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Related Concept Videos

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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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IR Spectroscopy: Molecular Vibration Overview01:24

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When Infrared (IR) radiation passes through a covalently bonded molecule, the bonds transition from lower to higher vibrational levels. The fundamental vibrational motions that result in infrared absorption can be classified as stretching or bending vibrations.
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¹H NMR of Conformationally Flexible Molecules: Temporal Resolution00:52

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At room temperature, the chair conformer of cyclohexane undergoes rapid ring flipping between two equivalent chair conformers at a rate of approximately 105 times per second. These two chair conformers are in equilibrium. The rapid ring flipping results in the interconversion of the axial proton to an equatorial proton and an equatorial to the axial proton. Such interconversions are too rapid and cannot be detected on the NMR timescale. Hence, the NMR spectrometer cannot distinguish between the...
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NMR Spectroscopy Of Amines01:19

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In proton NMR spectroscopy, primary amines and secondary amines showcase their N–H protons as a broad signal in the chemical shift range between δ 0.5 and 5 ppm. The exact position in this range depends on several factors, including sample concentration, hydrogen bonding, and the type of solvent used. Since amine protons undergo fast proton exchange in solution, the protons are labile and therefore do not participate in any splitting with adjacent protons. Thus, the observed peak is...
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IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

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Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
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Updated: Jan 15, 2026

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Dynamic protein structures in solution: decoding the amide I band with 2D-IR spectral libraries and machine learning.

Amy L Farmer1, Kelly Brown1, Sophie E T Kendall-Price1

  • 1Department of Chemistry and York Biomedical Research Institute, University of York York UK neil.hunt@york.ac.uk.

Chemical Science
|January 14, 2026
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Summary
This summary is machine-generated.

Ultrafast 2D-IR spectroscopy combined with machine learning rapidly determines protein structures in solution. This hybrid approach accurately quantifies protein structural elements like alpha-helices and beta-sheets.

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Area of Science:

  • Protein structure analysis
  • Spectroscopy
  • Computational biology

Background:

  • Protein 3D structures are crucial for function but difficult to study in solution.
  • Ultrafast 2D-IR spectroscopy offers rapid, label-free analysis of protein backbone structure in aqueous solution.
  • Translating 2D-IR spectral fingerprints into quantitative structural data requires advanced interpretation methods.

Purpose of the Study:

  • To develop a method for quantitative, solution-phase protein structure determination using 2D-IR spectroscopy and machine learning.
  • To establish the link between 2D-IR spectral fingerprints and atomistic protein structures.
  • To enable rapid analysis of dynamic protein structures under physiological conditions.

Main Methods:

  • Utilized ultrafast 2D-IR spectroscopy to generate spectral fingerprints of proteins in H2O.
  • Compiled a dataset of 6732 spectra from 35 diverse proteins.
  • Employed machine learning, specifically Support-Vector Machine (SVM) models, to analyze spectral data.

Main Results:

  • SVM models accurately classified protein structural content and quantified alpha-helix and beta-sheet amounts with an RMS error of ≤7%.
  • Demonstrated the potential to predict helix counts/lengths and differentiate parallel/antiparallel beta-sheets from 2D-IR spectra.
  • Established a quantitative link between 2D-IR spectral data and protein secondary structure.

Conclusions:

  • A hybrid 2D-IR spectroscopy and machine learning approach enables rapid, quantitative analysis of protein structures in solution.
  • This method provides a foundation for studying dynamic protein structures under physiologically relevant conditions.
  • The findings pave the way for high-throughput structural biology applications.