Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing
The authors present BARASA, an approach to assign backbone triple resonance spectra of proteins that augments traditional approaches with a Bayesian statistical analysis of the observed chemical shifts. The algorithm employs a simulated annealing engine to establish a consensus set of resonance assi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-37219-z |
| _version_ | 1797864237619478528 |
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| author | Anthony C. Bishop Glorisé Torres-Montalvo Sravya Kotaru Kyle Mimun A. Joshua Wand |
| author_facet | Anthony C. Bishop Glorisé Torres-Montalvo Sravya Kotaru Kyle Mimun A. Joshua Wand |
| author_sort | Anthony C. Bishop |
| collection | DOAJ |
| description | The authors present BARASA, an approach to assign backbone triple resonance spectra of proteins that augments traditional approaches with a Bayesian statistical analysis of the observed chemical shifts. The algorithm employs a simulated annealing engine to establish a consensus set of resonance assignments and is tested against systems ranging in size to over 450 amino acids including examples of intrinsically disordered proteins. |
| first_indexed | 2024-04-09T22:49:44Z |
| format | Article |
| id | doaj.art-b8c804182311451eb70bca6041e4fffb |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-09T22:49:44Z |
| publishDate | 2023-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-b8c804182311451eb70bca6041e4fffb2023-03-22T11:42:36ZengNature PortfolioNature Communications2041-17232023-03-0114111510.1038/s41467-023-37219-zRobust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealingAnthony C. Bishop0Glorisé Torres-Montalvo1Sravya Kotaru2Kyle Mimun3A. Joshua Wand4Department of Biochemistry & Biophysics, Texas A&M UniversityDepartment of Biochemistry & Biophysics, Texas A&M UniversityGraduate Group in Biochemistry & Molecular Biophysics, Perelman School of Medicine, University of PennsylvaniaDepartment of Biochemistry & Biophysics, Texas A&M UniversityDepartment of Biochemistry & Biophysics, Texas A&M UniversityThe authors present BARASA, an approach to assign backbone triple resonance spectra of proteins that augments traditional approaches with a Bayesian statistical analysis of the observed chemical shifts. The algorithm employs a simulated annealing engine to establish a consensus set of resonance assignments and is tested against systems ranging in size to over 450 amino acids including examples of intrinsically disordered proteins.https://doi.org/10.1038/s41467-023-37219-z |
| spellingShingle | Anthony C. Bishop Glorisé Torres-Montalvo Sravya Kotaru Kyle Mimun A. Joshua Wand Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing Nature Communications |
| title | Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing |
| title_full | Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing |
| title_fullStr | Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing |
| title_full_unstemmed | Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing |
| title_short | Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing |
| title_sort | robust automated backbone triple resonance nmr assignments of proteins using bayesian based simulated annealing |
| url | https://doi.org/10.1038/s41467-023-37219-z |
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