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A STEADY-STATE APPROACH FOR ANALYSIS OF HIGH-RESOLUTION RELAXOMETRY

This tool fits combined low-field (field-cycling) and high-field relaxation data to the Lipari-Szabo Model-Free spectral density function, extracting per-residue rotational correlation times and order parameters for protein backbone dynamics.

Relaxometry App: Graphic User Interface

Download & Installation

System requirements:
Windows 10 or later / macOS 10.14 or later / Linux (64-bit, released 2022 or later — e.g. Ubuntu 22.04+, Debian 12+, Fedora 38+). Older Linux distributions may not be compatible; if the app fails to launch on an older system, please contact us and we can provide a build for your specific distribution.
No separate Python installation needed — everything required is bundled. Download size is approximately 150–500 MB depending on platform, since a full scientific computing stack is included.

Operation SystemsDownload
Windows 10 or laterfile
macOS 10.14 or laterfile
Linux (64-bit, released 2022 or later)file

Note: this software is not yet code-signed. On first launch, your operating system may show a security warning — this is expected for unsigned software, not a sign of a problem with the file.
On macOS: right-click (or Control-click) the app and choose "Open", then confirm "Open" in the dialog that appears.
On Windows: if SmartScreen appears, click "More info", then "Run anyway".

For input file format, please download the example input files: relaxometry data for E. coli ribonuclease HI

No installer needed — this is a portable, ready-to-run application.

  1. Download the zip file for your operating system above.
  2. Unzip it. Keep the executable together with its accompanying folder (e.g. "_internal") — they must stay in the same directory for the app to run.
  3. Double-click the application to launch it. A browser tab will open automatically with the interface — no separate browser setup is needed.
  4. A console/terminal window will also open in the background. Leave it running — closing it will shut down the app. This is expected behavior for this release.

This is an early-access (beta) release. We're actively refining it based on real-world use — feedback, bug reports, and feature requests are very welcome via our Contact page.

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Usage

Relaxometry App: single-residue fit results and fit curves

Single-residue fit: parameters and fit curves, generated directly in the app.

  1. Upload the LF (field-cycling) R1 CSV and the HF (static high-field) Rates CSV in the sidebar. Use the precise-field-value ('_cc') style LF file — column headers with decimal Tesla values, e.g. '16.440T', not rounded whole-Tesla labels — to avoid a systematic field-offset in the fit.
  2. On Multi-Nucleus-Pair Support:
    • 15N–1H (amide, validated) — the default
    • 13C–1H (aliphatic/methyl, UNVALIDATED) — fills in literature-typical γ, bond length, and CSA defaults, but the steady-state remote-1H-bath formula itself has NOT been checked against real 13C data yet. The app shows a warning when this preset is active. Treat results as exploratory until validated against a real 13C dataset
    • Custom — set every constant by hand.
  3. Check/adjust physical constants (γ_N, γ_H, r_NH, r_HH, CSA_N, CSA_H ...).
  4. Data Preview tab: sanity-check the parsed LF/HF data before fitting anything.
  5. ScaleFactor Search tab: run a grid search across a subset of residues to find the dataset-wide consensus ScaleFactor (c), matching the reference notebook's methodology (trimmed mean/median across residues, NOT fit per residue).
  6. Enter that consensus c into the sidebar "ScaleFactor (c)" field — it's applied as a single fixed value to every residue, exactly as in the reference workflow.
  7. Single-Residue Fit tab: test one residue, see fitted parameters (τc, S2f, τf, S2s, τs, Rex), χ2, and R2 (goodness of fit), plus comparison plots.
  8. Batch Fit tab: fit every common residue, download results as CSV.
  9. LF field range slider (sidebar, appears after data is loaded): Options to exclude outliers if neccessary.
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Reference

If you publish or present results from this tool, please cite:

  • Bhattacharya, S. et al. (2025). Steady-state relaxometry paper. Journal of Magnetic Resonance. doi: 10.1016/j.jmr.2025.107989
  • Palmer, A.; Bhattacharya, S. (2025). Relaxometry for human ubiquitin and E. coli ribonuclease HI. Mendeley Data, V1. doi: 10.17632/ssrg4pwtt2.1
Also shown in-app under the sidebar "Citation / references" expander.

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License

This tool combines two components under different licenses:

  • Core algorithm: the steady-state relaxometry method, developed by Arthur G. Palmer and Shibani Bhattacharya (Columbia University / NYSBC), available under CC BY 4.0 via Mendeley Data (doi: 10.17632/ssrg4pwtt2.1) — free to use, including commercially, with attribution.
  • Packaged application (this tool): the GUI, executables, and documentation, developed by Field Cycling Technology Ltd., available under CC BY-NC 4.0 — free for non-commercial use, with attribution. For commercial use, please contact us.
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