PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The pharmacophore kernel for virtual screening with support vector machines
Pierre Mahé, Liva Ralaivola, Véronique Stoven and Jean-Philippe Vert
Journal of Chemical Information and Modeling Volume 46, Number 5, pp. 2003-2014, 2006.

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.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:2502
Deposited By:Jean-Philippe Vert
Deposited On:22 November 2006