Theoretical studies of ligand-receptor interactions in ion channels

离子通道中配体-受体相互作用的理论研究

• 批准号: RGPIN-2014-04894
• 负责人: Zhorov, Boris
• 金额: $ 3.42万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=588086
• 关键词: Theoretical; studies; ligand; receptor; interactions

The human genome encodes over 400 proteins that form ion channels. Voltage-gated K+, Na+, and Ca2+ channels are drug targets for pain control and treatment of cardiovascular, neurological, autoimmune and other disorders. The channels exist in structurally different closed, open and inactivated states. Drugs often bind preferentially to certain states. Such state-dependent action is difficult to study by high-throughput ligand screening, the major experimental approach in drug discovery. Molecular modeling helps understand atomistic mechanisms of state-dependent drug action. In 2009-2013 we have published 13 NSERC-funded papers in PNAS USA, Chem Reviews, Trends Pharmacol Sci, J Biol Chem and other journals. We will continue theoretical studies of ion channels with drugs and toxins. Our approach includes 5 stages. 1) Building homology models of medicinally important ion channels using as templates available X-ray structures of K+ and Na+ channels in the open, closed, and inactivated states. 2) Analyzing published data on structure-activity relations of ligands and mutational analysis of ligand-binding sites. 3) Revealing paradoxes in the experimental data and focusing on data that lack structural interpretations or suggest questionable ones. 4) Docking representative ligands in the homology models with considering a possibility that ligands may directly interact with permeant cations (Zhorov & Tikhonov, 2013, Trends Pharmacol Sci). 5) Docking experiments usually predict an ensemble of energetically reasonable ligand-binding modes. We select those that are best consistent with experimental data. We will use the Monte Carlo-minimization method realized in the ZMM program, which I am elaborating over many years, as a major computational tool. ZMM has been validated, e.g., in (Garden & Zhorov, 2010). An advantage of the home-made software is that it can be adapted to address new problems. There is no shortage of published experimental data that need structural interpretations. Recent x-ray structures of bacterial Na+ channels provide reliable templates to model Na+ and Ca2+ channels with toxins and medically important drugs. I also propose a new direction for my research program. Mutational analysis is used to determine ligand-binding sites, but structural interpretation of results is difficult. Indeed, a ligand action may change due to mutation of a residue in the ligand-binding site (a direct effect) or far beyond this site (an allosteric effect). We will elaborate an approach to discriminate the direct and allosteric effects. The driving hypothesis is that mutations, which change state-depended contacts between ion channel segments, change populations of the open/closed/inactivated states and thus may allosterically affect drug action. To discriminating these effects we will partition the channel energy, select residues involved in strong intersegment contracts, explore how such contacts change in different channel states, and analyze mutational data in view of these results. This approach will help explain why mutations of conserved asparagines in Na+ and Ca2+ channels, which do not face the pore, affect action of many pore-targeting ligands. Mutational analyses of Kv1 channels block by structurally similar ligands PAP-1 and Psora-4 resulted in conflicting ligand-binding models (Zimin et al. 2010; Marzian et al. 2013). We will analyze underlying mutations and readdress the mechanism of Kv1 channel block by these highly potent ligands. Discriminating direct and allosteric effects of mutations will be important for building other ligand-channel models. Our studies will contribute to basic knowledge and development of new drugs that will help maintain and improve health of Canadians.

人类基因组编码超过400种形成离子通道的蛋白质。电压门控的K+、Na+和Ca 2+通道是用于疼痛控制和治疗心血管、神经、自身免疫和其它病症的药物靶标。通道以结构上不同的闭合、开放和失活状态存在。药物往往优先与某些状态结合。这种状态依赖的作用很难通过高通量配体筛选来研究，高通量配体筛选是药物发现的主要实验方法。分子建模有助于理解状态依赖性药物作用的原子机制。2009-2013年，我们在PNAS USA，Chem Reviews，Trends Pharmacol Sci，J Biol Chem和其他期刊上发表了13篇NSERC资助的论文。我们将继续离子通道与药物和毒素的理论研究。我们的方法包括五个阶段。1)建立同源性模型的医学重要的离子通道作为模板可用的X射线结构的K+和Na+通道的开放，关闭，和失活状态。2)分析已发表的配体构效关系数据和配体结合位点的突变分析。3)揭示实验数据中的悖论，并关注缺乏结构解释或提出可疑解释的数据。4)考虑配体可以直接与渗透阳离子相互作用的可能性，在同源模型中对接代表性配体（Zhorov & Tikhonov，2013，Trends Pharmacol Sci）。5)对接实验通常预测能量合理的配体结合模式的集合。我们选择那些最符合实验数据。我们将使用ZMM程序中实现的蒙特卡洛最小化方法，我多年来一直在详细阐述该方法，作为主要的计算工具。ZMM已得到验证，例如，in（Garden & Zhorov，2010）. 自制软件的一个优点是它可以适应新的问题。已经发表的实验数据并不缺乏结构解释。最近的细菌Na+通道的X射线结构提供了可靠的模板来模拟具有毒素和医学重要药物的Na+和Ca 2+通道。我还为我的研究计划提出了一个新的方向。 突变分析用于确定配体结合位点，但结果的结构解释是困难的。事实上，配体作用可能由于配体结合位点中残基的突变（直接效应）或远远超出该位点（变构效应）而改变。我们将阐述一种方法来区分直接和变构效应。驱动假说是突变改变离子通道区段之间的状态依赖性接触，改变开放/闭合/失活状态的群体，从而可能变构影响药物作用。为了区分这些影响，我们将划分通道能量，选择参与强片段间合同的残基，探索这种接触如何在不同的通道状态下变化，并分析突变数据，鉴于这些结果。这种方法将有助于解释为什么保守的天冬酰胺在Na+和Ca 2+通道，不面对孔的突变，影响许多孔靶向配体的行动。通过结构相似的配体PAP-1和Psora-4阻断Kv 1通道的突变分析产生了相互矛盾的配体结合模型（Zimin et al. 2010; Marzian et al. 2013）。我们将分析潜在的突变，并重新探讨这些高效配体阻断Kv 1通道的机制。区分突变的直接和变构效应对于建立其他配体通道模型将是重要的。我们的研究将有助于基本知识和新药的开发，这将有助于保持和改善加拿大人的健康。