Carbohydrates NMR Prediction

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The accurate prediction of Nuclear Magnetic Resonance (NMR) spectra for carbohydrates is a critical aspect in the field of carbohydrate research. It offers valuable insights into the structure, conformation, and interactions of these complex biomolecules. At CD ComputaBio, we provide advanced Computational Modeling-based Carbohydrates NMR Prediction services.

Introduction to Carbohydrates NMR Prediction

Carbohydrates play vital roles in numerous biological processes and have diverse applications in various industries. Understanding their NMR spectra is essential for precise characterization and analysis. Our team of experts is dedicated to delivering reliable and accurate NMR predictions for carbohydrates.

Fig 1.Carbohydrates NMR Prediction Figure 1. Carbohydrates NMR Prediction.( Stryeck S, et al.2018)

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Fig 2. 1H NMR Prediction

1H NMR Prediction

Accurately predict the proton NMR spectra of carbohydrates, providing information on hydrogen atom environments and chemical shifts.

Example: Helping to identify the different sugar units in a complex carbohydrate structure.

Fig 3. 13C NMR Prediction

13C NMR Prediction

Predict the carbon-13 NMR spectra, offering insights into the carbon atom chemical environments and connectivity.

Example: Assisting in the determination of glycosidic linkages in carbohydrate polymers.

Fig 4. 2D NMR Prediction (COSY, HSQC, etc.)

2D NMR Prediction (COSY, HSQC, etc.)

Predict two-dimensional NMR spectra such as Correlation Spectroscopy (COSY) and Heteronuclear Single Quantum Coherence (HSQC), enhancing structural elucidation.

Example: Facilitating the assignment of proton and carbon correlations in carbohydrate molecules.

Fig 5. NMR Spectra under Different Solvents and pH

NMR Spectra under Different Solvents and pH

Predict NMR spectra of carbohydrates in various solvents and at different pH values, accounting for environmental effects.

Example: Enabling the understanding of how solvent polarity and pH influence carbohydrate NMR spectra.

Sample Requirements and Result Delivery

Sample Requirements	Result Delivery
The chemical structure of the carbohydrate in a standard format (e.g., SMILES, Mol file). Information on the desired solvents, pH conditions, and temperature if relevant. Specific NMR techniques and nuclei (1H, 13C, 2D, etc.) for which predictions are required.	Predicted NMR spectra in a clear and easily interpretable format (graphs and tables). A detailed report explaining the computational methods used, the predicted chemical shifts, and any notable features or trends. Comparative analysis with available experimental data or similar compounds if applicable.

Approaches toCarbohydrates NMR Prediction

Density Functional Theory (DFT) Calculations

Utilize DFT to compute the electronic structure and magnetic shielding tensors, which are correlated with NMR chemical shifts.

Molecular Dynamics (MD) Simulations

Incorporate MD simulations to account for conformational averaging and solvent effects on NMR spectra.

Machine Learning-Based Predictions

Employ machine learning algorithms trained on large datasets of experimentally measured NMR spectra of carbohydrates.

Advantages of Our Services

High Accuracy and Reliability

Our predictions are based on sophisticated computational models and extensive validation against experimental data.

Comprehensive Analysis

We provide not only the predicted spectra but also detailed interpretations and comparisons with related compounds.

Customized Solutions

Tailor our predictions to meet the specific needs and requirements of each client's research or application.

Timely Delivery

We understand the importance of timely results and strive to deliver our predictions within the agreed-upon timeframe.

Frequently Asked Questions

How does carbohydrates NMR prediction work?

There are several methods for predicting carbohydrates NMR spectra. One common approach is to use quantum mechanical calculations, such as density functional theory (DFT), to calculate the electronic structure of the carbohydrate molecule. From this, the chemical shifts and coupling constants can be determined using appropriate algorithms. Another approach is to use empirical methods that are based on correlations between the structure of carbohydrates and their NMR spectra. These methods typically involve building a database of known carbohydrate structures and their corresponding NMR spectra, and then using machine learning or statistical techniques to predict the spectra of new carbohydrates.

What are the advantages of using carbohydrates NMR prediction?

How can I validate the accuracy of carbohydrates NMR prediction?

What types of carbohydrates can be predicted using NMR prediction?

CD ComputaBio's Carbohydrates NMR Prediction service is a powerful tool for researchers and professionals in the carbohydrate field. Our advanced feature services, algorithms, and advantages enable us to provide accurate and insightful NMR predictions. Contact us today to enhance your carbohydrate research and development efforts with our cutting-edge computational modeling solutions.

Reference

Stryeck S, Horvath A, Leber B, et al. NMR spectroscopy enables simultaneous quantification of carbohydrates for diagnosis of intestinal and gastric permeability. Scientific reports, 2018, 8(1): 14650.

For research use only. Not intended for any clinical use.

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