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Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR
ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [(13)C,(15)N]-labeled protein sample loaded into the NMR spe...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3299752/ https://www.ncbi.nlm.nih.gov/pubmed/22427982 http://dx.doi.org/10.1371/journal.pone.0033173 |
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author | Bahrami, Arash Tonelli, Marco Sahu, Sarata C. Singarapu, Kiran K. Eghbalnia, Hamid R. Markley, John L. |
author_facet | Bahrami, Arash Tonelli, Marco Sahu, Sarata C. Singarapu, Kiran K. Eghbalnia, Hamid R. Markley, John L. |
author_sort | Bahrami, Arash |
collection | PubMed |
description | ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [(13)C,(15)N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches. |
format | Online Article Text |
id | pubmed-3299752 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-32997522012-03-16 Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR Bahrami, Arash Tonelli, Marco Sahu, Sarata C. Singarapu, Kiran K. Eghbalnia, Hamid R. Markley, John L. PLoS One Research Article ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [(13)C,(15)N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches. Public Library of Science 2012-03-12 /pmc/articles/PMC3299752/ /pubmed/22427982 http://dx.doi.org/10.1371/journal.pone.0033173 Text en Bahrami et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Bahrami, Arash Tonelli, Marco Sahu, Sarata C. Singarapu, Kiran K. Eghbalnia, Hamid R. Markley, John L. Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR |
title | Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR |
title_full | Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR |
title_fullStr | Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR |
title_full_unstemmed | Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR |
title_short | Robust, Integrated Computational Control of NMR Experiments to Achieve Optimal Assignment by ADAPT-NMR |
title_sort | robust, integrated computational control of nmr experiments to achieve optimal assignment by adapt-nmr |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3299752/ https://www.ncbi.nlm.nih.gov/pubmed/22427982 http://dx.doi.org/10.1371/journal.pone.0033173 |
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