title: Convenient QSAR model for predicting the complexation of structurally diverse compounds with beta-cyclodextrins.
abstract: This paper reports a QSAR study for predicting the complexation of a large and heterogeneous variety of substances (233 organic compounds) with beta-cyclodextrins (beta-CDs). Several different theoretical molecular descriptors, calculated solely from the molecular structure of the compounds under investigation, and an efficient variable selection procedure, like the Genetic Algorithm, led to models with satisfactory global accuracy and predictivity. But the best-final QSAR model is based on Topological descriptors meanwhile offering a reasonable interpretation. This QSAR model was able to explain ca. 84% of the variance in the experimental activity, and displayed very good internal cross-validation statistics and predictivity on external data. It shows that the driving forces for CD complexation are mainly hydrophobic and steric (van der Waals) interactions. Thus, the results of our study provide a valuable tool for future screening and priority testing of beta-CDs guest molecules.
authors.affiliation: Enviromental Engineering and Toxicology Dpt., Catholic University of San Antonio, Murcia, C.P., Guadalupe 30107, Spain. Aperez@pdi.ucam.edu
authors.forename: Alfonso
authors.initials: A
authors.lastname: Pérez-Garrido
authors.forename: Aliuska
authors.initials: A
authors.lastname: Morales Helguera
authors.forename: Adela
authors.initials: A
authors.lastname: Abellán Guillén
authors.forename: M Natália D S
authors.initials: MN
authors.lastname: Cordeiro
authors.forename: Amalio
authors.initials: A
authors.lastname: Garrido Escudero
mesh_terms: D057927:Hydrophobic and Hydrophilic Interactions; D009930:Organic Chemicals / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D047392:beta-Cyclodextrins / Q000737:chemistry* / Q000494:pharmacology
chemical_list: D009930:Organic Chemicals; D047392:beta-Cyclodextrins