Lill Markus A, Vedani Angelo
Biographics Laboratory 3R, Friedensgasse 35, 4056 Basel, Switzerland.
J Chem Inf Model. 2006 Sep-Oct;46(5):2135-45. doi: 10.1021/ci6001944.
We recently reported the development of two receptor-modeling concepts (software Quasar and Raptor) based on multidimensional quantitative structure-activity relationships (QSAR) and allowing for the explicit simulation of induced fit. As the identification of the bioactive configuration of ligand molecules in such studies is all but unambiguous, each compound may be represented by an ensemble of different conformations, orientations, stereoisomers, and protonation states, leading to a 4D data set. In this account, we present a novel technology (software Symposar) allowed to automatically generate a 4D pharmacophore as input for multidimensional QSAR. Symposar aligns ligands utilizing fuzzylike 2D-subfeature mapping and, subsequently, a Monte Carlo search on a 3D similarity grid. The two-step concept (4D pharmacophore generation and quantification of ligand binding by multidimensional QSAR) was applied to 186 compounds binding to the bradykinin B2 receptor. The prediction of their binding affinity by means of the Quasar and Raptor technologies allowed for consensus scoring and generated topologically and quantitatively consistent receptor models. These converged at a cross-validated r2 of 0.752 and 0.815 and yielded a predictive r2 of 0.784 and 0.853 for a test set (for Quasar and Raptor, respectively).
我们最近报道了基于多维定量构效关系（QSAR）并允许明确模拟诱导契合的两种受体建模概念（软件Quasar和Raptor）的开发。由于在此类研究中配体分子生物活性构型的识别几乎不明确，每种化合物可能由不同构象、取向、立体异构体和质子化状态的集合表示，从而产生一个四维数据集。在本报告中，我们提出了一种新技术（软件Symposar），它能够自动生成一个四维药效团作为多维QSAR的输入。Symposar利用类似模糊的二维子特征映射对齐配体，随后在三维相似性网格上进行蒙特卡罗搜索。两步概念（四维药效团生成和通过多维QSAR对配体结合进行定量）应用于与缓激肽B2受体结合的186种化合物。通过Quasar和Raptor技术预测它们的结合亲和力可进行一致性评分，并生成拓扑和定量一致的受体模型。这些模型在交叉验证的r2分别为0.752和0.815时收敛，对于测试集（分别针对Quasar和Raptor）产生的预测r2为0.784和0.853。
