Dr ADITI BORKAR Aditi.Borkar@nottingham.ac.uk
ASSISTANT PROFESSOR IN MOLECULARBIOCHEMISTRY & BIOPHYSICS
AUTOBA: automation of backbone assignment from HN(C)N suite of experiments.
Borkar, Aditi; Kumar, Dinesh; Hosur, Ramakrishna V.
Authors
Dinesh Kumar
Ramakrishna V. Hosur
Abstract
Development of efficient strategies and automation represent important milestones of progress in rapid structure determination efforts in proteomics research. In this context, we present here an efficient algorithm named as AUTOBA (Automatic Backbone Assignment) designed to automate the assignment protocol based on HN(C)N suite of experiments. Depending upon the spectral dispersion, the user can record 2D or 3D versions of the experiments for assignment. The algorithm uses as inputs: (i) protein primary sequence and (ii) peak-lists from user defined HN(C)N suite of experiments. In the end, one gets HN, 15N, Cα and C′ assignments (in common BMRB format) for the individual residues along the polypeptide chain. The success of the algorithm has been demonstrated, not only with experimental spectra recorded on two small globular proteins: ubiquitin (76 aa) and M-crystallin (85 aa), but also with simulated spectra of 27 other proteins using assignment data from the BMRB.
Citation
Borkar, A., Kumar, D., & Hosur, R. V. (2011). AUTOBA: automation of backbone assignment from HN(C)N suite of experiments. Journal of Biomolecular NMR, 50, 285–297. https://doi.org/10.1007/s10858-011-9518-0
Journal Article Type | Article |
---|---|
Acceptance Date | May 12, 2011 |
Online Publication Date | May 29, 2011 |
Publication Date | May 29, 2011 |
Deposit Date | Jan 29, 2025 |
Journal | Journal of biomolecular NMR |
Print ISSN | 0925-2738 |
Electronic ISSN | 1573-5001 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 50 |
Pages | 285–297 |
DOI | https://doi.org/10.1007/s10858-011-9518-0 |
Keywords | Structural proteomics, HN(C)N, Backbone assignment, Start points, Checkpoints, Automated assignment, AUTOBA |
Public URL | https://nottingham-repository.worktribe.com/output/43946026 |
Publisher URL | https://link.springer.com/article/10.1007/s10858-011-9518-0 |
PMID | 21626212 |
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