Literature DB >> 20054986

Predicting multiple binding modes using a kernel method based on a vector space model molecular descriptor.

Forbes J Burkowski1, William W L Wong.   

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.

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Year:  2009        PMID: 20054986     DOI: 10.1504/ijcbdd.2009.027584

Source DB:  PubMed          Journal:  Int J Comput Biol Drug Des        ISSN: 1756-0756


  1 in total

1.  A constructive approach for discovering new drug leads: Using a kernel methodology for the inverse-QSAR problem.

Authors:  William Wl Wong; Forbes J Burkowski
Journal:  J Cheminform       Date:  2009-04-28       Impact factor: 5.514

  1 in total

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