We are pleased to announce that our two published models developed by Dr. Sehan Lee who is a former team leader in the Chemoinformatics Team are going to be part of PreADMET.
Generalized Solvation Free Energy Density (G-SFED)
– Generalized Solvation Free Energy Density (G-SFED) is a generalized version of the SFED with the purpose of predicting solvation free energies in virtually any solvent. In the model, the solvation free energy of a solute is represented as a linear combination of empirical functions of the solute properties representing the effects of solute on various solute-solvent interactions, and the complementary solvent effects on these interactions were reflected in the linear expansion coefficients with a few solvent properties.
G-SFED provides accurate prediction results for a wide range of sizes and polarities of solute molecules in various solvents as shown by a set of5,753 solvation free energies of diverse solute-solvent combinations as well as octanol-water partition coefficients of small organic compounds and peptides.
– Human nephrotoxicity prediction models provide prediction of three common patterns of drug-induced kidney injury, i.e., tubular necrosis, interstitial nephritis, and tubulo-interstitial nephritis. A Support Vector Machine (SVM) with clinical data on the nephrotoxicity of pharmacological compounds was used to build the binary classification models of nephrotoxin versus non-nephrotoxin with eight fingerprint descriptors.