Author

J. W. Labonte

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

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Biophysics· 3

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Approach:deep learning· 3 Approach:statistical model· 3 Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Organism:human· 1 Research Focus:protein design· 1 Research Focus:protein folding & dynamics· 1 Assay:proteomics· 1

Frequent Co-Authors

J. J. Gray· 3 shared J. R. Jeliazkov· 2 shared A. Leaver-Fay· 1 shared B. Kuhlman· 1 shared D. Baker· 1 shared F. P. DiMaio· 1 shared H. Park· 1 shared J. H. Lubin· 1 shared

Activity by Year

2017-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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3 shared papersBiophysics

J. J. Gray

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3 papers

Recent·Most cited

Structural basis for peptide substrate specificities of glycosyltransferase GalNAc-T2

S. P. Mahajan, Y. Srinivasan, J. W. Labonte, M. P. DeLisa, J. J. Gray

This study identifies sequence and structural motifs that determine peptide substrate specificity for GalNAc-T2, revealing key residues and conformations that influence glycosylation efficiency.

bioRxiv · Jun 25, 2020Biophysics

Novel sampling strategies and a coarse-grained score function for docking homomers, flexible heteromers, and oligosaccharides using Rosetta in CAPRI Rounds 37-45

S. S. Roy Burman, M. L. Nance, J. R. Jeliazkov, J. W. Labonte, J. H. Lubin, N. Biswas, J. J. Gray

The paper improves Rosetta docking methods for complex targets in CAPRI Rounds 37-45, achieving successful predictions and refining models for symmetric and carbohydrate-containing complexes.

bioRxiv · Nov 3, 2019Biophysics

The Rosetta all-atom energy function for macromolecular modeling and design

R. F. Alford, A. Leaver-Fay, J. R. Jeliazkov, M. J. O'Meara, F. P. DiMaio, H. Park, M. V. Shapovalov, P. D. Renfrew, V. K. Mulligan, K. Kappel, J. W. Labonte, M. S. Pacella, R. Bonneau, P. Bradley, R. L. Dunbrack, , J. J. Gray

The paper explains the Rosetta all-atom energy function, its mathematical models, and its application to biomolecular modeling and design, including new capabilities for membrane proteins and other macromolecules.

bioRxiv · Feb 7, 2017Biophysics