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 library cctbx and structured 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 cellulose I-alpha/I-beta, alpha-chitin, and cellulose triacetate, 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 and serves as both a research and a teaching resource.