Nicotinic Ligand Development to Target Smoking Cessation and Gain a Molecular Level Understanding of Partial Agonism
Nicotinic Ligand Development to Target Smoking Cessation and Gain a Molecular Level Understanding of Partial Agonism
批准号:
EP/N024117/1
负责人:
Timothy Gallagher
金额:
$92.32万
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 --
中文摘要
这项建议涉及一类新的戒烟“药物”的作用机制,这种药物的成分能结合并部分激活大脑中的高亲和力尼古丁受体。(伐伦克林)是一种尼古丁部分激动剂,但受到FDA的限制,反映了受体亚型选择性水平不足;伐尼克兰靶向高亲和力烟碱结合位点(α 4 β 2),但也是α 7受体的完全激动剂。如果较差的亚型选择性是伐尼克兰副作用的原因,那么更好地了解配体结构如何与受体(和亚型)功能联系是关键,但要做到这一点,我们需要扩大我们对配体结合模式的认识。金雀花碱,这是我们的重点,是一种天然存在的部分烟碱激动剂,已用于戒烟,因此本身也具有商业潜力。我们最近开发了强大而有效的化学方法,使我们能够直接,特异性地修饰金雀花碱,并且在分子上几乎未被探索的位点。这种化学方法使用金雀花碱作为一个非常容易的起点来探索一系列新的结构变体,以探测新的结合模式,从而潜在地找到实现烟碱亚型特异性的新方法。最近推测金雀花碱(和伐尼克兰)介导配体与烟碱受体结合的那些分子特征将通过(i)制备其结构特征将减弱配体结合的特定分子和(ii)以非常直接的方式扩大配体-蛋白质接触的范围来研究。我们将建立在初步的结构和计算研究,并创建新的配体与C3和C4位置的金雀花碱。这两种类型,但特别是C4变体,提供了一个机会,使现有的(但目前“旁观者”)蛋白残基参与配体结合,这些蛋白残基位于与关键受体亚型之间的分化直接相关的结合位点区域内。通过访问这些额外的模式来修改现有的绑定将允许我们合理地“调整”子类型选择性。成功将极大地提高我们的烟碱配体内的结构关系的看法,并提供见解的范围和空间分布的增强的“活性位点”template.We的药物化学家将研究这些新的相互作用的具体细节,使用晶体学精确定位模型蛋白质内的配体,从而确定新的“从事”残基。然后,我们将把它与仍然不能结晶的完整的人类受体蛋白联系起来,以了解配体结合以及任何新的结合模式如何转化为完整的蛋白质受体功能。我们将使用新的和强大的计算方法来研究配体结合的结果的细节,以便将配体结构与整个受体功能相关联。我们已经有一系列的合作者在一个多学科的计划中,使我们能够探索这些新配体的生物学,结构特性和商业潜力,并将其与我们的预测和分析计算方法相关联。这个项目的成功将主要取决于我们新的计算技术和合成化学之间的密切相互作用。我们将阐明决定亚型选择性的配体结构的分子水平特征,这将对戒烟药物的安全性/用户可接受性产生长期影响。通过了解配体结构如何与整体受体功能联系的细节,这是一项特别具有挑战性的计算任务,我们希望将亚型选择性问题与更通用的“下游”效应(与烟碱活化相关)分开,这有可能指导基于烟碱的治疗剂的进一步开发。
英文摘要
This proposal addresses the mechanism of action of a new class of "drug" used for smoking cessation based on agents which bind to and partially activate the high affinity nicotine receptors in the brain.The "first to market" drug (varenicline) is a nicotinic partial agonist but is subject to FDA restrictions that reflect an inadequate level of receptor subtypes selectivity; varenicline targets the high affinity nicotinic binding site (alpha4beta2) but is also a full agonist at the alpha7 receptor. If poor subtype selectivity is responsible for varenicline's side effects, a better insight into how ligand structure links to the receptor (and subtype) function is key, but to do this we will need to broaden our appreciation the modes of ligand binding. Cytisine, which is our focus, is a naturally-occurring partial nicotinic agonist that has been used for smoking cessation, and so itself is also of commercial potential. We have recently developed robust and efficient chemistry that allows us to modify cytisine directly, specifically, and at an otherwise almost unexplored site on the molecule. This chemistry uses cytisine as a very accessible starting point to explore a range of new structural variants to probe novel binding modes and so potentially new ways to achieve nicotinic subtype specificity. Recent speculation as to those molecular features of cytisine (and varenicline) that mediate ligand binding to nicotinic receptors will be investigated by (i) making specific molecules whose structural features will attenuate ligand binding and by (ii) expanding the range of ligand-protein contacts made in a very directed manner. We will build on preliminary structural and computational studies and create new ligands associated with C3 and C4 positions of cytisine. Both classes, but especially C4 variants, offer an opportunity to engage existing (but currently "spectator") protein residues in ligand binding that are within that region of the binding site directly associated with differentiation between the key receptor subtypes. Modifying existing binding by accessing these additional modes will allow us to rationally "tune" subtype selectivity. Success will dramatically improve our view of structure-relationships within nicotinic ligands and offer insights to medicinal chemists as to the range and spatial distribution of an enhanced "active site" template.We will study the specific detail of these new interactions using crystallography to pinpoint the ligand within a model protein and so identify newly "engaged" residues. We will then link this to the full human receptor protein, which still cannot be crystallised, in order to understand how ligand binding, as well as any new modes of binding, translates into how the full protein receptor functions. We will do this with new and powerful computational methods to look at the detail of the consequences of ligand binding in order to correlate ligand structure to whole receptor function.We have a series of collaborators in place in what is already a multidisciplinary programme to enable us to explore the biological, structural properties and commercial potential of these new ligands, and to correlate that to our predictive and analytical computational methods. Success in this project will critically depend on a close interplay between our new computational techniques and the synthetic chemistry. We will shed light on molecular level features of ligand structure which determine subtype selectivity and this will have longer term implications for safety/user acceptability within smoking cessation agents. By understanding the detail of how ligand structure links to overall receptor function, and this is an especially challenging computational task, we hope to separate subtype selectivity issues from more generic "downstream" effects (associated with nicotinic activation) which has the potential to guide further development of nicotinic-based therapeutic agents.
期刊论文(10)
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DOI:
10.3390/e21080750
发表时间:
2019-07-31
期刊:
Entropy (Basel, Switzerland)
影响因子:
--
作者:
[Ali HS, Higham J, Henchman RH]
通讯作者:
Henchman RH
DOI:
10.1021/acs.jctc.1c00547
发表时间:
2021-10-12
期刊:
Journal of chemical theory and computation
影响因子:
5.5
作者:
[Ansell TB, Curran L, Horrell MR, Pipatpolkai T, Letham SC, Song W, Siebold C, Stansfeld PJ, Sansom MSP, Corey RA]
通讯作者:
Corey RA
New methods: general discussion.
新方法:一般性讨论。
DOI:
10.1039/c6fd90075e
发表时间:
2016
期刊:
Faraday discussions
影响因子:
3.4
作者:
[Angulo G]
通讯作者:
Angulo G
DOI:
10.1109/mcse.2020.3024155
发表时间:
2020-11
期刊:
Computing in science & engineering
影响因子:
2.1
作者:
[Amaro RE, Mulholland AJ]
通讯作者:
Mulholland AJ
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负责人:Timothy Gallagher
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依托单位:
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