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首页> 外文期刊>European Journal of Medicinal Chemistry: Chimie Therapeutique >Topological sub-structural molecular design approach: radical scavenging activity.
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Topological sub-structural molecular design approach: radical scavenging activity.

机译:拓扑亚结构分子设计方法:激进的清除活动。

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In the last decades phenolic compounds have gained enormous interest because of their beneficial health effects such as anti-inflammatory, anticancer, or antiviral activities. The pharmacological effects of phenolic compounds are mainly due to their antioxidant activity and their inhibition of certain enzymes. This antoxidant activity is related to the structure and has been extensively reported throught SAR or QSAR models. These studies confirmed that the number and position of hydroxyl groups, the related glycosylation and other substitutions in the phenolic ring largely determined radical scavenging activity. Most of these models are based on certain families of chemicals (flavonoids, cinnamic acids, etc…) and the model by itself is not useful for other substances of a different family. In this study we developed a QSAR model for a heterogeneous group of substances with TOPS-MODE descriptors for an interpretation of the antioxidant activity of these compounds in the form of bond contributions. The model developed, able to describe more than 90% of the variance in the experimental activity, also has a good predictive ability and stability. The information extracted from the QSAR model revealed that the major driving forces for radical scavenging activity are hydrogen bond donation and polarity. With this work we have managed to unify the different families of antioxidants in a single model with sufficient capacity to make predictions of radical scavenging activity for unknown substances.
机译:在过去的几十年酚类化合物已经由于其具有保健功效,如抗炎,抗癌或抗病毒活动中获得巨大的利益。酚类化合物的药理作用主要是由于它们的抗氧化活性和它们的某些酶的抑制。这antoxidant活动相关的结构和已被广泛throught SAR或QSAR模型的报道。这些研究证实,数量和羟基的位置,相关的糖基化和其它取代的酚环很大程度上取决于自由基清除活性。大多数这些模型是基于化学品的某些家庭(黄酮类化合物,肉桂酸等),并通过自身的模式并不适合不同家庭的其他物质是有用的。在这项研究中,我们开发了用于异构基团与TOPS-MODE描述符的物质的QSAR模型中的键捐款的形式,这些化合物的抗氧化活性的解释。开发,能够在实验活动来形容90%以上的方差模型,还具有良好的预测能力和稳定性。从QSAR模型中提取的信息显示,该主要驱动力自由基清除活性是氢键捐献和极性。随着这项工作,我们已成功地统一的抗氧化剂不同的家庭有足够容量的单一模式,使未知物质自由基清除活性的预测。

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