60 research outputs found
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SAD phasing of XFEL data depends critically on the error model.
A nonlinear least-squares method for refining a parametric expression describing the estimated errors of reflection intensities in serial crystallographic (SX) data is presented. This approach, which is similar to that used in the rotation method of crystallographic data collection at synchrotrons, propagates error estimates from photon-counting statistics to the merged data. Here, it is demonstrated that the application of this approach to SX data provides better SAD phasing ability, enabling the autobuilding of a protein structure that had previously failed to be built. Estimating the error in the merged reflection intensities requires the understanding and propagation of all of the sources of error arising from the measurements. One type of error, which is well understood, is the counting error introduced when the detector counts X-ray photons. Thus, if other types of random errors (such as readout noise) as well as uncertainties in systematic corrections (such as from X-ray attenuation) are completely understood, they can be propagated along with the counting error, as appropriate. In practice, most software packages propagate as much error as they know how to model and then include error-adjustment terms that scale the error estimates until they explain the variance among the measurements. If this is performed carefully, then during SAD phasing likelihood-based approaches can make optimal use of these error estimates, increasing the chance of a successful structure solution. In serial crystallography, SAD phasing has remained challenging, with the few examples of de novo protein structure solution each requiring many thousands of diffraction patterns. Here, the effects of different methods of treating the error estimates are estimated and it is shown that using a parametric approach that includes terms proportional to the known experimental uncertainty, the reflection intensity and the squared reflection intensity to improve the error estimates can allow SAD phasing even from weak zinc anomalous signal
Gold Standard for macromolecular crystallography diffraction data
Macromolecular crystallography (MX) is the dominant means of determining the three-dimensional structures of biological macromolecules. Over the last few decades, most MX data have been collected at synchrotron beamlines using a large number of different detectors produced by various manufacturers and taking advantage of various protocols and goniometries. These data came in their own formats: sometimes proprietary, sometimes open. The associated metadata rarely reached the degree of completeness required for data management according to Findability, Accessibility, Interoperability and Reusability (FAIR) principles. Efforts to reuse old data by other investigators or even by the original investigators some time later were often frustrated. In the culmination of an effort dating back more than two decades, a large portion of the research community concerned with high data-rate macromolecular crystallography (HDRMX) has now agreed to an updated specification of data and metadata for diffraction images produced at synchrotron light sources and X-ray free-electron lasers (XFELs). This 'Gold Standard' will facilitate the processing of data sets independent of the facility at which they were collected and enable data archiving according to FAIR principles, with a particular focus on interoperability and reusability. This agreed standard builds on the NeXus/HDF5 NXmx application definition and the International Union of Crystallography (IUCr) imgCIF/CBF dictionary, and it is compatible with major data-processing programs and pipelines. Just as with the IUCr CBF/imgCIF standard from which it arose and to which it is tied, the NeXus/HDF5 NXmx Gold Standard application definition is intended to be applicable to all detectors used for crystallography, and all hardware and software developers in the field are encouraged to adopt and contribute to the standard
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Photoreversible interconversion of a phytochrome photosensory module in the crystalline state.
A major barrier to defining the structural intermediates that arise during the reversible photointerconversion of phytochromes between their biologically inactive and active states has been the lack of crystals that faithfully undergo this transition within the crystal lattice. Here, we describe a crystalline form of the cyclic GMP phosphodiesterases/adenylyl cyclase/FhlA (GAF) domain from the cyanobacteriochrome PixJ in Thermosynechococcus elongatus assembled with phycocyanobilin that permits reversible photoconversion between the blue light-absorbing Pb and green light-absorbing Pg states, as well as thermal reversion of Pg back to Pb. The X-ray crystallographic structure of Pb matches previous models, including autocatalytic conversion of phycocyanobilin to phycoviolobilin upon binding and its tandem thioether linkage to the GAF domain. Cryocrystallography at 150 K, which compared diffraction data from a single crystal as Pb or after irradiation with blue light, detected photoconversion product(s) based on Fobs - Fobs difference maps that were consistent with rotation of the bonds connecting pyrrole rings C and D. Further spectroscopic analyses showed that phycoviolobilin is susceptible to X-ray radiation damage, especially as Pg, during single-crystal X-ray diffraction analyses, which could complicate fine mapping of the various intermediate states. Fortunately, we found that PixJ crystals are amenable to serial femtosecond crystallography (SFX) analyses using X-ray free-electron lasers (XFELs). As proof of principle, we solved by room temperature SFX the GAF domain structure of Pb to 1.55-Å resolution, which was strongly congruent with synchrotron-based models. Analysis of these crystals by SFX should now enable structural characterization of the early events that drive phytochrome photoconversion
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Comparing serial X-ray crystallography and microcrystal electron diffraction (MicroED) as methods for routine structure determination from small macromolecular crystals.
Innovative new crystallographic methods are facilitating structural studies from ever smaller crystals of biological macromolecules. In particular, serial X-ray crystallography and microcrystal electron diffraction (MicroED) have emerged as useful methods for obtaining structural information from crystals on the nanometre to micrometre scale. Despite the utility of these methods, their implementation can often be difficult, as they present many challenges that are not encountered in traditional macromolecular crystallography experiments. Here, XFEL serial crystallography experiments and MicroED experiments using batch-grown microcrystals of the enzyme cyclophilin A are described. The results provide a roadmap for researchers hoping to design macromolecular microcrystallography experiments, and they highlight the strengths and weaknesses of the two methods. Specifically, we focus on how the different physical conditions imposed by the sample-preparation and delivery methods required for each type of experiment affect the crystal structure of the enzyme
Mapping protein dynamics at high spatial resolution with temperature-jump X-ray crystallography
温度による酵素の構造変化を分子動画撮影 様々な生体高分子のダイナミクスを決定する新たな方法論. 京都大学プレスリリース. 2023-09-19.Understanding and controlling protein motion at atomic resolution is a hallmark challenge for structural biologists and protein engineers because conformational dynamics are essential for complex functions such as enzyme catalysis and allosteric regulation. Time-resolved crystallography offers a window into protein motions, yet without a universal perturbation to initiate conformational changes the method has been limited in scope. Here we couple a solvent-based temperature jump with time-resolved crystallography to visualize structural motions in lysozyme, a dynamic enzyme. We observed widespread atomic vibrations on the nanosecond timescale, which evolve on the submillisecond timescale into localized structural fluctuations that are coupled to the active site. An orthogonal perturbation to the enzyme, inhibitor binding, altered these dynamics by blocking key motions that allow energy to dissipate from vibrations into functional movements linked to the catalytic cycle. Because temperature jump is a universal method for perturbing molecular motion, the method demonstrated here is broadly applicable for studying protein dynamics
Finding Our Way in the Dark Proteome
The traditional structure-function paradigm has provided significant insights for well-folded proteins in which structures can be easily and rapidly revealed by X-ray crystallography beamlines. However approximately one third of the human proteome are comprised of intrinsically disordered proteins and regions (IDPs/IDRs) that do not adopt a dominant well-folded structure, and therefore remain “unseen” by traditional structural biology methods. This Perspective article considers the challenges raised by the “Dark Proteome”, in which determining the diverse conformational substates of IDPs in their free states, in encounter complexes of bound states, and in complexes retaining significant disorder, requires an unprecedented level of integration of multiple and complementary solution-based experiments that are analyzed with state-of-the art molecular simulation, Bayesian probabilistic models, and high throughput computation. We envision how these diverse experimental and computational tools can work together through formation of a “computational beamline” that will allow key functional features to be identified in IDP structural ensembles
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Understanding and Improving Designed Enzymes by Computer Simulations
AbstractUnderstanding and Improving Designed Enzymes by Computer SimulationsBy Asmit BhowmickDoctor of Philosophy in Chemical EngineeringUniversity of California, BerkeleyProfessor Teresa Head-Gordon, ChairThe ability to control for protein structure, electrostatics and dynamical motions is a fundamental problem that limits our ability to rationally design catalysts for new chemical reactions not known to have a natural biocatalyst. Current computational approaches for de novo enzyme design seek to engineer a small catalytic construct into an accommodating protein scaffold as exemplified by the Rosetta strategy. Here we consider 3 designed enzymes for the Kemp elimination reaction (KE07, KE70 and KE15) that showed minimal catalytic activity. KE07 and KE70 were subsequently improved by 2 orders of magnitude in catalytic efficiency by directed evolution and highlighted the shortcomings of the design process. This work studies two keys issues plaguing the designs – side chain conformational variability and electrostatics.For the first part, a new Monte Carlo sampling method was developed that uses a physical forcefield and coupled with backbone variability and a backbone dependent rotamer library. Using transition state theory with energies/entropies calculated from Monte Carlo simulations, it is shown that in both KE07 and KE70, the initial design was over-optimized to stabilize the enzyme-substrate complex. Mutations introduced by directed evolutions led to destabilization of the enzyme-substrate complex and stabilization of the transition state. Furthermore, analysis of residue correlations via mutual information yielded hotspots, several of which were mutations during directed evolution. Laboratory mutations of these hotspots in the best variant of KE07 led to a drop in catalytic performance, demonstrating their importance. The metrics identified in KE07/KE70 studies were used to predict mutations to improve enzyme KE15 that had not been improved prior to this study. Several mutants, all predicted through computer simulations have now yielded better catalytic activity in the laboratory with the best one 10-fold better than the starting enzyme. In order to quantify the role of electrostatics, a new method was developed using the AMOEBA polarizable forcefield that allowed splitting the contribution of electric field at the substrate by residues and solvent. The improvement in KE07 series could be tracked directly through changes in electric field at the substrate. In comparison, KE70 did not show a significant shift in electrostatic field, suggesting other factors like substrate binding may have been the reason for enhancement of activity. However, the common theme in both enzymes was the lack of participation (and in fact detrimental role) of the scaffold in the reaction. Future design efforts would benefit from an expanded theozyme and careful selection of scaffold based on electrostatic properties. Generating efficient biocatalysts without using laboratory directed evolution would be an inflection point in the field of enzyme design. This work is a step in that direction
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