Predicting multiple binding modes using a kernel method based on a Vector Space Model Molecular Descriptor
by Forbes J. Burkowski, William W.L. Wong
International Journal of Computational Biology and Drug Design (IJCBDD), Vol. 2, No. 1, 2009

Abstract: We describe the use of our Vector Space Model Molecular Descriptor (VSMMD), based on a Vector Space Model (VSM) that is suitable for kernel studies in Quantitative Structure-Activity Relationship (QSAR) modelling. Our experiments provide convincing comparative empirical evidence that this kernel method can provide sufficient discrimination to predict various biological activities of a molecule with reasonable accuracy. Furthermore, together with a kernel feature space algorithm, experiments also provide convincing empirical evidence that our VSMMD can provide sufficient information to identify different binding modes with high accuracy.

Online publication date: Sun, 02-Aug-2009

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