ABI Innovation: New Algorithms for Biological X-ray Free Electron Laser Data

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Major advances in structural biology have often resulted from novel approaches to data collection and analysis. Historically, increasingly powerful X-ray sources led to great leaps in the ability to obtain information about structures of biomolecules, which is critically related to the molecules' biological function. The first X-ray free electron laser (XFEL) came online in 2009 at SLAC National Accelerator Laboratory, granting researchers the unprecedented ability to see the detailed atomic arrangements in, and movements of, biological molecules in their natural state (i.e. warm and wet). Serial femtosecond crystallography (SFX), a novel extension of crystallography making use of the extreme flux and ultra-short duration of XFEL pulses, has produced new insights into fundamentally important processes such as photosynthesis, helping to understand how plants and bacteria convert sunlight into energy and create the oxygen we breathe, making life possible on earth, as well as improving human health by aiding pharmaceutical drug design, for example guiding improvements in pain killers and blood pressure regulators. However, XFEL experiments with biological targets typically require very large volumes of data and thus a correspondingly large volume of scarce, precious protein, to obtain high-resolution molecular structures. Furthermore, XFEL facilities typically host only one or two experiments simultaneously, and only two XFELs presently serve the global user community, while more will be coming online in 2017. The number of biological targets that can be studied and the rate of discoveries can be dramatically increased through the development of innovative, advanced algorithms that reduce the number of necessary measurements and extract more information from the samples by fully exploiting the information content that is unique to XFEL diffraction, and by extending XFEL use to uncrystallized targets. This project has three main objectives: (a) explore algorithms for improving data accuracy in XFEL serial femtosecond crystallography through modeling and optimization (beyond the Monte Carlo approach for data merging), (b) explore and develop novel phasing methods which exploit the full spatial coherence of the XFEL for 2D and 3D nanocrystals, and (c) develop structure-determination methods that can be applied to samples that cannot be crystallized, through XFEL fast solution scattering (FSS). FSS can provide dynamic structural information from "snapshot" diffraction from particles that can be studied dynamically in solution, broadening the range of samples suitable for XFELs. Further development of this approach to include statistical intensity correlations that are unique to XFEL measurements can potentially displace the need for crystal growth altogether. These new algorithms, which will be freely available to the scientific community, will increase accessibility and applicability of the revolutionary capabilities of XFELs for biological imaging by significantly decreasing the amount of sample, data and experimental time (and therefore overall costs) necessary to obtain high-resolution structures. Thus the project will contribute directly to improved understanding of the fundamental biomolecular mechanisms by providing time-resolved images of molecular machines at work. The results of this project will be available at http://www.public.asu.edu/~nzatsepi