Ertl Peter, Jelfs Stephen, Mühlbacher Jörg, Schuffenhauer Ansgar, Selzer Paul
Novartis Institutes for BioMedical Research, CH-4002 Basel, Switzerland.
J Med Chem. 2006 Jul 27;49(15):4568-73. doi: 10.1021/jm060217p.
Bioactive molecules only contain a relatively limited number of unique ring types. To identify those ring properties and structural characteristics that are necessary for biological activity, a large virtual library of nearly 600 000 heteroaromatic scaffolds was created and characterized by calculated properties, including structural features, bioavailability descriptors, and quantum chemical parameters. A self-organizing neural network was used to cluster these scaffolds and to identify properties that best characterize bioactive ring systems. The analysis shows that bioactivity is very sparsely distributed within the scaffold property and structural space, forming only several relatively small, well-defined "bioactivity islands". Various possible applications of a large database of rings with calculated properties and bioactivity scores in the drug design and discovery process are discussed, including virtual screening, support for the design of combinatorial libraries, bioisosteric design, and scaffold hopping.
生物活性分子仅包含相对有限数量的独特环类型。为了确定那些对于生物活性必不可少的环性质和结构特征，创建了一个包含近60万个杂芳基支架的大型虚拟库，并通过计算性质进行表征，这些性质包括结构特征、生物利用度描述符和量子化学参数。使用自组织神经网络对这些支架进行聚类，并识别最能表征生物活性环系统的性质。分析表明，生物活性在支架性质和结构空间中分布非常稀疏，仅形成了几个相对较小的、定义明确的“生物活性岛”。讨论了具有计算性质和生物活性分数的大环数据库在药物设计和发现过程中的各种可能应用，包括虚拟筛选、支持组合库设计、生物电子等排体设计和骨架跃迁。
