OBJECTIVES: The goal of this study is to develop a model used to predict octanol/water partition coefficients (log P(o/w)) values for a variety of potential dental materials. In this way, a primary consideration for potential toxicity and a rough estimate of solubility in various environments can be obtained. METHOD: The AM1 semiempirical quantum mechanical method (in AMPAC) was used to compute chemical data for all compounds in the study. CODESSA then imported the chemical information from AMPAC and computed a large set of informational descriptors. A quantitative structure activity relationship (QSAR) model was derived correlating experimental results from a training set of molecules with certain of the descriptors computed above. RESULTS: A training set of 92 molecules was used to derive the QSAR model and three descriptors were obtained: the molecular surface area, the total dipole moment of the molecule, and FPSA-3 (fractional atom charge weighted partial positive surface area). Various quality indicators were also computed and all fell within acceptable ranges: R(2)=0.945; adjusted R(2)=0.943; R(cv)(2)=0.940; variance inflation factors (VIF) for the descriptors above are 1.116, 1.044, and 1.162, respectively. SIGNIFICANCE: This QSAR model can be used to accurately and rapidly predict log P(o/w) values for a wide variety of small organic molecules, including potential dental monomers.
OBJECTIVES: The goal of this study is to develop a model used to predict octanol/water partition coefficients (log P(o/w)) values for a variety of potential dental materials. In this way, a primary consideration for potential toxicity and a rough estimate of solubility in various environments can be obtained. METHOD: The AM1 semiempirical quantum mechanical method (in AMPAC) was used to compute chemical data for all compounds in the study. CODESSA then imported the chemical information from AMPAC and computed a large set of informational descriptors. A quantitative structure activity relationship (QSAR) model was derived correlating experimental results from a training set of molecules with certain of the descriptors computed above. RESULTS: A training set of 92 molecules was used to derive the QSAR model and three descriptors were obtained: the molecular surface area, the total dipole moment of the molecule, and FPSA-3 (fractional atom charge weighted partial positive surface area). Various quality indicators were also computed and all fell within acceptable ranges: R(2)=0.945; adjusted R(2)=0.943; R(cv)(2)=0.940; variance inflation factors (VIF) for the descriptors above are 1.116, 1.044, and 1.162, respectively. SIGNIFICANCE: This QSAR model can be used to accurately and rapidly predict log P(o/w) values for a wide variety of small organic molecules, including potential dental monomers.