Scaling and merging time-resolved pink-beam diffraction with variational inference

• Published in: Structural Dynamics
• Main Authors: Kara A. Zielinski, Cole Dolamore, Harrison K. Wang, Robert W. Henning, Mark A. Wilson, Lois Pollack, Vukica Srajer, Doeke R. Hekstra, Kevin M. Dalton
• Format: Article
• Language: English
• Published: AIP Publishing LLC and ACA 2024-11-01
• Online Access: http://dx.doi.org/10.1063/4.0000269

Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.