Propersea (Property Prediction)

Propersea contains calculated predictions for a wide range of molecular and physicochemical properties for small molecules, such as melting and boiling points, density, solubility, polarizability, and more. It employs various algorithms, including RDKit, semi-empirical quantum methods, Bayesian regression trees, and transformer neural networks. Propersea also contains predicted IUPAC names generated using a machine learning model. Propersea can be searched using the PSDI Cross Data Search service using InChIs, SMILES or by drawing a molecule. Results include predicted values, confidence intervals and reliability scores for the prediction.