Gregori-Puigjané Elisabet, Mestres Jordi
Chemogenomics Laboratory, Research Unit on Biomedical Informatics, Institut Municipal d'Investigació Mèdica and Universitat Pompeu Fabra, Passeig Marítim de la Barceloneta 37-49, 08003 Barcelona, Catalonia, Spain.
J Chem Inf Model. 2006 Jul-Aug;46(4):1615-22. doi: 10.1021/ci0600509.
A novel set of molecular descriptors called SHED (SHannon Entropy Descriptors) is presented. They are derived from distributions of atom-centered feature pairs extracted directly from the topology of molecules. The value of a SHED is then obtained by applying the information-theoretical concept of Shannon entropy to quantify the variability in a feature-pair distribution. The collection of SHED values reflecting the overall distribution of pharmacophoric features in a molecule constitutes its SHED profile. Similarity between pairs of molecules is then assessed by calculating the Euclidean distance of their SHED profiles. Under the assumption that molecules having similar pharmacological profiles should contain similar features distributed in a similar manner, examples are given to show the ability of SHED for scaffold hopping in virtual chemical screening and pharmacological profiling compared to that of substructural BCI fingerprints and three-dimensional GRIND descriptors.
提出了一组名为SHED（香农熵描述符）的新型分子描述符。它们源自直接从分子拓扑结构中提取的以原子为中心的特征对的分布。然后，通过应用香农熵的信息论概念来量化特征对分布中的变异性，从而获得SHED的值。反映分子中药效基团特征总体分布的SHED值集合构成了其SHED图谱。然后，通过计算它们的SHED图谱的欧几里得距离来评估分子对之间的相似性。在具有相似药理图谱的分子应包含以相似方式分布的相似特征这一假设下，给出了示例，以展示与亚结构BCI指纹和三维GRIND描述符相比，SHED在虚拟化学筛选和药理图谱分析中进行骨架跃迁的能力。
