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Abstract: The world is full of treasure troves of hoarded scientific samples - everything from pressed plants in herbaria and pinned insects in museum drawers to rocks from the Moon and asteroids in air-tight vaults. Generations of scientists have contributed to collecting, preserving and studying such specimens, amassing an immense amount of knowledge about our natural world and how it changes over time. As we develop ever more powerful technologies to explore them, these historical samples can lead us to new discoveries, as an international team of researchers recently found. Their work, published in Nature Communications, began with a 70-year-old viral sample tracked down in a low temperature freezer. This viral sample was of a Nudivirus that are economically important in agriculture, where they are used as biological agents to control some insect pests. However, they can be pests themselves, damaging large-scale crustacean and insect farming efforts. Using X-ray crystallography, the research team solved the lattice structure of a polyhedrin (occlusion body) from Nudiviridae, which adds to our knowledge of how viruses use protein self-assembly to protect themselves from the environment.

Open Access

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Abstract: We present an in-depth analysis of selected CASP15 targets, focusing on their biological and functional significance. The authors of the structures identify and discuss key protein features and evaluate how effectively these aspects were captured in the submitted predictions. While the overall ability to predict three-dimensional protein structures continues to impress, reproducing uncommon features not previously observed in experimental structures is still a challenge. Furthermore, instances with conformational flexibility and large multimeric complexes highlight the need for novel scoring strategies to better emphasize biologically relevant structural regions. Looking ahead, closer integration of computational and experimental techniques will play a key role in determining the next challenges to be unraveled in the field of structural molecular biology.

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Abstract: The work of this thesis focuses on the development of novel computational methods for the determination of protein structures through macromolecular X-ray crystallography (MX). The main focus of Chapters 2 and 3 is the development of alternative molecular replacement (MR) approaches in cases where no related structure is available as a search model. In Chapter 2, the performance of a library of helical ensembles created by clustering helical segments is explored. A 30% increase in the number of solutions obtained using these search models was observed when compared with the performance recorded for single-model ideal helices. In Chapter 3, SWAMP is presented: a novel pipeline for the solution of structures of transmembrane proteins. SWAMP includes a library of ensembles built by clustering commonly observed packings of transmembrane helical pairs in close contact. The search models in this library are then ranked based on the similarity between their observed residue contacts and the contacts predicted for the unknown structure. Results show that SWAMP is capable of detecting valid search models originating from unrelated solved structures solely exploiting this contact information. In Chapter 4, the main focus of the work presented remains MR, particularly, the importance of experimental data collection and the quality of the obtained diffraction data. Specifically, the relation between data completeness, the distribution of missing reflections and the quality of the maps obtained through MR is studied. For this purpose, a set of new metrics for the distribution of missing reflections in the reciprocal lattice are proposed, and a large-scale study to assess the effects of data incompleteness on MR outcome is carried out. Results revealed low resolution completeness as a major factor affecting the quality of the maps obtained through MR, highlighting the importance of low resolution reflections in the process of MR. Overall data completeness, signal-to-noise ratio and search model quality were also other factors observed to determine, in conjunction MR outcome. In Chapter 5, new metrics for model validation are presented. These metrics are based on the availability of accurate inter-residue distance predictions, which are compared with the distances observed in the emerging model. These metrics were fed into a support vector machine classifier that was trained to detect model errors based on historical data from the EM Validation Challenges. Further analysis of the possible register errors is done by performing an alignment of the predicted contact map and the map inferred from the contacts observed in the model. Regions of the model where the maximum contact overlap is achieved through a sequence register different to that observed in the model are flagged and the optimal sequence register can then be used to fix the register error. Results suggest that both the detection of model errors and the correction of sequence register errors is possible, even in challenging cases, through the use of the trained classifier in conjunction with the contact map alignment. The approach, implemented in ConKit, thus provides a new tool for protein structure validation that is orthogonal to existing methods. Lastly in Chapter 6 ConPlot is presented: a web-based application which uses the typically empty space near the residue contact map diagonal to display multiple coloured tracks representing other sequence-based predictions. The integration of these different sources of information enables researchers to easily analyse a variety of data simultaneously.

Open Access

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Abstract: The mounting of microcrystals (<10 µm) for single crystal cryo-crystallography presents a non-trivial challenge. Improvements in data quality have been seen for microcrystals with the development of beamline optics, beam stability and variable beam size focusing from submicron to microns, such as at the VMXm beamline at Diamond Light Source. Further improvements in data quality will be gained through improvements in sample environment and sample preparation. Microcrystals inherently generate weaker diffraction, therefore improving the signal-to-noise is key to collecting quality X-ray diffraction data and will predominantly come from reductions in background noise. Major sources of X-ray background noise in a diffraction experiment are from their interaction with the air path before and after the sample, excess crystallization solution surrounding the sample, the presence of crystalline ice and scatter from any other beamline instrumentation or X-ray windows. The VMXm beamline comprises instrumentation and a sample preparation protocol to reduce all these sources of noise. Firstly, an in-vacuum sample environment at VMXm removes the air path between X-ray source and sample. Next, sample preparation protocols for macromolecular crystallography at VMXm utilize a number of processes and tools adapted from cryoTEM. These include copper grids with holey carbon support films, automated blotting and plunge cooling robotics making use of liquid ethane. These tools enable the preparation of hundreds of microcrystals on a single cryoTEM grid with minimal surrounding liquid on a low-noise support. They also minimize the formation of crystalline ice from any remaining liquid surrounding the crystals. We present the process for preparing and assessing the quality of soluble protein microcrystals using visible light and scanning electron microscopy before mounting the samples on the VMXm beamline for X-ray diffraction experiments. We will also provide examples of good quality samples as well as those which require further optimization and strategies to do so.