Simulation of Raman optical activity of multi-component monosaccharide samples

Area of Science:

• Carbohydrate chemistry
• Computational chemistry
• Spectroscopy

Background:

• Determining saccharide structure in solution is challenging.
• Optical spectroscopies like Raman optical activity (ROA) offer enhanced analysis but require computational interpretation.
• Current computational tools have limitations in precision for spectral analysis.

Purpose of the Study:

• To investigate the link between spectral shapes and saccharide structure.
• To understand the limitations of computational tools in interpreting ROA and Raman spectra.
• To improve the accuracy of computational methods for analyzing monosaccharide solutions.

Main Methods:

• Measurement and interpretation of Raman and ROA spectra of glucose and mannose solutions.
• Utilized a combination of molecular dynamics (MD) and density functional theory (DFT).
• Compared different hydration models (dielectric continuum vs. solvent-solute clusters) and incorporated NMR data for anomer and rotamer ratios.

Main Results:

• Simulation accuracy is highly dependent on the hydration model; cluster-based models showed better accuracy than continuum models.
• Combined MD/DFT simulations, informed by NMR data, yielded the most accurate results for anomer and rotamer ratios.
• Decomposition of experimental spectra into calculated subspectra provided realistic results for monosaccharide mixtures, with Raman (∼5%) outperforming ROA (∼10%) in accuracy.

Conclusions:

• The combination of vibrational spectroscopy (Raman and ROA) and theoretical simulations is a powerful tool for saccharide structure analysis.
• ROA and Raman data can serve as a validation tool for computational modeling, including MD force fields.
• Accurate hydration models and integration of experimental data (like NMR) are crucial for precise computational analysis of saccharide solutions.