Author

T. F. Huddy

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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Biochemistry· 2 Biophysics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein design· 2 Approach:experimental assay· 1 Research Focus:protein folding & dynamics· 1 Assay:protein sequence· 1 Assay:protein structure· 1

Frequent Co-Authors

D. Baker· 3 shared A. Courbet· 2 shared A. Kang· 2 shared B. Sankaran· 2 shared J. Dauparas· 2 shared N. Bethel· 2 shared P. J. Y. Leung· 2 shared A. Bera· 1 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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3 shared papersBiochemistry

D. Baker

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Author profile →

3 papers

Recent·Most cited

Directing polymorph specific calcium carbonate formation with de novo protein templates

F. A. Davila Hernandez, B. Jin, H. Pyles, S. Zhang, Z. Wang, T. F. Huddy, C.-L. Chen, J. J. De Yoreo, D. Baker

De novo designed protein templates promote nucleation of nano-calcite and direct its growth by oriented particle attachment.

bioRxiv · Jun 9, 2023Biochemistry

Blueprinting expandable nanomaterials with standardized protein building blocks

T. F. Huddy, Y. Hsia, R. D. Kibler, J. Xu, N. Bethel, D. Nagarajan, R. Redler, P. J. Y. Leung, A. Courbet, E. C. Yang, A. K. Bera, N. Coudray, S. J. Calise, F. A. Davila-Hernandez, C. Weidle, , D. Baker

This paper introduces standardized protein building blocks and geometric design principles to create expandable protein nanomaterials, validated through X-ray crystallography and electron microscopy.

bioRxiv · Jun 9, 2023Biochemistry

Robust deep learning based protein sequence design using ProteinMPNN

J. Dauparas, I. Anishchenko, N. Bennett, H. Bai, R. J. Ragotte, L. F. Milles, B. I. M. Wicky, A. Courbet, R. J. de Haas, N. Bethel, P. J. Y. Leung, T. F. Huddy, S. Pellock, D. Tischer, F. Chan, , D. Baker

A deep learning method for protein sequence design shows high performance in both simulations and experiments, applicable to various design challenges.

bioRxiv · Jun 3, 2022Biophysics