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Multiscale Computer Modeling to Evaluate Protein-Ligand Off-Target Interactions

Multiscale Computer Modeling to Evaluate Protein-Ligand Off-Target Interactions
用于评估蛋白质-配体脱靶相互作用的多尺度计算机建模
批准号:
RGPIN-2020-04437
负责人:
Barakat, Khaled
金额:
$3.06万
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:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31

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中文摘要
翻译
为了具有生物活性,所有蛋白质和小分子必须物理地适合其靶标内的结合位点。然而,在达到目标的过程中,它们必须与各种细胞成分相互作用。所有这些事件增加了分子,特别是外源细胞来源的小分子(例如食品添加剂和污染物)与不期望的脱靶结合的可能性,导致几种生理功能的破坏。我的研究项目专注于使用计算机模拟来了解蛋白质和小分子脱靶相互作用背后的生物物理机制。我们使用心脏离子通道作为模型来研究这一过程。 心脏离子通道(例如hERG)是含有混杂结合位点的膜蛋白,据报道可与多种小分子相互作用。更重要的是,这些相互作用的数据是公开的,并且在过去的几十年中一直保持着,这使得心脏离子通道成为使用计算机模拟来理解蛋白质脱靶相互作用的优秀模型。在过去的几年里,我的研究小组和其他人为几个心脏通道开发了各种基于计算机的模型。尽管这些模型为理解离子通过其孔域的机制和脱靶相互作用提供了有用的工具,但仍有许多研究问题需要回答。例如,新出现的证据强调抑制通道运输作为小分子的替代脱靶途径,以降低心脏通道的密度,从而降低离子流量。它们主要通过阻断离子通道与其分子伴侣(例如HSP 70/90)的相互作用来实现这一点,这显著减少了膜中活性通道的数量。此外,心脏通道与某些脂质或性激素的相互作用也可以调节它们的活性。小分子利用这些脂质介导的位点/途径的脱靶机制尚未完全了解。 因此,目前的建议扩展了我们早期的工作,旨在从计算的角度了解小分子抑制心脏通道运输并与这些通道中的脂质结合位点相互作用的脱靶机制。 长期目标:了解蛋白质和小分子脱靶相互作用背后的生物物理机制。 短期目标:我们将使用多尺度模拟:1)研究小分子对抑制通道伴侣形成的影响。2)研究脂溶性分子对心肌离子通道的调节作用。 重要性:该方案的成功实施可以帮助克服目前基于计算机的脱靶预测模型的主要局限性,该模型主要集中在通道的孔阻塞上。预计这一建议还将培训大量的HQP。
英文摘要
To be biologically active, all proteins and small molecules must physically fit into the binding site(s) within their targets. However, in reaching their targets, they have to interact with a variety of cellular components. All these events increase the probability for a molecule, particularly a small molecule of exogenous cellular origin (e.g. food additives and pollutants), to bind to an undesired off-target(s), leading to the disruption of several physiological functions. My research program is focused on using computer simulations to understand the biophysical mechanisms behind off-target interactions of proteins and small molecules. We use cardiac ion channels as a model to study this process. Cardiac ion channels (e.g. hERG) are membrane proteins that contain promiscuous binding sites and have been reported to interact with diverse small molecules. More importantly, these interactions' data are publicly available and have been maintained over the last decades, making cardiac ion channels an excellent model to understand proteins' off-target interactions using computer simulations. Over the last few years my research group and others developed various computer-based models for several cardiac channels. Although, these models provided useful tools to understand the mechanisms of ions' passage and off-target interactions through their pore domains, there are still many research questions that need to be answered. For example, emerging evidences emphasize the inhibition of channel trafficking as an alternative off-target pathway for small molecules to reduce cardiac channels' density, hence, lowering ions' flow. They mainly do that by blocking the interactions of ion channels with their molecular chaperones (e.g. HSP70/90), which significantly reduces the number of active channels in the membrane. In addition, interactions of cardiac channels with certain lipids or sex hormones can also modulate their activity. The off-target mechanisms for small molecules to exploit these lipid-mediated sites/pathways are not fully understood. Thusly motivated, the current proposal expands upon our earlier work and aims to understand the off-target mechanisms by which small molecules inhibit cardiac channels' trafficking and interact with lipids' binding sites in these channels from a computational perspective. Long-term goal: To understand the biophysical mechanisms behind off-target interactions of proteins and small molecules. Short-term goals: We will use multiscale simulations to: 1) Study the effects of small molecules on inhibiting channels-chaperones formation. 2) Study the effects of lipid-soluble molecules on cardiac ion channels' modulation. Significance: The successful implementation of this proposal can help overcome a major limitation of current off-target computer-based predictive models, which mainly focused on channels' pore blockade. This proposal is also expected to train a significant number of HQPs.
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Multiscale Computer Modeling to Evaluate Protein-Ligand Off-Target Interactions
  • 批准号:
    RGPIN-2020-04437
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.06万
  • 财政年份:
    2022
  • 负责人:
    Barakat, Khaled
  • 依托单位:
Multiscale Computer Modeling to Evaluate Protein-Ligand Off-Target Interactions
  • 批准号:
    RGPIN-2020-04437
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.06万
  • 财政年份:
    2020
  • 负责人:
    Barakat, Khaled
  • 依托单位:
Atomistic Computational Models To Evaluate Protein-Ligand Off-Target Interactions
  • 批准号:
    RGPGP-2015-00055
  • 项目类别:
    Discovery Grants Program - Group
  • 资助金额:
    $2.19万
  • 财政年份:
    2019
  • 负责人:
    Barakat, Khaled
  • 依托单位:
Atomistic Computational Models To Evaluate Protein-Ligand Off-Target Interactions
  • 批准号:
    RGPGP-2015-00055
  • 项目类别:
    Discovery Grants Program - Group
  • 资助金额:
    $2.19万
  • 财政年份:
    2018
  • 负责人:
    Barakat, Khaled
  • 依托单位:
国内基金
海外基金
基于多重计算全息片(Computer-generated Hologram,CGH)的光学非球面干涉绝对检验方法研究
  • 批准号:
    62375132
  • 项目类别:
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  • 资助金额:
    54.00万元
  • 批准年份:
    2023
  • 负责人:
    马骏
  • 依托单位:
Journal of Computer Science and Technology
  • 批准号:
    61224001
  • 项目类别:
    专项基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2012
  • 负责人:
    万晓霰
  • 依托单位:
Journal of Computer Science and Technology
  • 批准号:
    61040017
  • 项目类别:
    专项基金项目
  • 资助金额:
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    2010
  • 负责人:
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