Maxence Lalis, Matej Hladiš, Samar Abi Khalil, Christophe Deroo, Christophe Marin, Moustafa Bensafi, Nicolas Baldovini, Loïc Briand, Sébastien Fiorucci, Jérémie Topin
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引用次数: 0
摘要
嗅觉感知始于气味物质与位于专用感觉神经元表面的特化受体相互作用。对气味的识别取决于一种复杂的机制,其中涉及气味物质与一组气味受体(ORs)之间相互作用的组合。尽管这些相互作用已经被研究了几十年,但人们对配体识别的规则仍然知之甚少,而且只知道少数几种气味物质的完整组合代码。我们仔细分析了有关 OR 与分子间相互作用的实验结果,提供了一份有关 OR 非形态化(即识别出特定序列的第一个激动剂)的现状报告。这一细致的分析凸显了实验方法(细胞系或读数)对分子-受体关联结果的影响,并表明无论实验条件如何,83%的结果是一致的。另一个关键参数 EC50 的分布表明,大多数 OR 配体的活性在微摩尔范围内,杂质可能导致错误结论。以人类 OR 为重点,我们的研究表明,88% 的记录序列仍需进行非形态化处理。最后,我们还估算了ORs识别范围的大小或广度,即激活特定ORs的气味物质的数量。通过类比估算分子广度并将两种估算结果结合起来,我们提出了一个基本框架,可作为未来预测 OR 分子活性的机器学习算法的比较点。
A status report on human odorant receptors and their allocated agonists.
Olfactory perception begins when odorous substances interact with specialized receptors located on the surface of dedicated sensory neurons. The recognition of smells depends on a complex mechanism involving a combination of interactions between an odorant and a set of odorant receptors (ORs), where molecules are recognized according to a combinatorial activation code of ORs. Although these interactions have been studied for decades, the rules governing this ligand recognition remain poorly understood, and the complete combinatorial code is only known for a handful of odorants. We have carefully analyzed experimental results regarding the interactions between ORs and molecules to provide a status report on the deorphanization of ORs, i.e. the identification of the first agonist for a given sequence. This meticulous analysis highlights the influence of experimental methodology (cell line or readout) on molecule-receptor association results and shows that 83% of the results are conserved regardless of experimental conditions. The distribution of another key parameter, EC50, indicates that most OR ligand activities are in the micromolar range and that impurities could lead to erroneous conclusions. Focusing on the human ORs, our study shows that 88% of the documented sequences still need to be deorphanized. Finally, we also estimate the size of the ORs' recognition range, or broadness, as the number of odorants activating a given OR. By analogously estimating molecular broadness and combining the two estimates we propose a basic framework that can serve as a comparison point for future machine learning algorithms predicting OR-molecule activity.
期刊介绍:
Chemical Senses publishes original research and review papers on all aspects of chemoreception in both humans and animals. An important part of the journal''s coverage is devoted to techniques and the development and application of new methods for investigating chemoreception and chemosensory structures.