Theoretical studies of ligand-receptor interactions in ion channels

人类基因组编码了400多种形成离子通道的蛋白质。电压门控K+、Na+和Ca2+通道是控制疼痛和治疗心血管、神经、自身免疫和其他疾病的药物靶点。这些通道在结构上处于不同的关闭、打开和失活状态。药物通常优先与某些州绑定。这种状态依赖的作用很难通过高通量配基筛选来研究，高通量配基筛选是药物发现的主要实验方法。分子模拟有助于理解状态依赖的药物作用的原子机制。在2009-2013年间，我们在PNAS USA、Chem Review、Trends Pharmacol Sci、J Biol Chem和其他期刊上发表了13篇由NSERC资助的论文。我们将继续药物和毒素离子通道的理论研究。我们的方法包括5个阶段。1)以K+和Na+通道在开放、关闭和失活状态下的X射线结构为模板，建立医学上重要离子通道的同源模型。2)分析已发表的有关配体构效关系的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，并关注缺乏结构性解释或提出有问题的数据。4)将代表性配体与同源模型中的代表性配体对接，并考虑到配体可能直接与意向阳离子相互作用的可能性(Zhorov&Tikhonov，2013，Trends Pharmacol Sci)。5)对接实验通常预测出一系列能量合理的配体结合模式。我们选择那些与实验数据最一致的。我们将使用在ZMM程序中实现的蒙特卡罗最小化方法作为主要的计算工具，我多年来一直在详细阐述该方法。ZMM已经得到了验证，例如在(Garden&Zhorov，2010)中。国产软件的一个优点是，它可以适应新的问题。并不缺乏需要结构性解释的已发表的实验数据。细菌Na+通道的最新X射线结构为用毒素和医学上重要的药物模拟Na+和Ca+通道提供了可靠的模板。我还为我的研究计划提出了一个新的方向。突变分析被用来确定配体结合位点，但结果的结构解释是困难的。事实上，配体的作用可能会由于配体结合部位残基的突变而改变(直接影响)，或者远远超出这个位置(变构效应)。我们将详细阐述一种区分直接和变构效应的方法。驱动假说是，改变离子通道片段之间依赖于状态的接触的突变，改变了打开/关闭/失活状态的群体，从而可能变构地影响药物的作用。为了区分这些影响，我们将划分通道能量，选择参与强片段间收缩的残基，探索这些接触在不同通道状态下是如何变化的，并根据这些结果分析突变数据。这种方法将有助于解释为什么钠离子和钙离子通道中保守的天冬酰胺突变会影响许多孔靶向配体的作用。KV1通道被结构相似的配体PAP-1和Psora-4阻断的突变分析导致了相互冲突的配体结合模型(Zimin等人。2010年；Marzian等人。2013)。我们将分析潜在的突变，并重新讨论这些高效配体阻断KV1通道的机制。区分突变的直接效应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，这将有助于维持和改善加拿大人的健康。

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.