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CCP4 Grant Renewal 2014-2019: Question-driven crystallographic data collection and advanced structure solution

ReferenceBB/L007037/1
Principal Investigator / Supervisor Dr Evgeny Krissinel
Co-Investigators /
Co-Supervisors		 Dr Ronan Keegan
Institution STFC - Laboratories
DepartmentScientific Computing Department
Funding typeResearch
Value (£) 407,684
StatusCompleted
TypeResearch Grant
Start date 01/04/2015
End date 31/03/2020
Duration60 months

Abstract

This proposal incorporates five related work packages. In WP1 we will track synchrotron-collected data through computational structure determination, to find whether the most useful data can be recognised a priori using established or novel metrics of data quality and consistency. We will then enable data collection software to communicate with pipelines and graphics programs to assess when sufficient data have been collected for a given scientific question, and so to prioritise further beamtime usage. We will also communicate extra information about diffraction data to structure determination programs, and so support the statistical models and algorithms being developed in WP4. WP2 will improve the key MR step of model preparation, especially from diverged, NMR, or ab initio models. One development will be to extend the size limit of ab initio search model generation by exploiting sequence covariance algorithms. In WP3 we will use our description of electron density maps as a field of control points to better use electron density or atomic models positioned by MR. Restrained manipulation of these points provides a low-order parameterisation of refinement decoupled from atomic models, and therefore suitable for highly diverged atomic models or EM-derived maps. We will extend this approach to characterise local protein mobility without the requirement of TLS for predefinition of rigid groups. In WP4 we will statistically model non-idealities in experimental data, including non isomorphism, spot overlap, and radiation damage. The resulting models, implemented in REFMAC, will be applied to refinement using data that are annotated by WP1 tools and tracked by WP0. WP0 will provide the tools to integrate the other WPs. For this, it will create a cloud environment where storage- and compute-resources can be utilised optimally, and where rich information can be passed among beamlines, pipelines, and graphics programs.

Summary

Proteins, DNA and RNA are the active machines of the cells which make up living organisms, and are collectively known as macromolecules. They carry out all of the functions that sustain life, from metabolism through replication to the exchange of information between a cell and its environment. They are coded for by a 'blueprint' in the form of the DNA sequence in the genome, which describes how to make them as linear strings of building blocks. In order to function, however, most macromolecules fold into a precise 3D structure, which in turn depends primarily on the sequence of building blocks from which they are made. Knowledge of the molecule's 3D structure allows us both to understand its function, and to design chemicals to interfere with it. Due to advances in molecular biology, a number of projects, including the Human Genome Project, have led to the determination of the complete DNA sequences of many organisms, from which we can now read the linear blueprints for many macromolecules. As yet, however, the 3D structure cannot be predicted from knowledge of the sequence alone. One way to "see" macromolecules, and so to determine their 3D structure, involves initially crystallising the molecule under investigation, and subsequently imaging it with suitable radiation. Macromolecules are too small to see with normal light, and so a different approach is required. With an optical microscope we cannot see objects which are smaller than the wavelength of light, roughly 1 millionth of a metre: Atoms are about 1000 times smaller than this. However X-rays have a wavelength about the same as the size of the atoms. For this reason, in order to resolve the atomic detail of macromolecular structure, we image them with X-rays rather than with visible light. The process of imaging the structures of macromolecules that have been crystallised is known as X-ray crystallography. X-ray crystallography is like using a microscope to magnify objects that are too small to be seen with visible light. Unfortunately X-ray crystallography is complicated because, unlike a microscope, there is no lens system for X-rays and so additional information and complex computation are required to reconstruct the final image. This information may come from known protein structures using the Molecular Replacement (MR) method, or from other sources including Electron Microscopy (EM). Once the structure is known, it is easier to pinpoint how macromolecules contribute to the living cellular machinery. Pharmaceutical research uses this as the basis for designing drugs to turn the molecules on or off when required. Drugs are designed to interact with the target molecule to either block or promote the chemical processes which they perform within the body. Other applications include protein engineering and carbohydrate engineering. The aim of this project is to improve the key computational tools needed to extract a 3D structure from X-ray crystallography experiments. It will provide continuing support to a Collaborative Computing Project (CCP4 first established in 1979), which has become one of the leading sources of software for this task. The project will help efficient and effective use to be made of the synchrotrons that make the X-rays that are used in most crystallographic experiments. It will provide more powerful tools to allow users to exploit information from known protein structures when the match to the unknown structure is very poor. It will also automate the use of information from electron microscopy, even when the crystal structure has been distorted by the process of growing the protein crystal. Finally, it will allow structures to be solved, even when poor quality and very small crystals are obtained.

Impact Summary

The generic importance of macromolecular crystallography in general and CCP4 in particular is provided in the Pathways to Impacts section. Macromolecular crystallography represents a mature field, where both experimental and computational techniques are expected to be mere instruments for obtaining atomic-scale images of biological macromolecules. A high level of instrumentation is reached at the data-production end, where modern X-ray installations, such as synchrotrons, produce high volumes of data in nearly automatic mode, and often allow researchers to conduct experiments remotely from their home labs. On computational side, high level of automation is achieved by combining many individual steps into sophisticated pipelines, which choose most appropriate structure solution pathway depending on the type of experiment, data quality and structure properties. As a result, over last decade, crystallographic software has grown considerably in size and complexity, which puts increasing maintenance burden on local support teams and researchers. In addition, advanced automation requires significant computation resources, not always available in small to medium size labs. A similar situation is observed in data management domain, where logistics is stressed by high volumes of data produced by both X-ray facilities and in the course of structure solution. Successful accomplishment of WP0 will have the following impacts: 1) Cloud-based resource for macromolecular computations will allow to seamlessly bridge data production and structure solution, and also provide users with crystallographic software and computational resources as a service. This is expected to simplify data logistics significantly and decrease software, data and hardware maintenance burden on small to medium size research groups. 2) A particular impact will be observed in the simplicity of using automatic structure solution software, where most of computational resources are required. Cloud computing will make automatic structure solution possible with the use of virtually any ultra-portable devices. For most users today, crystallographic computations at home start from merged data sets, processed at synchrotron's beamline. In five year perspective, most users will have the option to start manual work from nearly complete structures, obtained in automatic way in the cloud, without the necessity of moving significant volumes of data between synchrotrons and home setups. 3) An additional impact will be seen in the possibility to archive experimental data and structure solution results, as well as complete track of structure solution process, in the cloud. This will allow for the possibility to re-examine experimental results retrospectively, which is not always possible today. 4) A significant impact will be seen in high homogeneity of computational setup and data accessibility for cloud users with multiple workplaces, for example, home lab, synchrotron, on a visit to a colleague, at a conference or personal residence. No data transfer and exporting/importing CCP4 cloud projects with possible compatibility problems will be ever required for switching between work sites. 5) HTML5-based development is likely to have a very long lifetime and backward compatibility due to the exceptional role of HTML format in the World Wide Web. This will have a substantial positive impact on maintenance burden and resources needed for future developments.
Committee Research Committee D (Molecules, cells and industrial biotechnology)
Research TopicsStructural Biology
Research PriorityX – Research Priority information not available
Research Initiative X - not in an Initiative
Funding SchemeX – not Funded via a specific Funding Scheme
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