Prediction of IC50 values for ACAT inhibitors from molecular structure.

A quantitative structure-activity study is performed on several series of compounds derived from N-chlorosulfonyl isocyanate to develop models that relate their structures to IC50 activity for inhibition of acyl-CoA:cholesterol O-acyltransferase (ACAT). Numerical descriptors are used to encode topological, electronic, and geometric information from the molecular structures of the inhibitors. A data set of 157 compounds showing triglyceride- and cholesterol-lowering activity is used to develop successful linear regression models and nonlinear computational neural network models. The models are validated using an external prediction set.