Shape signatures: new descriptors for predicting cardiotoxicity in silico.

ABSTRACT: Shape Signatures is a new computational tool that is being evaluated for applications in computational toxicology and drug discovery. The method employs a customized ray-tracing algorithm to explore the volume enclosed by the surface of a molecule and then uses the output to construct compact histograms (i.e., signatures) that encode for molecular shape and polarity. In the present study, we extend the application of the Shape Signatures methodology to the domain of computational models for cardiotoxicity. The Shape Signatures method is used to generate molecular descriptors that are then utilized with widely used classification techniques such as k nearest neighbors ( k-NN), support vector machines (SVM), and Kohonen self-organizing maps (SOM). The performances of these approaches were as

SUBMITTER: Chekmarev DS 

PROVIDER: S-EPMC2758060 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature