Cátedra de Ingeniería y Toxicología Ambiental, Universidad Católica San Antonio, Guadalupe, Murcia, Spain.
Eur J Med Chem. 2012 Mar;49:86-94. doi: 10.1016/j.ejmech.2011.12.030. Epub 2012 Jan 4.
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.
在过去的几十年中,由于酚类化合物具有抗炎、抗癌或抗病毒等有益的健康作用,因此引起了极大的关注。酚类化合物的药理作用主要归因于其抗氧化活性和对某些酶的抑制作用。这种抗氧化活性与结构有关,并通过 SAR 或 QSAR 模型得到了广泛的报道。这些研究证实,酚环中羟基的数量和位置、相关的糖基化和其他取代基在很大程度上决定了清除自由基的活性。这些模型大多基于某些化学物质家族(黄酮类化合物、肉桂酸等),并且该模型本身对于不同家族的其他物质没有用处。在这项研究中,我们使用拓扑描述符(TOPS-MODE)开发了一个用于异构物质组的 QSAR 模型,以解释这些化合物在形成键贡献时的抗氧化活性。所开发的模型能够描述实验活性中超过 90%的变化,并且还具有良好的预测能力和稳定性。从 QSAR 模型中提取的信息表明,清除自由基活性的主要驱动力是氢键供体和极性。通过这项工作,我们成功地将不同的抗氧化剂家族统一在一个具有足够能力的单一模型中,以对未知物质的清除自由基活性进行预测。