Xue Ling, Godden Jeffrey W, Stahura Florence L, Bajorath Jürgen
Department of Computer-Aided Drug Discovery, Albany Molecular Research, Inc. (AMRI), AMRI Bothell Research Center (AMRI-BRC), 18804 North Creek Parkway, Bothell, Washington 98011-8012, USA.
J Chem Inf Comput Sci. 2004 Jul-Aug;44(4):1275-81. doi: 10.1021/ci040120g.
An analysis method termed similarity search profiling has been developed to evaluate fingerprint-based virtual screening calculations. The analysis is based on systematic similarity search calculations using multiple template compounds over the entire value range of a similarity coefficient. In graphical representations, numbers of correctly identified hits and other detected database compounds are separately monitored. The resulting profiles make it possible to determine whether a virtual screening trial can in principle succeed for a given compound class, search tool, similarity metric, and selection criterion. As a test case, we have analyzed virtual screening calculations using a recently designed fingerprint on 23 different biological activity classes in a compound source database containing approximately 1.3 million molecules. Based on our predefined selection criteria, we found that virtual screening analysis was successful for 19 of 23 compound classes. Profile analysis also makes it possible to determine compound class-specific similarity threshold values for similarity searching.
一种称为相似性搜索剖析的分析方法已被开发出来，用于评估基于指纹的虚拟筛选计算。该分析基于在相似系数的整个取值范围内使用多种模板化合物进行的系统相似性搜索计算。在图形表示中，正确识别的命中数和其他检测到的数据库化合物会被分别监测。所得的剖析结果能够确定对于给定的化合物类别、搜索工具、相似性度量和选择标准，虚拟筛选试验原则上是否能够成功。作为一个测试案例，我们使用最近设计的指纹对一个包含约130万个分子的化合物源数据库中的23种不同生物活性类别进行了虚拟筛选计算分析。基于我们预先定义的选择标准，我们发现23种化合物类别中有19种的虚拟筛选分析是成功的。剖析分析还能够确定相似性搜索中特定化合物类别的相似性阈值。
Zotero 插件