Author

J. Holmes

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· 1 Biophysics· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Approach:Bayesian inference· 1 Assay:clinical cohort / trial· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

A. J. Warren· 1 shared A. Klein· 1 shared B. D. Bax· 1 shared D. Warrell· 1 shared E. A. Ashley· 1 shared E. Mahenthiralingam· 1 shared F. Smithuis· 1 shared H. Morgan· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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1 shared paperBiophysics

A. J. Warren

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3 papers

Recent·Most cited

A 2.8A structure of zoliflodacin in a DNA-cleavage complex with Staphylococcus aureus DNA gyrase

H. Morgan, M. Lipka-Lloyd, A. J. Warren, N. Hughes, J. Holmes, N. P. Burton, E. Mahenthiralingam, B. D. Bax

This paper reports the 2.8Å X-ray structure of zoliflodacin bound to Staphylococcus aureus DNA gyrase, showing its mechanism of DNA cleavage inhibition and improved antibacterial activity.

bioRxiv · Nov 30, 2022 · PreprintBiophysics

Residue-specific insights into (2x)72 kDa tryptophan synthase obtained from fast-MAS 1H-detected solid-state NMR

A. Klein, P. Rovó, V. V. Sakhrani, Y. Wang, J. Holmes, V. Liu, P. Skowronek, L. Kukuk, S. K. Vasa, P. Güntert, L. J. Mueller, R. Linser

This study uses solid-state NMR to characterize a 72 kDa tryptophan synthase, overcoming size limitations and providing insights into catalytic residues.

bioRxiv · May 12, 2021 · PreprintBiochemistry

A Bayesian phase 2 model based adaptive design to optimise antivenom dosing: application to a dose-finding trial for a novel Russell's viper antivenom in Myanmar

J. A. Watson, T. Lamb, J. Holmes, D. Warrell, K. T. Thwin, Z. L. Aung, M. T. Nwe, F. Smithuis, E. A. Ashley

This paper proposes a Bayesian adaptive design for antivenom dose-finding trials, showing it can identify optimal doses with fewer patients than traditional methods.

bioRxiv · Feb 6, 2020Pharmacology & Toxicology