2d nmr pulse sequence implementation
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Use when when you need to generate 2D metabolomic NMR spectra (COSY for homonuclear or HSQC/HMQC for heteronuclear correlations) from parsed metabolite concentration and spin-system J-coupling data, and you want to simulate realistic peak patterns including indirect-dimension evolution and phase.
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SKILL.md
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2D NMR Pulse Sequence Implementation
License: restricted — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution. <!-- asb-license-banner -->
Summary
Design and execute 2D NMR pulse sequences (COSY, HSQC/HMQC) to compute 1H–1H or 1H–13C correlation multiplets with appropriate indirect-dimension evolution, enabling metabolomic structure elucidation. This skill bridges simulated spin systems to 2D frequency-domain spectra by applying phase-encoding and indirect-dimension time steps.
When to use
When you need to generate 2D metabolomic NMR spectra (COSY for homonuclear or HSQC/HMQC for heteronuclear correlations) from parsed metabolite concentration and spin-system J-coupling data, and you want to simulate realistic peak patterns including indirect-dimension evolution and phase encoding.
When NOT to use
- Input is already a measured 2D NMR spectrum (no simulation needed; use acquisition software instead)
- Metabolite identities or J-couplings are unknown or unavailable (simulation requires explicit spin-system topology)
- Goal is to process or interpret experimental 2D spectra rather than generate synthetic reference data
Inputs
- Metabolite concentration values (numeric array or list)
- Spin-system coupling constants (J-values) per metabolite (Hz)
- Chemical shifts for involved nuclei (ppm)
- Pulse sequence parameters (indirect-dimension increments, phase encoding steps, receiver phases)
- Lineshape function specification (Lorentzian or Gaussian bandwidth)
Outputs
- 2D NMR spectral array (frequency-domain, real or complex)
- Indirect and direct dimension frequency axes (ppm)
- 2D spectral data in HDF5 or netCDF format
- Cross-peak multiplet patterns (COSY or HSQC/HMQC correlation map)
How to apply
Starting from parsed metabolite concentrations and spin-system coupling constants (J-values), select the appropriate 2D pulse sequence (COSY for 1H–1H correlation or HSQC/HMQC for 1H–13C heteronuclear correlation). Implement the sequence by evolving the spin system through indirect-dimension time increments with phase encoding, computing cross-peak multiplets that reflect scalar coupling between correlated nuclei. Apply the same lineshape convolution (Lorentzian or Gaussian) used in the 1D simulation to account for realistic peak broadening. Fourier-transform both direct and indirect dimensions to produce a 2D frequency-domain array. Save the result in standard NMR data formats (HDF5 or netCDF) compatible with downstream NMR analysis software.
Related tools
- MetAssimulo 2 (Web application that implements 2D pulse sequences (COSY, HSQC/HMQC) for simulating 1H–1H and 1H–13C correlations from metabolite inputs) — https://github.com/yanyan5420/MetAssimulo_2
Examples
python3 apps/index.py -p Input/parameters.txt
Evaluation signals
- Cross-peaks appear at expected chemical shift intersections corresponding to coupled spin pairs (COSY) or coupled nuclei (HSQC/HMQC)
- Multiplet structure in cross-peaks matches theoretical J-coupling patterns (e.g., doublet, triplet) for the underlying spin system
- Indirect and direct dimension Fourier transforms produce peak frequencies (ppm) that align with input chemical shifts and J-couplings
- Output 2D spectral array conforms to HDF5 or netCDF schema with labeled frequency axes and metadata
- Lineshape convolution produces realistic peak widths without excessive broadening or ringing artifacts
Limitations
- Simulation uses first-order or density-matrix approximations; higher-order coupling effects are not explicitly modeled
- Pulse sequence parameters (flip angles, phase cycles, gradient strengths) must be manually specified; default values may not match all experimental protocols
- No experimental validation of simulated spectra against real NMR data is performed within the tool; realism depends on accurate input J-values and lineshape assumptions
- Complex spin systems (>4 coupled spins) may require longer computation or density-matrix methods; scalability limits are not documented
Evidence
- [other] For 2D spectra, compute 1H–1H correlation (COSY) or 1H–13C heteronuclear (HSQC/HMQC) multiplets using appropriate 2D pulse sequences and indirect-dimension evolution.: "For 2D spectra, compute 1H–1H correlation (COSY) or 1H–13C heteronuclear (HSQC/HMQC) multiplets using appropriate 2D pulse sequences and indirect-dimension evolution."
- [other] Generate theoretical spin multiplets using first-order or density-matrix NMR simulation for each spin system, accounting for chemical shift and J-coupling.: "Generate theoretical spin multiplets using first-order or density-matrix NMR simulation for each spin system, accounting for chemical shift and J-coupling."
- [other] Convolve simulated multiplets with a Lorentzian or Gaussian lineshape function to approximate realistic peak broadening.: "Convolve simulated multiplets with a Lorentzian or Gaussian lineshape function to approximate realistic peak broadening."
- [other] Save simulated 1D and 2D spectra as HDF5 or netCDF spectral arrays compatible with standard NMR data formats.: "Save simulated 1D and 2D spectra as HDF5 or netCDF spectral arrays compatible with standard NMR data formats."
- [readme] This repository contains all the necessary code for the MetAssimulo 2 project.: "This repository contains all the necessary code for the MetAssimulo 2 project."