CCP4: Low resolution complexes handling difficult data; empowering structural biologists and supporting UK structural biology
CCP4: Low resolution complexes handling difficult data; empowering structural biologists and supporting UK structural biology
批准号:
BB/F020805/1
负责人:
Martyn Winn
金额:
$159.17万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2008
资助国家:
英国
项目状态:
已结题
起止时间:
2008 至 --
中文摘要
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英文摘要
Structural Biology is a powerful tool for analysing biological molecules. In essence it locates the atoms that make up proteins and other biomolecules. It is used in basic science to define the 3D structures of such molecules as the ribosome, ion channels and complex protein assemblies such as ATPase. Once a 3D 'model' of all the atoms in the biological model is available, it is possible to make deductions about how the molecule functions within the organism. This knowledge has corresponding applications in controlling that function, often leading to medical advances in drug design, better understanding of biological and feedback systems in the natural environment, new approaches in chemical engineering, and many other benefits. The process of 'solving' the structure involves first obtaining crystals and then exposing these to X-rays: this is equivalent to using a very powerful microscope and allows us to 'see' individual atoms. Getting crystals is in itself very demanding and involves a lot of skill and scientific insight. There is an additional problem in using X-rays in that there is no lens system for the microscope. This means that indirect, so-called diffraction images of the crystal are recorded. The process of extracting data from these images and proceeding to a final structure is computationally intensive and requires an entirely different set of skills from those of the biologist. Developing new computer methods and crucially embedding them in robust easy-to-use software will transform structural biology from a labour intensive highly technical process to a routine tool in biology. The main focus of this grant is on the computational process of solving 3D structures. CCP4 is a project which has collected, developed, packaged and distributed software for the many stages of this process, acting as a focus for methods development for over 25 years and making software available to both Academic and Industrial teams working in this area. It is an excellent example of technology transfer of basic science into a major UK Industry: Pharmaceutical development. The problem cannot yet be said to be totally solved. Biologists firstly are tackling more and more difficult structures, which require novel techniques. In addition, they are solving large number of sometimes related structures, such as a series of mutants and complexes, where automated high throughput is vital and systematic record keeping is essential. This proposal is focussed on enabling these developments.
期刊论文(10)
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科研奖励(0)
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DOI:
10.1107/s2059798323003595
发表时间:
2023-06-01
期刊:
Acta crystallographica. Section D, Structural biology
影响因子:
--
作者:
[]
通讯作者:
Crystallization and preliminary X-ray characterization of the 2,4'-dihydroxyacetophenone dioxygenase from Alcaligenes sp. 4HAP.
产碱杆菌 2,4-二羟基苯乙酮双加氧酶的结晶和初步 X 射线表征。
DOI:
10.1107/s2053230x14009649
发表时间:
2014
期刊:
Acta crystallographica. Section F, Structural biology communications
影响因子:
--
作者:
[Beaven G]
通讯作者:
Beaven G
DOI:
10.1107/s1399004714015053
发表时间:
2014-09
期刊:
Acta crystallographica. Section D, Biological crystallography
影响因子:
--
作者:
[Keegan R, Lebedev A, Erskine P, Guo J, Wood SP, Hopper DJ, Rigby SE, Cooper JB]
通讯作者:
Cooper JB
DOI:
10.1107/s0021889810001846
发表时间:
2010
期刊:
Journal of Applied Crystallography
影响因子:
6.1
作者:
[Lovelace J]
通讯作者:
Lovelace J
DOI:
10.1107/s0907444911001314
发表时间:
2011-04
期刊:
Acta crystallographica. Section D, Biological crystallography
影响因子:
--
作者:
[Murshudov GN, Skubák P, Lebedev AA, Pannu NS, Steiner RA, Nicholls RA, Winn MD, Long F, Vagin AA]
通讯作者:
Vagin AA
共 9 条
Particle classification and identification in cryoET of crowded cellular environments
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-
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依托单位:
Intermediate-to-low resolution feature detection in cryoEM maps using cascaded neural networks
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依托单位:
Automated de novo building of protein models into electron microscopy maps
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财政年份:2017
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依托单位:
Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM): Supporting the software infrastructure for cryoEM techniques.
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Towards a Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM) and bridging the gaps between structure determination methods
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依托单位:
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项目类别:Research Grant
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资助金额:$4.25万
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财政年份:2010
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负责人:Martyn Winn
-
依托单位:
国内基金
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