Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, 20156 Milano, Italy.
KODE Srl, 56122 Pisa, Italy.
Molecules. 2022 Oct 5;27(19):6605. doi: 10.3390/molecules27196605.
Read-across applies the principle of similarity to identify the most similar substances to represent a given target substance in data-poor situations. However, differences between the target and the source substances exist. The present study aims to screen and assess the effect of the key components in a molecule which may escape the evaluation for read-across based only on the most similar substance(s) using a new open-access software: Virtual Extensive Read-Across (VERA). VERA provides a means to assess similarity between chemicals using structural alerts specific to the property, pre-defined molecular groups and structural similarity. The software finds the most similar compounds with a certain feature, e.g., structural alerts and molecular groups, and provides clusters of similar substances while comparing these similar substances within different clusters. Carcinogenicity is a complex endpoint with several mechanisms, requiring resource intensive experimental bioassays and a large number of animals; as such, the use of read-across as part of new approach methodologies would support carcinogenicity assessment. To test the VERA software, carcinogenicity was selected as the endpoint of interest for a range of botanicals. VERA correctly labelled 70% of the botanicals, indicating the most similar substances and the main features associated with carcinogenicity.
读通法（read-across）应用相似性原则，在数据匮乏的情况下，确定最相似的物质来代表给定的目标物质。然而，目标物质和源物质之间存在差异。本研究旨在使用新的开放获取软件：虚拟广泛读通法（VERA）筛选和评估分子中关键成分的影响，这些关键成分可能仅基于最相似的物质（s）而无法进行读通法评估。VERA 提供了一种使用特定于属性的结构警示、预定义的分子基团和结构相似性来评估化学品之间相似性的方法。该软件可以找到具有特定特征（例如结构警示和分子基团）的最相似化合物，并在比较不同簇中的相似物质时提供相似物质的簇。致癌性是一个具有多种机制的复杂终点，需要资源密集型的实验生物测定和大量动物；因此，将读通法作为新方法学的一部分使用将支持致癌性评估。为了测试 VERA 软件，选择致癌性作为一系列植物的感兴趣终点。VERA 正确标记了 70%的植物，指出了最相似的物质和与致癌性相关的主要特征。
