2002 Volume 3 Pages 99-106
In 3D-QSAR analysis such as comparative molecular field analysis (CoMFA), proper superimposition of molecules is required. Since appropriate superimposition is an important factor for construction of predictive model, various methodologies for molecular alignment have been proposed. We have proposed the novel molecular alignment method using Hopfield Neural Network (HNN). In this paper, 3D-QSAR analysis of human epidermal growth factor receptor-2 (HER2) inhibitors which consist of two different types of skeleton, was reported. The structures of HER2 inhibitors were automatically aligned using HNN and then the correlation between the HER2 activity and the molecular fields was analyzed by PLS. The robust PLS model (R²=0.805, Q²=0.701) was obtained and it was validated by contour map of the regression coefficients.
