Related ArticlesCHESPA/CHESCA-SPARKY: automated NMR data analysis plugins for SPARKY to map protein allostery.
Bioinformatics. 2020 Sep 14;:
Authors: Shao H, Boulton S, Olivieri C, Mohamed H, Akimoto M, Subrahmanian MV, Veglia G, Markley JL, Melacini G, Lee W
Abstract
MOTIVATION: Correlated NMR chemical shift changes identified through the CHEmical Shift Projection Analysis (CHESPA) and CHEmical Shift Covariance Analysis (CHESCA) reveal pathways of allosteric transitions in biological macromolecules. To address the need for an automated platform that implements CHESPA and CHESCA and integrates them with other NMR analysis software packages, we introduce here integrated plugins for NMRFAM-SPARKY that implement the seamless detection and visualization of allosteric networks.
AVAILABILITY: CHESCA-SPARKY and CHESPA-SPARKY are available in the latest version of NMRFAM-SPARKY from the National Magnetic Resonance Facility at Madison (http://pine.nmrfam.wisc.edu/download_packages.html), the NMRbox Project (https://nmrbox.org) and to subscribers to the SBGrid (https://sbgrid.org). The assigned spectra involved in this study and tutorial videos using this data set are available at https://sites.google.com/view/chescachespa-sparky.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Online.
PMID: 32926121 [PubMed - as supplied by publisher]
[NMR paper] Automated Analysis of Large-Scale NMR Data Generates Metabolomic Signatures and Links Them to Candidate Metabolites.
Automated Analysis of Large-Scale NMR Data Generates Metabolomic Signatures and Links Them to Candidate Metabolites.
http://www.bionmr.com//www.ncbi.nlm.nih.gov/corehtml/query/egifs/http:--pubs.acs.org-images-pubmed-acspubs.jpg Related Articles Automated Analysis of Large-Scale NMR Data Generates Metabolomic Signatures and Links Them to Candidate Metabolites.
J Proteome Res. 2019 09 06;18(9):3360-3368
Authors: Khalili B, Tomasoni M, Mattei M, Mallol Parera R, Sonmez R, Krefl D, Rueedi R, Bergmann S
Abstract
Identification of...
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08-12-2020 02:10 PM
Principal component analysis for automated classification of 2D spectra and interferograms of protein therapeutics: influence of noise, reconstruction details, and data preparation
Principal component analysis for automated classification of 2D spectra and interferograms of protein therapeutics: influence of noise, reconstruction details, and data preparation
Abstract
Protein therapeutics have numerous critical quality attributes (CQA) that must be evaluated to ensure safety and efficacy, including the requirement to adopt and retain the correct three-dimensional fold without forming unintended aggregates. Therefore, the ability to monitor protein higher order structure (HOS) can be valuable throughout the lifecycle of a protein...
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07-22-2020 09:36 PM
[NMR paper] PINE-SPARKY.2 for automated NMR-based protein structure research.
PINE-SPARKY.2 for automated NMR-based protein structure research.
Related Articles PINE-SPARKY.2 for automated NMR-based protein structure research.
Bioinformatics. 2017 Dec 21;:
Authors: Lee W, Markley JL
Abstract
Summary: NMR (nuclear magnetic resonance) spectroscopy, along with X-ray crystallography and Cryo-EM, is one of the three major tools that enable the determination of atomic-level structural models of biological macromolecules. Of these, NMR has the unique ability to follow important processes in solution, including...
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12-29-2017 02:19 AM
[NMR paper] Fast and Efficient Fragment-Based Lead Generation by Fully Automated Processing and Analysis of Ligand-Observed NMR Binding Data.
Fast and Efficient Fragment-Based Lead Generation by Fully Automated Processing and Analysis of Ligand-Observed NMR Binding Data.
http://www.bionmr.com//www.ncbi.nlm.nih.gov/corehtml/query/egifs/http:--pubs.acs.org-images-pubmed-acspubs.jpg Related Articles Fast and Efficient Fragment-Based Lead Generation by Fully Automated Processing and Analysis of Ligand-Observed NMR Binding Data.
J Med Chem. 2016 Apr 14;59(7):3303-10
Authors: Peng C, Frommlet A, Perez M, Cobas C, Blechschmidt A, Dominguez S, Lingel A
Abstract
NMR...
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09-28-2016 06:22 PM
[Question from NMRWiki Q&A forum] Data processing and Sparky
Data processing and Sparky
Dear NMRWikiers, I'm fresh in nmr field and would like to ask couple questions: 1. Our protein has about 132 residues.The NHSQC is well dispersed but many peaks can't be found in CBCANH and CBCACONH. HNCA/HNCOCA + HNCO/HNCACO are planned for backbone assignment. Other people processed data with NMRPipe. The NHSQC peaks can mostly find matching peaks in HNCO/HNCACO, while HNCA/HNCOCA can't be matched (no same resonances can be seen when synchronized). But, many peaks can be seen in HNCA/HNCOCA. I found that the whole scale of 13C axis in HNCA is from 51 to 66 and...
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01-26-2012 02:22 PM
[NMR Sparky Yahoo group] Sparky to CNS
Sparky to CNS
Hi, I would like to use CNS for structural calculations - I could not find a way to convert Sparky peak least to CNS (XPLOR) format. I can convert the NOESY
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08-21-2010 03:03 PM
[NMR Sparky Yahoo group] Sparky to CNS
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Hi, I would like to use CNS for structural calculations - I could not find a way to convert Sparky peak least to CNS (XPLOR) format. I can convert the NOESY
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nmrlearner
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08-21-2010 03:03 PM
CCPN Analysis - a hybrid of Sparky, Ansing & more
New CCPN program for protein spectra analysis and automatic assignment.
http://www.ccpn.ac.uk/ccpnmr/ccpnmr/doc/graphics/analysis_smallMol.jpg
Info from the CCPN website:
"CcpNmr Analysis is a new analysis program built on top of the CCP Data Model. The program is based partly on the existing ANSIG, written by Per Kraulis, partly on the current Sparky... Analysis will run under both Unix/Linux and Windows. Compared to ANSIG, CcpNmr Analysis includes a completely new graphical user interface, support for automatic assignment, Python as a scripting and macro language, and a number...
CHESPA/CHESCA-SPARKY: automated NMR data analysis plugins for SPARKY to map protein allostery.
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