课题基金 / 基金详情

Molecular signatures of synergy

Molecular signatures of synergy
协同作用的分子特征
批准号:
238978-2010
负责人:
Hallett, Michael
金额:
$1.97万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2010
资助国家:
加拿大
项目状态:
已结题
起止时间:
2010-01-01 至 2011-12-31

项目摘要

项目成果

Hallett, Michael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
Drugs that act against individual molecular targets are often insufficient to combat fungal infections, multigenic diseases such as cancer, and multiple cell or tissue type diseases including immune and inflammatory disorders. Multicomponent therapies that impact several targets simultaneously are less prone to the development of drug resistance, and increase therapeutic efficacy. One of the major benefits of multicomponent therapies is the potential for synergistic effects: that is, the overall therapeutic benefit of the drug combination is greater than the sum of the effects of the individual agents. In particular, synergies between the constituent compounds can provide broader pharmacological windows and reduced toxicity. There are many challenges associated with the identification of molecular synergy and it appears that such synergies are rare. In fact, even for the well-studied yeast, only ~20 synergies are known. High-throughput screens can examine on the order of several thousand of compound pairs, but this represents a very small fraction of the exponential number of chemical combinations available. If we consider that there are >10 million compounds in screening libraries, it is unlikely that experimental techniques will be sufficient to completely survey the vast space of only pairwise synergies (~1013 pairs) in a cost effective and timely fashion. There is a clear need for an approach that winnows this space to a manageably large set of combinations that is enriched for synergistic combinations. We propose to construct a combined genomics and bioinformatics approach to identify and characterize molecular synergies. Using high-throughput gene expression profiles generated from yeast or human cell lines subjected to a single chemical perturbation, our de novo bioinformatics tool will predict pairs of chemical compounds which are highly likely to exhibit a pair-wise synergistic affect. Moreover, analysis of the downstream transcriptional changes caused by the pair of drugs, either in combination or individually, will provide fundamental insight into the molecular nature of synergy.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Bioinformatics Algorithms
  • 批准号:
    CRC-2017-00215
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $14.57万
  • 财政年份:
    2021
  • 负责人:
    Hallett, Michael
  • 依托单位:
Probabilistic approaches to optimize synthetic organisms
  • 批准号:
    RGPIN-2018-05085
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $5.03万
  • 财政年份:
    2020
  • 负责人:
    Hallett, Michael
  • 依托单位:
Bioinformatics algorithms
  • 批准号:
    CRC-2017-00215
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $14.57万
  • 财政年份:
    2020
  • 负责人:
    Hallett, Michael
  • 依托单位:
Bioinformatics algorithms
  • 批准号:
    CRC-2017-00215
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $14.57万
  • 财政年份:
    2019
  • 负责人:
    Hallett, Michael
  • 依托单位:
海外基金