Author

A. Courbet

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

Biology Disciplines

Click to filter author papers

Biochemistry· 2 Biophysics· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 3 Research Focus:protein design· 3 Assay:protein structure· 3 Approach:experimental assay· 2 Research Focus:protein folding & dynamics· 1 Assay:protein sequence· 1

Frequent Co-Authors

A. Kang· 4 shared D. Baker· 4 shared A. K. Bera· 3 shared J. Dauparas· 3 shared B. I. M. Wicky· 2 shared B. Sankaran· 2 shared G. Bhabha· 2 shared H. Nguyen· 2 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 42 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

4 shared papersBiochemistry

A. Kang

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

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

Hallucinating protein assemblies

B. I. M. Wicky, L. F. Milles, A. Courbet, R. J. Ragotte, J. Dauparas, E. Kinfu, S. Tipps, R. D. Kibler, M. Baek, F. DiMaio, X. Li, L. Carter, A. Kang, H. Nguyen, A. K. Bera, D. Baker

Deep network-based protein design generates symmetric homo-oligomers with high structural accuracy, demonstrating the potential for creating novel nanomachines and biomaterials.

Science · Oct 7, 2022Peer-reviewedBiophysics

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

Hierarchical design of multi-scale protein complexes by combinatorial assembly of oligomeric helical bundle and repeat protein building blocks

Y. Hsia, R. Mout, W. Sheffler, N. I. Edman, I. Vulovic, Y.-J. Park, R. L. Redler, M. J. Bick, A. K. Bera, A. Courbet, A. Kang, T. Brunette, U. Nattermann, E. Tsai, A. Saleem, , D. Baker

This paper describes a hierarchical method to design multi-scale symmetric protein complexes using repeat proteins and helical bundles, resulting in large symmetric assemblies like an icosahedral nanocage.

bioRxiv · Jul 27, 2020Biochemistry