SPIND-TC

SPIND-TC extends the Sparse Pattern INDexing (SPIND) algorithm to index two-color X-ray free-electron laser diffraction patterns, enabling accurate indexing of dual-wavelength datasets for protein structure determination.


Key Features:

  • Two-Color Data Handling: Processes diffraction data from two-color X-ray free-electron laser sources, enabling analysis of dual-wavelength diffraction patterns.
  • Sparse-Pattern Indexing: Extends SPIND sparse-pattern indexing capability to two-color data and can index patterns with as few as five peaks.
  • Algorithmic Adaptation: Adapts the sparse-pattern indexing approach to accommodate identification and indexing of diffraction peaks across two wavelengths.
  • Support for Advanced Experiments: Enables analysis applicable to X-ray pump/X-ray probe experiments and multiple-wavelength anomalous dispersion phasing methods.
  • Validation: Demonstrated performance on simulated and experimental diffraction datasets of protein crystals.

Scientific Applications:

  • Structural Biology: Indexes two-color XFEL diffraction data to support protein structure determination from protein crystals.
  • Pump–Probe Studies and MAD Phasing: Supports workflows for X-ray pump/X-ray probe experiments and multiple-wavelength anomalous dispersion phasing at X-ray free-electron laser facilities.
  • Dual-Wavelength Diffraction Analysis: Facilitates analysis of complex dual-wavelength diffraction patterns arising in experiments at two-color XFELs.

Methodology:

Extension of the Sparse Pattern INDexing (SPIND) algorithm to two-color data; sparse-pattern indexing applied to patterns with as few as five peaks; algorithmic adjustments for identification and indexing of peaks across two wavelengths; validation on simulated and experimental protein-crystal diffraction datasets.

Topics

Details

License:
GPL-3.0
Programming Languages:
Python
Added:
1/18/2021
Last Updated:
2/21/2021

Operations

Publications

Li X, Li C, Liu H. <i>SPIND-TC</i>: an indexing method for two-color X-ray diffraction data. Acta Crystallographica Section A Foundations and Advances. 2020;76(3):369-375. doi:10.1107/s2053273320001916. PMID:32356787. PMCID:PMC7233013.

PMID: 32356787
PMCID: PMC7233013
Funding: - National Natural Science Foundation of China: 11575021, U1430237, U1930402 - National Science Foundation: 1565180