We introduce a family of positive definite kernels specifically optimized for the manipulation of 3D structures of molecules with kernel methods. The kernels are based on the comparison of the three-point pharmacophores present in the 3D structures of molecules, a set of molecular features known to be particularly relevant for virtual screening applications. We present a computationally demanding exact implementation of these kernels, as well as fast approximations related to the classical fingerprint-based approaches. Experimental results suggest that this new approach is competitive with state-of-the-art algorithms based on the 2D structure of molecules for the detection of inhibitors of several drug targets.

译文

我们介绍了一系列正定核,这些核专门针对使用核方法操纵分子的3D结构进行了优化。内核基于分子3D结构中存在的三点药效团的比较,这是一组已知与虚拟筛选应用特别相关的分子特征。我们提出了对这些内核的计算要求很高的精确实现,以及与经典的基于指纹的方法相关的快速逼近。实验结果表明,这种新方法与基于分子2D结构的最新算法具有竞争力,可用于检测几种药物靶标的抑制剂。

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