ArticleJournal of biomolecular NMR2003
PROSHIFT: protein chemical shift prediction using artificial neural networks.
Article in Journal of biomolecular NMR, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.
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Who cites it
79 citing papers in PubMed.
- Probing Solution Dynamics of Tissue Factor Using Molecular Dynamics Simulations Guided by NMR Chemical Shifts.The journal of physical chemistry. B · 2026Article
- Automatic forward model parameterization with Bayesian inference of conformational populations.APL machine learning · 2026Article
- Hyperpolarized NMR Combined with Quantum Mechanical Simulations Reveal Atomistic Structures of Calcium Phosphate Prenucleation Clusters.Analytical chemistry · 2025Article
- Structure-Based Experimental Datasets for Benchmarking Protein Simulation Force Fields [Article v1.0].Living journal of computational molecular science · 2025Article
- Automatic Forward Model Parameterization with Bayesian Inference of Conformational Populations.ArXiv · 2025Article
- New Insights into Nuclear Magnetic Resonance (NMR) Spectroscopy.Molecules (Basel, Switzerland) · 2025Article
- Spiers Memorial Lecture: NMR crystallography.Faraday discussions · 2025Article
- Accurate and Efficient Structure Elucidation from Routine One-Dimensional NMR Spectra Using Multitask Machine Learning.ACS central science · 2024Article
- Machine Learning IsotropicJournal of chemical theory and computation · 2024Article
- Molecular mechanisms and evolutionary robustness of a color switch in proteorhodopsins.Science advances · 2024Article
- Atomic-level structure determination of amorphous molecular solids by NMR.Nature communications · 2023Article
- Recent Advances in NMR Protein Structure Prediction with ROSETTA.International journal of molecular sciences · 2023Review
- Release of frustration drives corneal amyloid disaggregation by brain chaperone.Communications biology · 2023Article
- A Machine Learning Model of Chemical Shifts for Chemically and Structurally Diverse Molecular Solids.The journal of physical chemistry. C, Nanomaterials and interfaces · 2022Article
- High-Resolution Conformational Analysis of RGDechi-Derived Peptides Based on a Combination of NMR Spectroscopy and MD Simulations.International journal of molecular sciences · 2022Article
- A framework for automated structure elucidation from routine NMR spectra.Chemical science · 2021Article
- Gaussian Process Regression for Materials and Molecules.Chemical reviews · 2021Article
- Predicting chemical shifts with graph neural networks.Chemical science · 2021Article
- Hybrid methods for combined experimental and computational determination of protein structure.The Journal of chemical physics · 2020Review
- Using quantum chemistry to estimate chemical shifts in biomolecules.Biophysical chemistry · 2020Review
19 more citing papers are in PubMed but not listed here.
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1 author.
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Abstract
The importance of protein chemical shift values for the determination of three-dimensional protein structure has increased in recent years because of the large databases of protein structures with assigned chemical shift data. These databases have allowed the investigation of the quantitative relationship between chemical shift values obtained by liquid state NMR spectroscopy and the three-dimensional structure of proteins. A neural network was trained to predict the (1)H, (13)C, and (15)N of proteins using their three-dimensional structure as well as experimental conditions as input parameters. It achieves root mean square deviations of 0.3 ppm for hydrogen, 1.3 ppm for carbon, and 2.6 ppm for nitrogen chemical shifts. The model reflects important influences of the covalent structure as well as of the conformation not only for backbone atoms (as, e.g., the chemical shift index) but also for side-chain nuclei. For protein models with a RMSD smaller than 5 A a correlation of the RMSD and the r.m.s. deviation between the predicted and the experimental chemical shift is obtained. Thus the method has the potential to not only support the assignment process of proteins but also help with the validation and the refinement of three-dimensional structural proposals. It is freely available for academic users at the PROSHIFT server: www.jens-meiler.de/proshift.html
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