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Estimation of physicochemical properties using WebTEST 2.0, a database centered modeling platform for building and deploying QSAR models
Citation:
Martin, T., C. Ramsland, N. Charest, C. Lowe, AND A. Williams. Estimation of physicochemical properties using WebTEST 2.0, a database centered modeling platform for building and deploying QSAR models. QSAR, Copenhagen, DENMARK, June 05 - 09, 2023. https://doi.org/10.23645/epacomptox.23280233.v1
Impact/Purpose:
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Description:
WebTEST2.0 is web-based platform for real-time predictions using QSAR (quantitative structure activity relationship) models stored in a PostgreSQL database. WebTEST2.0 can develop QSAR models using methodologies such as random forest, support vector machines, and k nearest neighbors. The independent variables for the models are molecular descriptors calculated using open-source packages such as PaDEL, T.E.S.T., and RDKit. In this study, WebTEST2.0 was utilized to build models for physicochemical properties including water solubility, vapor pressure, and octanol water partition coefficient. The underlying datasets for the models were constructed using data from many different publicly available data sources. External prediction results from WebTEST2.0 have been shown to be comparable to tools such as OPERA (Open (Quantitative) Structure-activity/property Relationship App). The views expressed here are those of the authors and do not necessarily represent the views or the policies of the U.S. Environmental Protection Agency.
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DOI: Estimation of physicochemical properties using WebTEST 2.0, a database centered modeling platform for building and deploying QSAR models
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