Chemical shift assignment is vital for nuclear magnetic resonance (NMR)-based studies of protein structures, dynamics, and interactions, providing crucial atomic-level insight. However, obtaining chemical shift assignments is labor intensive and requires extensive measurement time. To address this limitation, we previously proposed ARTINA, a deep learning method for automatic assignment of two-dimensional (2D)-4D NMR spectra. Here, we present an integrative approach that combines ARTINA with...
[NMR paper] Rapid estimation approach for glycosylated serum protein of human serum based on the combination of deep learning and TD-NMR technology
Rapid estimation approach for glycosylated serum protein of human serum based on the combination of deep learning and TD-NMR technology
Rapid and precise estimation of glycosylated serum protein (GSP) of human serum is of great importance for the treatment and diagnosis of diabetes mellitus. In this study, we propose a novel method for estimation of GSP level based on the combination of deep learning and time domain nuclear magnetic resonance (TD-NMR) transverse relaxation signal of human serum. Specifically, a principal component analysis (PCA)-enhanced one-dimensional convolutional...
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03-10-2023 06:48 PM
[NMR paper] NMRNet: A deep learning approach to automated peak picking of protein NMR spectra.
NMRNet: A deep learning approach to automated peak picking of protein NMR spectra.
NMRNet: A deep learning approach to automated peak picking of protein NMR spectra.
Bioinformatics. 2018 Mar 14;:
Authors: Klukowski P, Augoff M, Zieba M, Drwal M, Gonczarek A, Walczak MJ
Abstract
Motivation: Automated selection of signals in protein NMR spectra, known as peak picking, has been studied for over 20 years, nevertheless existing peak picking methods are still largely deficient. Accurate and precise automated peak picking would...
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03-17-2018 12:12 PM
[NMR paper] An approach to sequential NMR assignments of proteins: application to chemical shift restraint-based structure prediction.
An approach to sequential NMR assignments of proteins: application to chemical shift restraint-based structure prediction.
Related Articles An approach to sequential NMR assignments of proteins: application to chemical shift restraint-based structure prediction.
J Biomol NMR. 2014 Jun 19;
Authors: Wiedemann C, Bellstedt P, Herbst C, Görlach M, Ramachandran R
Abstract
A procedure for the simultaneous acquisition of {HNCOCANH & HCCCONH} chemical shift correlation spectra employing sequential data acquisition for moderately sized...
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06-20-2014 08:14 PM
An approach to sequential NMR assignments of proteins: application to chemical shift restraint-based structure prediction
An approach to sequential NMR assignments of proteins: application to chemical shift restraint-based structure prediction
Abstract
A procedure for the simultaneous acquisition of {HNCOCANH & HCCCONH} chemical shift correlation spectra employing sequential \(^{1}\hbox {H}\) data acquisition for moderately sized proteins is presented. The suitability of the approach for obtaining sequential resonance assignments, including complete ...
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06-19-2014 10:21 PM
Solid state NMR chemical shift assignment and conformational analysis of a cellulose binding protein facilitated by optimized glycerol enrichment
Solid state NMR chemical shift assignment and conformational analysis of a cellulose binding protein facilitated by optimized glycerol enrichment
Abstract
Magic-angle spinning solid-state NMR has been applied to study CBM3bâ??Cbh9A (CBM3b), a cellulose binding module protein belonging to family 3b. It is a 146-residue protein having a unique nine-stranded β-sandwich fold, in which 35Â*% of the structure is in a β-sheet conformation and the remainder of the protein is composed of loops and unstructured regions. Yet, the protein can be crystalized...
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[NMR paper] Solid state NMR chemical shift assignment and conformational analysis of a cellulose binding protein facilitated by optimized glycerol enrichment.
Solid state NMR chemical shift assignment and conformational analysis of a cellulose binding protein facilitated by optimized glycerol enrichment.
http://www.bionmr.com//www.ncbi.nlm.nih.gov/corehtml/query/egifs/http:--production.springer.de-OnlineResources-Logos-springerlink.gif Related Articles Solid state NMR chemical shift assignment and conformational analysis of a cellulose binding protein facilitated by optimized glycerol enrichment.
J Biomol NMR. 2014 May 14;
Authors: Ivanir H, Goldbourt A
Abstract
Magic-angle spinning...
Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction
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