexander J. Kehl, Simon K. S. Chu, Jose Henrique Pereira…·Justin B. Siegel

This paper designs novel Rubisco variants using protein language models, identifying active candidates with improved CO2/O2 specificity and structural validity.

DOI 10.64898/2026.09.04.749267

protein sequencelarge language model

𝕏 PostBluesky

BiophysicsbioRxivNov 19, 2023

Protein Stability Prediction by Fine-tuning a Protein Language Model on a Mega-scale Dataset

Simon K. S. Chu, Kush Narang, Justin B. Siegel

This paper fine-tunes a protein language model on a large dataset to predict protein folding stability, showing reasonable performance on small domains but limitations in generalizing to larger scaffolds.

DOI 10.1371/journal.pcbi.1012248

protein sequencedeep learning

𝕏 PostBluesky