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In the AX proton spin system, proton A can sense the two spin states of a coupled proton X, resulting in a doublet NMR signal with two peaks of equal (1:1) intensity. When proton A is coupled to two equivalent protons (AX2 spin system), the spin states of each X can be aligned with or against the external field, creating three possible scenarios. This results in a 1:2:1  triplet signal, where the central peak corresponds to the chemical shift of A and is twice as large or intense as the...
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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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¹H NMR: Interpreting Distorted and Overlapping Signals01:02

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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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Different notations are used to represent the three-dimensional structure of molecules on two-dimensional surfaces. One of the most commonly used representations is the dash-wedge formula. The dashed wedges, solid wedges, and the plane lines indicate the groups situated behind the plane, coming out of the plane, and in the plane, respectively.
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Related Experiment Video

Updated: May 24, 2025

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Normalized and Directional Interplay Scoring for the Interrogation of Proteoform Data.

Karl F Poncha1, Alyssa T Paparella1,2, Nicolas L Young1,2,3

  • 1Verna & Marrs McLean Department of Biochemistry & Molecular Pharmacology, Baylor College of Medicine, Houston, Texas 77030, United States.

Journal of Proteome Research
|February 28, 2025
PubMed
Summary

We developed new computational tools to analyze histone post-translational modifications (PTMs) and their interactions. These methods reveal how histone PTMs change in mouse organs during aging, offering insights into chromatin regulation.

Keywords:
agingchromatincrosstalkepigeneticsinterplaypost-translational modificationsproteoformstop-down proteomics

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Proteomics

Background:

  • Histone proteoforms, with multiple co-occurring post-translational modifications (PTMs), are key regulators of chromatin and gene expression.
  • Understanding histone proteoform dynamics is crucial for deciphering chromatin-based regulatory mechanisms.
  • Proteomics advancements allow for the identification and quantification of numerous proteoforms, but data complexity poses analytical challenges.

Purpose of the Study:

  • To introduce novel computational methods for analyzing histone PTM dynamics.
  • To demonstrate the application of these methods in studying mouse organ aging.
  • To provide more accurate measures of PTM crosstalk and its directionality.

Main Methods:

  • Development of two new computational scores: 'normalized interplay' for PTM crosstalk and 'directional interplay' (ΔI) for magnitude and directionality.
  • Application of these scoring methods to analyze histone modification dynamics in mouse organs.
  • Utilizing middle-down and top-down proteomics data for proteoform identification and quantification.

Main Results:

  • The 'normalized interplay' score offers a more complete and accurate measure of PTM crosstalk compared to previous methods.
  • The 'directional interplay' (ΔI) score quantifies the magnitude and directionality of crosstalk between histone PTMs.
  • Analysis revealed specific dynamics of histone H3 modifications in mouse organs during aging.

Conclusions:

  • The developed computational tools enhance the analysis of complex histone proteoform data.
  • These methods provide novel insights into the dynamics of histone PTMs and their crosstalk during aging.
  • The findings contribute to a deeper understanding of chromatin regulation and its age-related changes.