title: Development of a general quantum-chemical descriptor for steric effects: density functional theory based QSAR study of herbicidal sulfonylurea analogues.
abstract: Quantitative structure-activity relationship (QSAR) analysis has become one of the most effective approaches for optimizing lead compounds and designing new drugs. Although large number of quantum-chemical descriptors were defined and applied successfully, it is still a big challenge to develop a general quantum-chemical descriptor describing the bulk effects more directly and effectively. In this article, we defined a general quantum-chemical descriptor by characterizing the volume of electron cloud for specific substituent using the method of density functional theory. The application of our defined steric descriptors in the QSAR analysis of sulfonylurea analogues resulted in four QSAR models with high quality (the best model: q2 = 0.881, r2 = 0.901, n = 35, s = 0.401, F = 68.44), which indicated that this descriptor may provide an effective way for solving the problem how to directly describe steric effect in quantum chemistry-based QSAR studies.
authors.affiliation: State Key Laboratory of Elemento-Organic Chemistry and Department of Chemical Biology, Nankai University, Tianjin, People's Republic of China, 300071.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Xi
authors.forename: Zhihong
authors.initials: Z
authors.lastname: Yu
authors.forename: Congwei
authors.initials: C
authors.lastname: Niu
authors.forename: Shurong
authors.initials: S
authors.lastname: Ban
authors.forename: Guangfu
authors.initials: G
authors.lastname: Yang
mesh_terms: D006540:Herbicides / Q000737:chemistry*; D008958:Models, Molecular; D021281:Quantitative Structure-Activity Relationship; D011789:Quantum Theory; D013453:Sulfonylurea Compounds / Q000737:chemistry*
chemical_list: D006540:Herbicides; D013453:Sulfonylurea Compounds