[NMR paper] A coarse-grained approach to NMR-data-assisted modeling of protein structures
A coarse-grained approach to NMR-data-assisted modeling of protein structures
The ESCASA algorithm for analytical estimation of proton positions from coarse-grained geometry developed in our recent work has been implemented in modeling protein structures with the highly coarse-grained UNRES model of polypeptide chains (two sites per residue) and nuclear magnetic resonance (NMR) data. A penalty function with the shape of intersecting gorges was applied to treat ambiguous distance restraints, which automatically selects consistent restraints. Hamiltonian replica exchange...
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09-23-2022 06:24 AM
[NMR paper] An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical Modeling
An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical Modeling
Paramagnetic nuclear magnetic resonance (NMR) methods have emerged as powerful tools for structure determination of large, sparsely protonated proteins. However traditional applications face several challenges, including a need for large datasets to offset the sparsity of restraints, the difficulty in accounting for the conformational heterogeneity of the spin-label, and noisy experimental data. Here we propose an integrative approach to structure determination combining...
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09-04-2021 10:34 AM
[NMR paper] PRE-driven Protein NMR Structures: an Alternative Approach in Highly Paramagnetic Systems.
PRE-driven Protein NMR Structures: an Alternative Approach in Highly Paramagnetic Systems.
http://www.bionmr.com//www.ncbi.nlm.nih.gov/corehtml/query/egifs/http:--media.wiley.com-assets-7388-69-wiley-full-text.png Related Articles PRE-driven Protein NMR Structures: an Alternative Approach in Highly Paramagnetic Systems.
FEBS J. 2020 Oct 30;:
Authors: Trindade IB, Invernici M, Cantini F, Louro RO, Piccioli M
Abstract
Metalloproteins play key roles across biology, and knowledge of their structure is essential to understand their...
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11-04-2020 05:04 PM
[NMR paper] High accuracy protein structures from minimal sparse paramagnetic solid-state NMR restraints.
High accuracy protein structures from minimal sparse paramagnetic solid-state NMR restraints.
http://www.bionmr.com//www.ncbi.nlm.nih.gov/corehtml/query/egifs/http:--media.wiley.com-assets-7315-19-Wiley_FullText_120x30_orange.png Related Articles High accuracy protein structures from minimal sparse paramagnetic solid-state NMR restraints.
Angew Chem Int Ed Engl. 2019 Mar 26;:
Authors: Perez A, Gaalswyk K, Jaroniec CP, MacCallum JL
Abstract
There is a pressing need for new computational tools to integrate data from diverse...
[NMR paper] 3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data.
3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data.
3D Computational Modeling of Proteins Using Sparse Paramagnetic NMR Data.
Methods Mol Biol. 2017;1526:3-21
Authors: Pilla KB, Otting G, Huber T
Abstract
Computational modeling of proteins using evolutionary or de novo approaches offers rapid structural characterization, but often suffers from low success rates in generating high quality models comparable to the accuracy of structures observed in X-ray crystallography or nuclear magnetic resonance (NMR)...
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11-30-2016 11:16 AM
[NMR paper] Capturing Conformational States in Proteins Using Sparse Paramagnetic NMR Data.
Capturing Conformational States in Proteins Using Sparse Paramagnetic NMR Data.
Related Articles Capturing Conformational States in Proteins Using Sparse Paramagnetic NMR Data.
PLoS One. 2015;10(5):e0127053
Authors: Pilla KB, Leman JK, Otting G, Huber T
Abstract
Capturing conformational changes in proteins or protein-protein complexes is a challenge for both experimentalists and computational biologists. Solution nuclear magnetic resonance (NMR) is unique in that it permits structural studies of proteins under greatly varying...
An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical ... - Frontiers
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