Author

D. Vafeados

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 Bioengineering· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 4 Research Focus:protein design· 3 Assay:protein structure· 3 Research Focus:benchmarking· 2 Research Focus:drug response / drug discovery· 2 Approach:transformer / foundation model· 2 Approach:diffusion model· 1 Approach:experimental assay· 1

Frequent Co-Authors

D. Baker· 4 shared I. Goreshnik· 3 shared B. Coventry· 2 shared B. Huang· 2 shared F. DiMaio· 2 shared G. R. Lee· 2 shared I. Anishchenko· 2 shared J. Dauparas· 2 shared

Activity by Year

2022-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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4 shared papersBioengineering

D. Baker

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Author profile →

4 papers

Recent·Most cited

Atomically accurate de novo design of antibodies with RFdiffusion

N. R. Bennett, J. L. Watson, R. J. Ragotte, A. J. Borst, D. L. See, C. Weidle, R. Biswas, Y. Yu, E. L. Shrock, R. Ault, P. J. Y. Leung, B. Huang, I. Goreshnik, J. Tam, K. D. Carr, , D. Baker

This paper designs antibodies de novo with atomic precision using RFdiffusion and yeast display, validated by cryo-EM and biophysical methods.

bioRxiv · Mar 14, 2024Bioengineering

Small-molecule binding and sensing with a designed protein family

G. R. Lee, S. J. Pellock, C. Norn, D. Tischer, J. Dauparas, I. Anishchenko, J. A. M. Mercer, A. Kang, A. Bera, H. Nguyen, I. Goreshnik, D. Vafeados, N. Roullier, H. L. Han, B. Coventry, , D. Baker

This paper designs a protein family that binds and senses small molecules using deep learning and physics-based methods, achieving nanomolar sensitivity for cortisol.

bioRxiv · Nov 1, 2023Biochemistry

Generalized Biomolecular Modeling and Design with RoseTTAFold All-Atom

R. Krishna, J. Wang, W. Ahern, P. Sturmfels, P. Venkatesh, I. Kalvet, G. R. Lee, F. S. Morey-Burrows, I. Anishchenko, I. R. Humphreys, R. McHugh, D. Vafeados, X. Li, G. A. Sutherland, A. Hitchcock, , D. Baker

This paper introduces RFAA and RFdiffusionAA, models that can predict and design complex biomolecular assemblies including proteins, nucleic acids, small molecules, and covalent modifications.

bioRxiv · Oct 9, 2023Biochemistry

Improving de novo Protein Binder Design with Deep Learning

N. Bennett, B. Coventry, I. Goreshnik, B. Huang, A. Allen, D. Vafeados, Y. P. Peng, J. Dauparas, M. Baek, L. Stewart, F. DiMaio, S. De Munck, S. Savvides, D. Baker

This paper improves de novo protein binder design by using deep learning models to assess design success rates and computational efficiency.

bioRxiv · Jun 15, 2022Bioengineering