QSAR models building software

The present paper is organized as follows. First, a brief introduction is given for each ADME-Tox property, especially how it is related to ADME-Tox, and then the latest in silico models for that property are discussed. Further, some experts opinion is presented on how to model that property more accurately and reliably. This is followed by a discussion on how to build up predictable QSAR models with all kinds of statistical tools. Finally, the ADME-Tox resources, including both databases and software packages are summarized. 

In order to assess the potential toxicological effects of onchidal from a predictive standpoint, the author subjected the two-dimensional molecular structure of onchidal (1) to an in silica QSAR computational analysis. Details regarding the approach of the software, including procedures and model building methods, have been described in recent publications (e.g., Choi et al., 2013 Valencia et al., 2013). The in silica analysis of the molecular structure of onchidal produced predictive information on nonclinical toxicities. The computational QSAR models included bacterial mutagenicity (Salmanella h/pln/murium mutagenicity (Ames) assay), and phospholipidosis (Table 30.3). 

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