课题基金 / 基金详情

Using Stream Computing on Mainstream PC Graphics Hardware for Fast de novo Protein Structure Prediction

Using Stream Computing on Mainstream PC Graphics Hardware for Fast de novo Protein Structure Prediction
在主流 PC 图形硬件上使用流计算进行快速从头蛋白质结构预测
批准号:
BB/E023533/1
负责人:
David Jones
金额:
$12.74万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2007
资助国家:
英国
项目状态:
已结题
起止时间:
2007 至 --

项目摘要

项目成果

David Jones的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Most genes are designed to code for specific proteins which have useful functions in the body. Proteins are essentially strings of simpler molecules, called amino acids and these strings can self-assemble into a complex 3-D structure as soon as the protein is formed by the protein-making machinery (ribosomes) in the cell. It is this unique structure which determines the precise chemical function of the protein (i.e. what is does in the cell and how it does it). By firing X-rays at crystallised proteins, scientists can determine their structure, but this process can take many months or even years. With hundreds of thousands of proteins for which the native structure is unknown, it is not surprising that scientists want to find a clever shortcut to working out the structure of proteins. We, like many other scientists have been trying to 'crack the code' of protein structure i.e. working out the rules which govern how the protein finds its unique structure and then trying to program a computer with these rules to allow scientists to quickly 'predict' what the structure of their protein of interest might be. At UCL we have been pioneering a number of approaches to predicting the structure of a protein from amino acid sequence. One of the most successful assembles new protein structures from small pieces of other proteins - a little bit like building a model from Lego(TM) parts. Although we have demonstrated a number of successful attempts at predicting protein structure, the technology is not readily available to bench scientists due to the fact that a lot of computer power is needed to carry out the calculations. One interesting new development that may allow any scientist to run these protein folding simulations on his own desktop PC is the use of graphics chips to run the simulations many times faster than the PC can on its own. Normally graphics chips allow users to run 3-D games or visualise 3-D environments at very high speed, but recently it has become apparent that these chips are capable of doing a lot more than just drawing 3-D objects. Our calculations indicate that the latest 3-D graphics boards available in the high street for less than 300 pounds are able to do as much work as 30 normal PCs. If this experiment is successful, any scientist with a cheap PC and graphics card will be able to run our software without needing access to an expensive supercomputer cluster.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1371/journal.pone.0092197
发表时间: 2014
期刊: PloS one
影响因子: 3.7
作者: [Kosciolek T, Jones DT]
通讯作者: Jones DT
DOI: 10.1093/nar/gkq427
发表时间: 2010-07
期刊: Nucleic acids research
影响因子: 14.9
作者: [Buchan DW, Ward SM, Lobley AE, Nugent TC, Bryson K, Jones DT]
通讯作者: Jones DT
Open Access Block Award 2024 - The Francis Crick Institute
  • 批准号:
    EP/Z531844/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $10.24万
  • 财政年份:
    2024
  • 负责人:
    David Jones
  • 依托单位:
Open Access Block Award 2023 - The Francis Crick Institute
  • 批准号:
    EP/Y530360/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $6.67万
  • 财政年份:
    2023
  • 负责人:
    David Jones
  • 依托单位:
Open Access Block Award 2022 - The Francis Crick Institute
  • 批准号:
    EP/X526381/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $4.85万
  • 财政年份:
    2022
  • 负责人:
    David Jones
  • 依托单位:
Exploiting Differentiable Programming Models For Protein Structure Prediction And Modelling
  • 批准号:
    BB/W008556/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $51.79万
  • 财政年份:
    2022
  • 负责人:
    David Jones
  • 依托单位:
国内基金
海外基金
基于LAMOST和GAIA的Magellanic Stream化学-动力学研究
  • 批准号:
    11773033
  • 项目类别:
    面上项目
  • 资助金额:
    64.0万元
  • 批准年份:
    2017
  • 负责人:
    张岚
  • 依托单位: