title: Effective descriptions of molecular structures and the quantitative structure-activity relationship studies.
abstract: In this research, we found CoMFA alone could not obtain sufficiently a strong equation to allow confident prediction for aminobenzenes. When some other parameter, such as heat of molecular formation of the compounds, was introduced into the CoMFA model, the results were improved greatly. It gives us a hint that a better description for molecular structures will yield a better prediction model, and this hint challenged us to look for another method--the projection areas of molecules in 3D space for 3D-QSAR. It is surprising that much better results than that obtained by using CoMFA were achieved. Besides the CoMFA analysis, multiregression analysis and neural network methods for building the models were used in this paper.
authors.affiliation: Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People's Republic of China. luxu@ns.ciac.jl.cn
authors.forename: Lu
authors.initials: L
authors.lastname: Xu
authors.forename: Jia-An
authors.initials: JA
authors.lastname: Yang
authors.forename: Ya-Ping
authors.initials: YP
authors.lastname: Wu