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Volume 4 Toxicology: Open Access
ISSN: 2476-2067 Toxicology Congress 2018
March 12-14, 2018
March 12-14, 2018 Singapore
14th World Congress on
Toxicology and Pharmacology
Active QSAR modeling for environmental toxicity prediction by partial least squares
Yoshimasa Takahashi, Ryota Kikuchi and Tetsuo Katsuragi
Toyohashi University of Technology, Japan
QSAR models obtained from a data set that consists of structurally diverse compounds
often give us poor results for the prediction. In the previous work, we proposed
a technique of active QSAR modeling that is based on active sampling of a temporary
training set. In the method, structurally similar compounds are explored and collected
as a training set to make a local model around the query. The result suggested that the
approach would often give us better prediction performance than that obtained by the
ordinal QSAR modeling. In this paper, we applied the PLS method to QSAR modeling for
fish toxicity prediction. We used topological fragment spectra (TFS) to describe structural
features of individual compounds. TFS is a digitization of the chemical structure information described in a multidimensional
numerical vector. We used a dataset of fish 96h-LC50 for 330 chemicals. The toxicity data were taken from the results of eco-
toxicity tests by Ministry of the Environment, Japan. Those toxicity were converted from units of milligrams per litre to moles
per litre (mol/L) and then to the corresponding logarithmic values. The TFS-based PLS model obtained with a single latent
variable gave us an approximation of R=0.931, R2=0.866, RMSE=0.341 to the experimental values. But, leave-one-out testing
for the data set resulted with the RMSE=0.886, unfortunately.
Recent Publications
1. Kentaro Kawai, Yoshimasa Takahashi (2014) De Novo Design of Drug-Like Molecules by a Fragment-Based Molecular
Evolutionary Approach. J. Chem. Inf. Model; 54(1): 49-56.
2. Kentaro Kawai, Kazutaka Yoshimaru, Yoshimasa Takahashi (2011) Generation of Target Selective Drug Candidate
Structures using Molecular Evolutionary Algorithm with SVM Classifiers. J. Comput. Chem. Jpn.; 10(3): 79-87.
Biography
Yoshimasa Takahashi has received his PhD in chemometrics at Kyoto University in 1984. He was awarded the Niwa Memorial Award for studies on information
management and computer-aided design system for chemical research in 1988, presented by Japan Information Center of Science and Technology (JICST). He
was also a past chair of Division of Structure-Activity Studies, Pharmaceutical Society of Japan. His current research interest center on intelligent information
processing based on structural similarity.
Yoshimasa Takahashi et al., Toxicol Open Access 2018, Volume 4
DOI: 10.4172/2476-2067-C1-006