Steindl Theodora M, Schuster Daniela, Laggner Christian, Chuang Karen, Hoffmann Rémy D, Langer Thierry
Institute of Pharmacy, Computer Aided Molecular Design Group, University of Innsbruck, Innrain 52c and Center for Molecular Biosciences Innsbruck (CMBI), Peter-Mair-Strasse 1, A-6020 Innsbruck, Austria.
J Chem Inf Model. 2007 Mar-Apr;47(2):563-71. doi: 10.1021/ci600321m.
Parallel Screening has been introduced as an in silico method to predict the potential biological activities of compounds by screening them with a multitude of pharmacophore models. This study presents an early application example employing a Pipeline Pilot-based screening platform for automatic large-scale virtual activity profiling. An extensive set of HIV protease inhibitor pharmacophore models was used to screen a selection of active and inactive compounds. Furthermore, we aimed to address the usually critically eyed point, whether it is possible in a parallel screening system to differentiate between similar molecules/molecules acting on closely related proteins, and therefore we incorporated a collection of other protease inhibitors including aspartic protease inhibitors. The results of the screening experiments show a clear trend toward most extensive retrieval of known active ligands, followed by the general protease inhibitors and lowest recovery of inactive compounds.
平行筛选作为一种计算机辅助方法被引入,通过使用多种药效团模型对化合物进行筛选来预测其潜在的生物活性。本研究展示了一个早期应用实例,该实例采用了基于管道先导的筛选平台进行自动大规模虚拟活性分析。使用了大量的HIV蛋白酶抑制剂药效团模型来筛选一系列活性和非活性化合物。此外,我们旨在解决通常备受关注的问题,即在平行筛选系统中是否能够区分相似分子/作用于密切相关蛋白质的分子,因此我们纳入了包括天冬氨酸蛋白酶抑制剂在内的其他蛋白酶抑制剂集合。筛选实验结果显示出明显的趋势,即已知活性配体的检索最为广泛,其次是一般蛋白酶抑制剂,非活性化合物的回收率最低。