Wolber Gerhard, Langer Thierry
Inte:Ligand GmbH, Mariahilferstrasse 74B/11, A-1070 Vienna, Austria.
J Chem Inf Model. 2005 Jan-Feb;45(1):160-9. doi: 10.1021/ci049885e.
From the historically grown archive of protein-ligand complexes in the Protein Data Bank small organic ligands are extracted and interpreted in terms of their chemical characteristics and features. Subsequently, pharmacophores representing ligand-receptor interaction are derived from each of these small molecules and its surrounding amino acids. Based on a defined set of only six types of chemical features and volume constraints, three-dimensional pharmacophore models are constructed, which are sufficiently selective to identify the described binding mode and are thus a useful tool for in-silico screening of large compound databases. The algorithms for ligand extraction and interpretation as well as the pharmacophore creation technique from the automatically interpreted data are presented and applied to a rhinovirus capsid complex as application example.
从蛋白质数据库中历史积累的蛋白质-配体复合物档案中提取小分子有机配体,并根据其化学特性和特征进行解读。随后,从这些小分子及其周围的氨基酸中衍生出代表配体-受体相互作用的药效团。基于仅六种化学特征和体积限制的定义集,构建三维药效团模型,该模型具有足够的选择性以识别所描述的结合模式,因此是用于虚拟筛选大型化合物数据库的有用工具。介绍了配体提取和解读算法以及从自动解读数据中创建药效团的技术,并将其应用于鼻病毒衣壳复合物作为应用实例。