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Integrated computational and synthetic tools to drive the discovery of orthosteric protein-protein interaction inhibitors

Integrated computational and synthetic tools to drive the discovery of orthosteric protein-protein interaction inhibitors
集成计算和合成工具来推动正位蛋白质-蛋白质相互作用抑制剂的发现
批准号:
EP/N013573/1
负责人:
Andrew Wilson
金额:
$350.6万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

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中文摘要
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英文摘要
Small molecule drugs continue to dominate our collective ability to treat disease. However, the pharmaceutical industry faces challenges on several fronts, and increasing productivity has been framed as the grand challenge for the sector. Against a background of increasingly cost-constrained healthcare systems, the cost of launching new drugs is increasingly high (recently estimated at £1.8 Bn for each new drug!). In order to improve productivity in drug discovery, it is necessary to develop innovative new medicines that address currently unmet medical needs. Protein-protein interactions represent a significant untapped, but challenging, opportunity for treating diseases including cancer, inflammatory disease, cardiovascular disease and infection.Drugs function by binding to a protein target within the body. Most existing small molecule drugs bind to well-defined pockets in proteins - analogous to a key fitting into a lock. In stark contrast, the design of drugs to inhibit protein-protein interactions generally requires a fundamentally different type of interaction of the drug with its protein target - analogous to a hand gripping a ball. Thus, the development of effective drugs that target protein-protein interactions raises new challenges that need to be met in future drug discovery. This programme will develop new tools and understanding that will facilitate future drug discovery against protein-protein interactions.We will develop computational tools to classify protein-protein interactions according to their underlying 3D structure and the probability that they can be inhibited using small molecules. We will then exploit these computational tools to design classes of small molecule that can be prepared readily using state-of-the-art synthetic methods, and that are predisposed to target different types of protein-protein interaction. The resulting small molecule inhibitors will be made available to biological researchers to help understand the role of protein-protein interactions in disease. In addition, the new tools will be made accessible to the research community to facilitate the early-stage discovery of small molecule drugs that target protein-protein interactions. The programme will benefit from the input of major pharmaceutical companies, smaller drug discovery companies, a not-for-profit drug discovery organisation, and international academics. The involvement of a wide range of experts is essential because of the increasing trend for early stage drug discovery to be conducted by a range of organisations (both industry and academic), especially for more challenging target classes. Thus, together with wider research community engagement, we will ensure that the required future capabilities for early-stage drug discovery against protein-protein interactions are met.
期刊论文(10)
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会议论文
Author Correction: Photocatalytic proximity labelling of MCL-1 by a BH3 ligand
作者更正:BH3 配体对 MCL-1 进行光催化邻近标记
DOI: 10.1038/s42004-019-0243-z
发表时间: 2019
期刊: Communications Chemistry
影响因子: 5.9
作者: [Beard H]
通讯作者: Beard H
Peptidomimetic inhibitors of ß-strand mediated protein-protein interactions: tuning binding affinity of intrinsically disordered sequences by covalent backbone modification
β-链介导的蛋白质-蛋白质相互作用的拟肽抑制剂:通过共价主链修饰调节本质上无序序列的结合亲和力
DOI: 10.26434/chemrxiv-2023-xglb4
发表时间: 2023
期刊:
影响因子: --
作者: [Cawood E]
通讯作者: Cawood E
Photocatalytic Proximity Labelling of MCL-1 by a BH3 Ligand
BH3 配体对 MCL-1 的光催化邻近标记
DOI: 10.26434/chemrxiv.7862006.v1
发表时间: 2019
期刊:
影响因子: --
作者: [Beard H]
通讯作者: Beard H
Affinity-guided chemical probes for the study of protein interactions
用于研究蛋白质相互作用的亲和引导化学探针
DOI: --
发表时间: 2018
期刊:
影响因子: --
作者: [Beard, H.A.]
通讯作者: Beard, H.A.
6
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    • 项目类别:
      Research Grant
    • 资助金额:
      $16.84万
    • 财政年份:
      2023
    • 负责人:
      Andrew Wilson
    • 依托单位:
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      BB/V008412/2
    • 项目类别:
      Research Grant
    • 资助金额:
      $25.01万
    • 财政年份:
      2023
    • 负责人:
      Andrew Wilson
    • 依托单位:
    Deciphering the function of intrinsically disordered protein regions in a cellular context
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      BB/V003577/2
    • 项目类别:
      Research Grant
    • 资助金额:
      $253.52万
    • 财政年份:
      2023
    • 负责人:
      Andrew Wilson
    • 依托单位:
    CAREER: New Frontiers in Bayesian Deep Learning
    • 批准号:
      2145492
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $48.52万
    • 财政年份:
      2022
    • 负责人:
      Andrew Wilson
    • 依托单位:
    国内基金
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    物体运动对流场扰动的数学模型研究
    • 批准号:
      51072241
    • 项目类别:
      专项基金项目
    • 资助金额:
      10.0万元
    • 批准年份:
      2010
    • 负责人:
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    • 依托单位:
    Computational Methods for Analyzing Toponome Data