[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...
More...
nmrlearner
Journal club
0
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...
nmrlearner
Journal club
0
09-04-2021 10:34 AM
[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)...
nmrlearner
Journal club
0
11-30-2016 11:16 AM
Protein structure modeling using sparse NMR data [Biophysics and Computational Biology]
Protein structure modeling using sparse NMR data
Thompson, J. M., Sgourakis, N. G., Liu, G., Rossi, P., Tang, Y., Mills, J. L., Szyperski, T., Montelione, G. T., Baker, D....
Date: 2012-06-19
While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that...
An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical Modeling - Frontiers
Linear Mode
