Cryo-electron microscopes routinely produce blurry 3D images of viruses and other large biomolecules, but existing software cannot turn those fuzzy maps into detailed atomic models. This matters because cryo-EM experiments are expensive and time-consuming, yet much of the data they generate goes to waste. When parts of a molecular image are too blurry—due to the instrument's limits or the molecule's own flexibility—current reconstruction algorithms simply give up. The result is an incomplete model that cannot support the biochemical research the experiment was designed for. The RECKON project will build software that fills in those blurry regions by incorporating additional information about the target, such as known chemical bonds and structural constraints. The team will test the method on a Qbeta bacteriophage—a virus that infects bacteria—producing the first complete atomistic model of the genome-loaded phage. If successful, the technique will let researchers extract far more scientific value from existing and future cryo-EM data, particularly for large viral assemblies. Virologists and molecular biologists will gain atomic-level views of targets that were previously out of reach, and the software toolkit could be adopted by both academic labs and industry groups working on structural biology.
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The project's aim is to develop a ready-to-use technique for all-atom structure reconstruction of biomolecules using poorly resolved cryo-electron microscopy (cryo-EM) data. The objectives include developing an intelligent protocol for dealing with low-resolution cryo-EM density, developing a toolkit of scripts or software modules for facilitating the process, and producing all-atom structure of a bacteriophage from newly-acquired cryo-EM data. The problem is highly relevant because the amount of published cryo-EM data growth rapidly, especially of large biomolecular objects such as whole viruses. Methodologies of reconstructing molecular structures from these data lag far behind. This strongly limits scientific output of such elaborate and expensive experiments. The ultimate goal of a cryo-EM experiment is an atomistic model of the target that can form the basis for further biochemical research. Currently, the goal can only be achieved if the collected cryo-EM density has high enough resolution to apply the existing reconstruction algorithms. However, often large regions with low resolution are present due to either instrumental or fundamental limitations, making commonly used algorithms to fail. Our methodology takes additional information on the target into account (chemical structure, biomolecular constraints, etc) in the reconstruction process. The intelligent algorithm to be developed will be able to deal with previously inaccessible regions of cryo-EM data and thus make it possible to reconstruct the target in its atomistic completeness. To test it, a cryo-EM measurement of a Qbeta bacteriophage will be done, which is an important biological target. The produced all-atom model of genome-loaded phage will be of high interest for virologists and molecular biologists, and the technique itself will attract attention of research groups specialising in cryo-EM, including industry.
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