title: Comparison of different approaches to define the applicability domain of QSAR models.
abstract: One of the OECD principles for model validation requires defining the Applicability Domain (AD) for the QSAR models. This is important since the reliable predictions are generally limited to query chemicals structurally similar to the training compounds used to build the model. Therefore, characterization of interpolation space is significant in defining the AD and in this study some existing descriptor-based approaches performing this task are discussed and compared by implementing them on existing validated datasets from the literature. Algorithms adopted by different approaches allow defining the interpolation space in several ways, while defined thresholds contribute significantly to the extrapolations. For each dataset and approach implemented for this study, the comparison analysis was carried out by considering the model statistics and relative position of test set with respect to the training space.
authors.affiliation: Milano Chemometrics and QSAR Research Group, Department of Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1-20126 Milano, Italy.
authors.forename: Faizan
authors.initials: F
authors.lastname: Sahigara
authors.forename: Kamel
authors.initials: K
authors.lastname: Mansouri
authors.forename: Davide
authors.initials: D
authors.lastname: Ballabio
authors.forename: Andrea
authors.initials: A
authors.lastname: Mauri
authors.forename: Viviana
authors.initials: V
authors.lastname: Consonni
authors.forename: Roberto
authors.initials: R
authors.lastname: Todeschini
mesh_terms: D000465:Algorithms; D008956:Models, Chemical; D015233:Models, Statistical; D021281:Quantitative Structure-Activity Relationship