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PreprintCC BY-NC-ND 4.0arXiv

FDTBX - Computational Tools for Simulation of X-ray Fiber Diffraction Patterns from Atomic Coordinates

Abstract

Fiber diffraction is one of the few experimental techniques capable of resolving molecular structure in partially ordered, non-crystalline systems such as fibrous proteins, biopolymers and synthetic polymers. Because fiber diffraction patterns are complex, exhibiting paracrystalline order, packing defects and broad, overlapping reflections, their interpretation relies on model-based refinement, in which theoretical patterns simulated from candidate atomic models are iteratively compared with experiment. We present fdtbx, a modern, open and extensible Python toolbox for simulating X-ray fiber diffraction patterns directly from atomic coordinates. Built on the crystallographic library cctbx and designed for readability and multicore execution, fdtbx computes structure factors from a PDB model and constructs realistic reciprocal-space reflection profiles that incorporate the principal physical broadening mechanisms of fiber diffraction: finite crystallite size, orientational disorder (with Gaussian, Lorentzian and Voigt angular peak shapes) and paracrystalline (second-kind) lattice disorder in Hosemann's formulation. A per-reflection shell-quadrature scheme evaluates the required convolutions at arbitrary query points rather than on a fixed grid, giving direct control over the trade-off between accuracy and speed, and an analytic Ewald-projection routine maps each sampled reflection, with an appropriate Lorentz correction, onto a flat detector to produce a simulated pattern for direct comparison with measured images. We illustrate the toolbox on α-chitin, cellulose~Iα and Iβ, cellulose triacetate and A-form DNA, and outline a practical simulation workflow. By providing a transparent, well-documented and parallelizable implementation of the specialized algorithms of fiber diffraction, fdtbx lowers the barrier to reproducible model-based analysis.

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BibTeX
@misc{sikorski2026fdtbx,
  title = {{FDTBX - Computational Tools for Simulation of X-ray Fiber Diffraction Patterns from Atomic Coordinates}},
  author = {Pawel Sikorski},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2608.23245},
  eprint = {2608.23245},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.23245},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - UNPB
TI  - FDTBX - Computational Tools for Simulation of X-ray Fiber Diffraction Patterns from Atomic Coordinates
AU  - Pawel Sikorski
PY  - 2026
DA  - 2026/10/08
PB  - arXiv
DO  - 10.48550/arxiv.2608.23245
UR  - https://arxiv.org/abs/2608.23245
AB  - Fiber diffraction is one of the few experimental techniques capable of resolving molecular structure in partially ordered, non-crystalline systems such as fibrous proteins, biopolymers and synthetic polymers. Because fiber diffraction patterns are complex, exhibiting paracrystalline order, packing defects and broad, overlapping reflections, their interpretation relies on model-based refinement, in which theoretical patterns simulated from candidate atomic models are iteratively compared with experiment. We present fdtbx, a modern, open and extensible Python toolbox for simulating X-ray fiber diffraction patterns directly from atomic coordinates. Built on the crystallographic library cctbx and designed for readability and multicore execution, fdtbx computes structure factors from a PDB model and constructs realistic reciprocal-space reflection profiles that incorporate the principal physical broadening mechanisms of fiber diffraction: finite crystallite size, orientational disorder (with Gaussian, Lorentzian and Voigt angular peak shapes) and paracrystalline (second-kind) lattice disorder in Hosemann's formulation. A per-reflection shell-quadrature scheme evaluates the required convolutions at arbitrary query points rather than on a fixed grid, giving direct control over the trade-off between accuracy and speed, and an analytic Ewald-projection routine maps each sampled reflection, with an appropriate Lorentz correction, onto a flat detector to produce a simulated pattern for direct comparison with measured images. We illustrate the toolbox on α-chitin, cellulose~Iα and Iβ, cellulose triacetate and A-form DNA, and outline a practical simulation workflow. By providing a transparent, well-documented and parallelizable implementation of the specialized algorithms of fiber diffraction, fdtbx lowers the barrier to reproducible model-based analysis.
ER  -