Estimation of physicochemical properties using WebTEST 2.0, a database centered modeling platform for building and deploying QSAR models email: martin.todd@epa.gov Overview of WebTEST 2.0 Martin, T1.; Ramsland, C.2; Charest, N.1; Lowe, C.1; Williams1, A. 1 US EPA/CCTE; 2 ORAU US EPA Disclaimer: The findings and conclusions in this poster have not been formally disseminated by the U.S. EPA and should not be construed to represent any agency determination or policy. WebTEST2.0’s database has the following schemas: Datasets, molecular descriptors, and QSAR methods can be versioned Schema Purpose exp_prop Raw experimental data qsar_datasets Datasets used for QSAR modeling qsar_descriptors Molecular descriptor values and QSAR ready SMILES qsar_models QSAR models, predictions, reports, and statistics QSAR Modeling Procedure Chemicals can be automatically mapped to DSSTox records using their source identifiers (name, CAS, SMILES) (or can be manually curated) Records are omitted if they have invalid molecular structures, property values, units, or experimental parameters A record for QSAR modeling consists of an identifier (e.g. QSAR ready smiles), the property value, and the molecular descriptor values WebTEST2.0 can generate Mordred, PaDEL, RDKit, ToxPrints, and WebTEST descriptors Using Python, WebTEST2.0 can develop random forest (RF), support vector machine (SVM), k Nearest neighbors (kNN), and consensus models Genetic algorithm (GA) feature selection can be used to tailor kNN models to specific datasets Physicochemical property data by source* Source HLC VP WS BP LogP MP Sum OChem 0 10241 17257 15365 38566 60424 141853 OPERA 694 2786 5074 5375 13549 8464 35942 Zang, et al 2017 N/A N/A N/A N/A 13798 N/A 13798 Open Melting Point Dataset N/A N/A N/A N/A N/A 11057 11057 PubChem N/A 0 2125 0 0 7896 10021 eChemPortalAPI 0 0 2129 0 0 5658 7787 AqSolDB N/A N/A 7374 N/A N/A N/A 7374 Sander 6322 N/A N/A N/A N/A N/A 6322 Kovdienko et al. 2010 N/A N/A 2593 N/A N/A N/A 2593 Bradley N/A N/A 2481 N/A N/A N/A 2481 QSARDB N/A 34 945 N/A 607 807 2393 Yalkowsky et al. 2002 N/A N/A 1017 N/A 691 N/A 1708 Oxford University Chemical Safety Data N/A N/A N/A 0 N/A 1205 1205 Tetko et al. 2001 N/A N/A 1103 N/A N/A N/A 1103 Lewis et al. 2016 N/A N/A 1065 N/A N/A N/A 1065 … Sum 7279 13680 44566 22118 67584 96009 251236 Property Property Range Parameter range Raw Mapped Flattened* HLC 1e-13<HLC (atm m3/mol)<1e2 20<T(C)<30 6.5<pH< 7.5 10521 7279 1910 VP 1e-14<VP(mmHg)<1e6 20<T(C)<30 34849 13680 3454 BP -150<BP(°C)<800 740 < P (mmHg) < 780 375470 22118 7061 WS 1e-14<WS(M)<100 1e-11<WS(g/L)<990 20<T(C)<30 740<P(mmHg)<780 6.5<pH< 7.5 82142 44566 9814 LogP -6<LogKow)<11 20<T(C)<30 107514 67584 14711 MP -250<MP(°C)<550 740 < P (mmHg) < 780 450775 96009 29513 * Number of records which can be mapped to DSSTox structures * Flattened records (one property value per structure) are used for modeling Physicochemical property data sets Modeling results Dataset knn rf xgb svm con HLC 0.70 0.81 0.82 0.80 0.82 VP 0.85 0.89 0.90 0.88 0.91 WS 0.76 0.82 0.82 0.82 0.84 BP 0.70 0.75 0.76 0.72 0.77 LogP 0.82 0.87 0.90 0.91 0.91 MP 0.65 0.74 0.76 0.76 0.77 Average 0.75 0.81 0.83 0.82 0.84 Q2_CV Dataset knn rf xgb svm con HLC 0.77 0.86 0.85 0.84 0.87 VP 0.87 0.90 0.92 0.89 0.92 WS 0.78 0.84 0.84 0.84 0.86 BP 0.74 0.76 0.77 0.72 0.78 LogP 0.84 0.89 0.91 0.93 0.93 MP 0.67 0.75 0.76 0.77 0.78 Average 0.78 0.83 0.84 0.83 0.86 R2_Test 2.0 HLC WS VP HLC WS VP Beta: https://www.epa.gov/chemical-research/cheminformatics QMRF Excel model summary Pred. report WebTEST2.0 Prediction report