[NMR paper] Blind assessment of monomeric AlphaFold2 protein structure models with experimental NMR data
Blind assessment of monomeric AlphaFold2 protein structure models with experimental NMR data
Recent advances in molecular modeling of protein structures are changing the field of structural biology. AlphaFold-2 (AF2), an AI system developed by DeepMind, Inc., utilizes attention-based deep learning to predict models of protein structures with high accuracy relative to structures determined by X-ray crystallography and cryo-electron microscopy (cryoEM). Comparing AF2 models to structures determined using solution NMR data, both high similarities and distinct differences have been...
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nmrlearner
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06-01-2023 05:37 PM
[NMR paper] Structure Determination of Challenging Protein-Peptide Complexes Combining NMR Chemical Shift Data and Molecular Dynamics Simulations
Structure Determination of Challenging Protein-Peptide Complexes Combining NMR Chemical Shift Data and Molecular Dynamics Simulations
Intrinsically disordered regions of proteins often mediate important protein-protein interactions. However, the folding-upon-binding nature of many polypeptide-protein interactions limits the ability of modeling tools to predict the three-dimensional structures of such complexes. To address this problem, we have taken a tandem approach combining NMR chemical shift data and molecular simulations to determine the structures of peptide-protein complexes. Here,...
nmrlearner
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03-31-2023 09:21 AM
[NMR paper] Blind Assessment of Monomeric AlphaFold2 Protein Structure Models with Experimental NMR Data
Blind Assessment of Monomeric AlphaFold2 Protein Structure Models with Experimental NMR Data
Recent advances in molecular modeling of protein structures are changing the field of structural biology. AlphaFold-2 (AF2), an AI system developed by DeepMind, Inc., utilizes attention-based deep learning to predict models of protein structures with high accuracy relative to structures determined by X-ray crystallography and cryo-electron microscopy (cryoEM). Comparing AF2 models to structures determined using solution NMR data, both high similarities and distinct differences have been...
...
nmrlearner
Journal club
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02-01-2023 06:19 AM
[NMR paper] Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information.
Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information.
Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information.
J Biomol NMR. 2013 Apr 28;
Authors: Fritzsching KJ, Yang Y, Schmidt-Rohr K, Hong M
Abstract
We introduce a Python-based program that utilizes the large database of (13)C and (15)N chemical shifts in the Biological Magnetic...
nmrlearner
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04-30-2013 10:21 PM
Interpreting protein chemical shift data
Interpreting protein chemical shift data
Publication year: 2011
Source:Progress in Nuclear Magnetic Resonance Spectroscopy, Volume 58, Issues 1–2</br>
David S. Wishart</br>
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nmrlearner
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03-09-2012 09:16 AM
GeNMR - template-based structure generation from NMR data
GeNMR website
GeNMR (GEnerate NMR structures) is a web server for template-based or ab initio generation of 3D protein structures using NOE-derived distance restraints and NMR chemical shifts. The web server produces an ensemble of PDB coordinates within a period ranging from 20 minutes to 4 hours, depending on protein size, server load, quality and type of experimental information, and selected protocol options.
References:
1. Berjanskii M, Tang P, Liang J, Cruz JA, Zhou J, Zhou Y, Bassett E, MacDonell C, Lu P, Lin G, Wishart DS. (2009)GeNMR: a web server for rapid NMR-based...
markber
NMR software
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02-23-2012 10:21 PM
Protein secondary structure prediction using NMR chemical shift data.
Protein secondary structure prediction using NMR chemical shift data.
Related Articles Protein secondary structure prediction using NMR chemical shift data.
J Bioinform Comput Biol. 2010 Oct;8(5):867-84
Authors: Zhao Y, Alipanahi B, Li SC, Li M
Accurate determination of protein secondary structure from the chemical shift information is a key step for NMR tertiary structure determination. Relatively few work has been done on this subject. There needs to be a systematic investigation of algorithms that are (a) robust for large datasets; (b)...
Consistent blind protein structure generation from NMR chemical shift data - pnas.org
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