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FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling |
Apr 19, 2021 - 10:30 AM - by nmrlearner
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FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling
Abstract
In recent years, the transformative potential of deep neural networks (DNNs) for analysing and interpreting NMR data has clearly been recognised. However, most applications of DNNs in NMR to date either struggle to outperform existing methodologies or are limited in scope to a narrow range of data that closely resemble the data that the network was trained on. These limitations have prevented a widescale uptake of DNNs in NMR. Addressing this, we introduce FID-Net, a deep neural network architecture inspired by WaveNet, for performing analyses on time domain NMR data. We first demonstrate the effectiveness of this architecture in reconstructing non-uniformly sampled (NUS) biomolecular NMR spectra. It is shown that a single network is able to reconstruct a diverse range of 2D NUS spectra that have been obtained with arbitrary sampling schedules, with a range of sweep widths, and a variety of other acquisition parameters. The performance of the trained FID-Net in this case exceeds or matches existing methods currently used for the reconstruction of NUS NMR spectra. Secondly, we present a network based on the FID-Net architecture that can efficiently virtually decouple 13Cα-13Cβ couplings in HNCA protein NMR spectra in a single shot analysis, while at the same time leaving glycine residues unmodulated. The ability for these DNNs to work effectively in a wide range of scenarios, without retraining, paves the way for their widespread usage in analysing NMR data.
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0 Replies | 2 Views
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A COVID moonshot: assessment of ligand binding to the SARS-CoV-2 main protease by saturation transfer difference NMR spectroscopy |
Apr 15, 2021 - 12:12 PM - by nmrlearner
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A COVID moonshot: assessment of ligand binding to the SARS-CoV-2 main protease by saturation transfer difference NMR spectroscopy
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological cause of the coronavirus disease 2019, for which no effective antiviral therapeutics are available. The SARS-CoV-2 main protease (Mpro) is essential for viral replication and constitutes a promising therapeutic target. Many efforts aimed at deriving effective Mpro inhibitors are currently underway, including an international open-science discovery project, codenamed COVID Moonshot. As part of COVID Moonshot, we used saturation transfer difference nuclear magnetic resonance (STD-NMR) spectroscopy to assess the binding of putative Mpro ligands to the viral protease, including molecules identified by crystallographic fragment screening and novel compounds designed as Mpro inhibitors. In this manner, we aimed to complement enzymatic activity assays of Mpro performed by other groups with information on ligand affinity. We have made the Mpro STD-NMR data publicly available. Here, we provide detailed information on the NMR protocols used and challenges faced, thereby placing these data into context. Our goal is to assist the interpretation of Mpro STD-NMR data, thereby accelerating ongoing drug design efforts.
Source: Journal of Biomolecular NMR
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0 Replies | 18 Views
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