An iterative refinement method combining detector geometry optimization and diffraction model refinement in serial femtosecond crystallography

Abstract

Recent advances in serial femtosecond crystallography (SFX) using X-ray free electron lasers (XFELs) have facilitated accurate structure determination for biological macromolecules. However, given the many fluctuations inherent in SFX, the acquisition of SFX data of sufficiently high quality still remains challenging. Aimed at enhancing the accuracy of SFX data, this study proposes an iterative refinement method to optimally match pairs of the observed and predicted reflections on the detector plane. This method features a combination of detector geometry optimization and diffraction model refinement in an alternate manner, concomitant with a cycle-by-cycle peak selection procedure. To demonstrate whether this iterative method is convergent and feasible, both numerical simulations and experimental tests have been performed. The results reveal that this method can gradually improve overall quality of the integrated SFX data and therefore accelerate the convergence of Monte Carlo integration, while simultaneously suppressing correlations inherent in certain parameters and precluding outliers to some extent during the refinement. We have demonstrated that our iterative refinement method is applicable to both simulated and experimental SFX data. It is expected that this method could provide meaningful insights into the refinement of SFX data and take the step forward toward more accurate Monte Carlo integration.