title: The pharmacophore kernel for virtual screening with support vector machines.
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-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.
authors.affiliation: Center for Computational Biology, Ecole des Mines de Paris, 35 rue Saint Honoré, 77305 Fontainebleau, France. pierre.mahe@ensmp.fr
authors.forename: Pierre
authors.initials: P
authors.lastname: Mahé
authors.forename: Liva
authors.initials: L
authors.lastname: Ralaivola
authors.forename: Véronique
authors.initials: V
authors.lastname: Stoven
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Vert
mesh_terms: D000465:Algorithms; D004364:Pharmaceutical Preparations
chemical_list: D004364:Pharmaceutical Preparations