|Keywords:||X-ray; free-electron laser; XFEL; diffraction analysis; structure determination; nanocrystal; molecular dynamics; GROMACS; biomolecular imaging; ubiquitin; trajectory; explosion; Natural Sciences; Biological Sciences; Biophysics; Naturvetenskap; Biologiska vetenskaper; Biofysik; Civilingenjörsprogrammet i molekylär bioteknik; Molecular Biotechnology Engineering Programme|
|Full text PDF:||http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-231009|
X-ray crystallography has been around for 100 years and remains the preferred technique for solving molecular structures today. However, its reliance on the production of sufficiently large crystals is limiting, considering that crystallization cannot be achieved for a vast range of biomolecules. A promising way of circumventing this problem is the method of serial femtosecond imaging of single-molecules or nanocrystals utilizing an X-ray free-electron laser. In such an approach, X-ray pulses brief enough to outrun radiation damage and intense enough to provide usable diffraction signals are employed. This way accurate snapshots can be collected one at a time, despite the sample molecule exploding immediately following the pulse due to extreme ionization. But as opposed to in conventional crystallography, the spatial orientation of the molecule at the time of X-ray exposure is generally unknown. Consequentially, assembling the snapshots to form a three-dimensional representation of the structure of interest is cumbersome, and normally tackled using algorithms to analyze the diffraction patterns. Here we explore the idea that the explosion data can provide useful insights regarding the orientation of ubiquitin, a eukaryotic regulatory protein. Through two series of molecular dynamics simulations totaling 588 unique explosions, we found that a majority of the carbon atoms prevalent in ubiquitin are directionally limited in their respective escape paths. As such we conclude it to be theoretically possible to orient a sample with known structure based on its explosion pattern. Working with an unknown sample, we suggest these discoveries could be applicable in tandem with X-ray diffraction data to optimize image assembly.