Putta Santosh, Landrum Gregory A, Penzotti Julie E
Rational Discovery LLC, 555 Bryant Street #467, Palo Alto, California 94301, USA.
J Med Chem. 2005 May 5;48(9):3313-8. doi: 10.1021/jm049066l.
Discovering essential features shared by active compounds, an important step in drug-design, is complicated by conformational flexibility. We present a new algorithm to efficiently mine the conformational space of multiple actives and find small subsets of conformations likely to be biologically relevant. The approach identifies chemical and steric similarities between actives, providing insight into features important for binding when structural data are absent. Validation studies (thrombin and CDK2 data) produce alignments similar to protein-based alignments.
发现活性化合物共有的基本特征是药物设计中的重要一步，但由于构象灵活性而变得复杂。我们提出了一种新算法，以有效地挖掘多种活性物质的构象空间，并找到可能与生物学相关的小构象子集。该方法识别活性物质之间的化学和空间相似性，在缺乏结构数据时，为理解结合的重要特征提供了思路。验证研究（凝血酶和细胞周期蛋白依赖性激酶2的数据）产生的比对结果与基于蛋白质的比对结果相似。
