Improving experimental phases for strong reflections prior to density modification.

Experimental phasing of diffraction data from macromolecular crystals involves deriving phase probability distributions. These distributions are often bimodal, making their weighted average, the centroid phase, improbable, so that electron-density maps computed using centroid phases are often non-interpretable. Density modification brings in information about the characteristics of electron density in protein crystals. In successful cases, this allows a choice between the modes in the phase probability distributions, and the maps can cross the borderline between non-interpretable and interpretable. Based on the suggestions by Vekhter [Vekhter (2005), Acta Cryst. D61, 899-902], the impact of identifying optimized phases for a small number of strong reflections prior to the density-modification process was investigated while using the centroid phase as a starting point for the remaining reflections. A genetic algorithm was developed that optimizes the quality of such phases using the skewness of the density map as a target function. Phases optimized in this way are then used in density modification. In most of the tests, the resulting maps were of higher quality than maps generated from the original centroid phases. In one of the test cases, the new method sufficiently improved a marginal set of experimental SAD phases to enable successful map interpretation. A computer program, SISA, has been developed to apply this method for phase improvement in macromolecular crystallography

Resolving polymorphs and radiation-driven effects in microcrystals using fixed-target serial synchrotron crystallography

The ability to determine high-quality, artefact-free structures is a challenge in micro-crystallography, and the rapid onset of radiation damage and requirement for a high-brilliance X-ray beam mean that a multi-crystal approach is essential. However, the combination of crystal-to-crystal variation and X-ray-induced changes can make the formation of a final complete data set challenging; this is particularly true in the case of metalloproteins, where X-ray-induced changes occur rapidly and at the active site. An approach is described that allows the resolution, separation and structure determination of crystal polymorphs, and the tracking of radiation damage in microcrystals. Within the microcrystal population of copper nitrite reductase, two polymorphs with different unit-cell sizes were successfully separated to determine two independent structures, and an X-ray-driven change between these polymorphs was followed. This was achieved through the determination of multiple serial structures from microcrystals using a high-throughput high-speed fixed-target approach coupled with robust data processing

Massive Scale Data Analytics at LCLS-II

The increasing volumes of data produced at light sources such as the Linac Coherent Light Source (LCLS) enable the direct observation of materials and molecular assemblies at the length and timescales of molecular and atomic motion. This exponential increase in the scale and speed of data production is prohibitive to traditional analysis workflows that rely on scientists tuning parameters during live experiments to adapt data collection and analysis. User facilities will increasingly rely on the automated delivery of actionable information in real time for rapid experiment adaptation which presents a considerable challenge for data acquisition, data processing, data management, and workflow orchestration. In addition, the desire from researchers to accelerate science requires rapid analysis, dynamic integration of experiment and theory, the ability to visualize results in near real-time, and the introduction of ML and AI techniques. We present the LCLS-II Data System architecture which is designed to address these challenges via an adaptable data reduction pipeline (DRP) to reduce data volume on-thefly, online monitoring analysis software for real-time data visualization and experiment feedback, and the ability to scale to computing needs by utilizing local and remote compute resources, such as the ASCR Leadership Class Facilities, to enable quasi-real-time data analysis in minutes. We discuss the overall challenges facing LCLS, our ongoing work to develop a system responsive to these challenges, and our vision for future developments

Mapping the conformational landscape of a dynamic enzyme by multitemperature and XFEL crystallography

Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its ca