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Raman Spectroscopy: Overview

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The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
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A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
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Metadynamics And Raman Spectroscopy For Glycan Structure-spectrum Mapping.

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Metadynamics And Raman Spectroscopy For Glycan Structure-spectrum Mapping.

Related Experiment Video

Mass Spectrometric Analysis of Glycosphingolipid Antigens

Mass Spectrometric Analysis of Glycosphingolipid Antigens

Published on: April 16, 2013

Metadynamics and Raman Spectroscopy for Glycan Structure-Spectrum Mapping.

Varun Dolia¹, Nicholas Siemons¹, Jack Hu²

¹Department of Materials Science and Engineering, Stanford University, 496 Lomita Mall, Stanford, California 94305, United States.

Journal of the American Chemical Society

|June 17, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

DynaSpec links molecular structures to Raman spectra, improving biomolecule analysis. This framework accurately classifies glycans and aids in distinguishing complex mixtures and isomers.

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Area of Science:

Biophysical Chemistry
Computational Chemistry
Spectroscopy

Background:

Raman spectroscopy provides label-free molecular vibration data across biological systems.
Interpreting Raman spectra for complex biomolecules like glycans is challenging due to heterogeneity.
Existing methods struggle to link conformational ensembles to vibrational spectra.

Purpose of the Study:

To introduce DynaSpec, a novel framework for ensemble-resolved structure-spectrum mapping.
To enable mechanistic interpretation of complex Raman spectra by linking molecular conformations to vibrational data.
To facilitate bidirectional inference between biomolecular structure and Raman spectra.

Main Methods:

Integrating metadynamics in a machine-learned latent space with population-weighted DFT Raman calculations.

Utilizing experimental spectroscopy alongside computational predictions for validation.

Developing a framework for bidirectional structure-spectrum inference.

Main Results:

DynaSpec achieved >85% classification accuracy for 13 N-glycans.
Identified a conserved α1,6 open-curled switching motif in N-glycans.
Enabled accurate discrimination of glycan positional isomers (>70%) and unmixing of mixtures (R² > 0.99).
Demonstrated generalization to O-glycans and glycosaminoglycans, validated with hyaluronic acid.

Conclusions:

DynaSpec establishes an ensemble-resolved framework for structure-informed spectroscopy.
The framework accurately interprets congested Raman signatures and links them to molecular conformations.
This approach advances the analysis of diverse biomolecular classes using vibrational spectroscopy.