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The pharmacophore kernel for virtual screening with support vector machines

Pierre Mahé·Liva Ralaivola·Véronique Stoven·Jean-Philippe Vert
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Abstract

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-points pharmacophores present in the 3D structures of molecul es, 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 approa ches. Experimental results suggest that this new approach outperforms state-of-the-art algorithms based on the 2D structure of mol ecules for the detection of inhibitors of several drug targets.

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Pierre Mahé, Liva Ralaivola, Véronique Stoven, Jean-Philippe Vert. 2006-03-03. The pharmacophore kernel for virtual screening with support vector machines. https://arxiv.org/abs/q-bio/0603006

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