Data collection in macromolecular crystallography is subject to significant systematic errors that prevent successful data collection on many systems and, ultimately, limit the accuracy of resulting structures. Creating simulation technologies that can account for these errors will have significant impact on three fronts: 1) solving new structures by better accounting for radiation damage, which is responsible for 80% of failed anomalous phasing attempts, 2) improving multi-crystal averaging by simulating non-isomorphism, which will open the gateway to arbitrary gains in signal-to-noise, 3) discriminating hotly contested alternative interpretations such as the presence or absence of a bound ligand, by creating simulations with more realistic solvent models. To move towards ?damage-free data? from a synchrotron, we will start by calibrating radiation damage curves on model and DBP samples. Using these curves we will incorporate realistic 3D models of radiation damage to non-cuboid crystals (RADDOSE 3D) into our diffraction image simulator (MLFSOM) to yield a 3D Dose Distribution and Illumination map along the crystal. This will result in a new generation of wavelength- dependent absorption factors for the crystal to complement existing absorption corrections. At the beamline, we will measure a 3D map of the crystal using cone beam online x-ray absorption radiography and a 2D map of the beam profile. These advances will allow us to generate zero-dose extrapolation values, in an open format, that account for experimental crystal and beam geometry. To improve multi-crystal averaging, we will begin by characterizing how non-isomorphism varies as a function of humidity, radiation damage, and functional state. By updating the classic ?Crick and Magdoff? simulations of non-isomorphism with increasing complexity, we will develop a singular value decomposition approach to parameterize non-isomorphism. Using the corrections derived from this analysis, we will correct the non-isomorphism present in multi-crystal experiments, enabling the determination of novel structures, including those collected using serial crystallography at next-generation light sources. To enable enhanced simulation for robust interpretation of experimental data, we will leverage new solvent models in macromolecular crystallography and small angle X- ray scattering. Our work will create standard protocols for comparing solvent density to alternative interpretations and to quantitatively assess how likely each simulated situation is compared to the real macromolecular crystallography or SAXS data. In addition to distinguishing between different interpretations of the experimental data, improving solvent models will enhance understanding of how macromolecules influence and interact with other molecules near their surface. Collectively, we expect the benefits of eliminating these critical systematic errors be transformative to both methods development and functional studies.
Data collection in macromolecular crystallography is subject to significant systematic errors that prevent successful soilution on many systems and, ultimately, limit the accuracy of resulting structures. Creating simulation technologies that can account for these errors will have significant impact on three fronts: 1) solving new structures by better accounting for radiation damage, which is responsible for 80% of failed anomalous phasing attempts, 2) improving multi-crystal averaging by simulating non-isomorphism, which will open the gateway to arbitrary gains in signal-to-noise, 3) discriminating hotly contested alternative interpretations such as the presence or absence of a bound ligand, by creating simulations with more realistic solvent models.
