title: General and class specific models for prediction of soil sorption using various physicochemical descriptors.
abstract: Diverse chemical descriptors were explored for use in QSAR models aimed to screen the soil sorption potential of organic compounds. The descriptors included logP, HyperChem QSARProperties descriptors, a combination of connectivity indices, geometrical, and quantum chemical measures, and two sets from the DRAGON and CODESSA program packages, respectively. Generally, the univariate logP models were capable of capturing most of the variation and give an indication of the sorption potential. The multivariate models required refined variable selection procedures but were shown to include crucial descriptors for modeling compound classes with specific chemical characteristics.
authors.affiliation: Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80176, 3508 TD Utrecht, The Netherlands. patrik.andersson@chem.umu.se
authors.forename: Patrik L
authors.initials: PL
authors.lastname: Andersson
authors.forename: Uko
authors.initials: U
authors.lastname: Maran
authors.forename: Dan
authors.initials: D
authors.lastname: Fara
authors.forename: Mati
authors.initials: M
authors.lastname: Karelson
authors.forename: Joop L M
authors.initials: JL
authors.lastname: Hermens
mesh_terms: D008956:Models, Chemical; D015394:Molecular Structure; D009930:Organic Chemicals / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D012984:Software; D012987:Soil / Q000032:analysis*
chemical_list: D009930:Organic Chemicals; D012987:Soil