title: Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.
abstract: We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.
authors.affiliation: Fraunhofer FIRST, Kekuléstrasse 7, 12489, Berlin, Germany. timon.schroeter@first.fraunhofer.de
authors.forename: Timon Sebastian
authors.initials: TS
authors.lastname: Schroeter
authors.forename: Anton
authors.initials: A
authors.lastname: Schwaighofer
authors.forename: Sebastian
authors.initials: S
authors.lastname: Mika
authors.forename: Antonius
authors.initials: A
authors.lastname: Ter Laak
authors.forename: Detlev
authors.initials: D
authors.lastname: Suelzle
authors.forename: Ursula
authors.initials: U
authors.lastname: Ganzer
authors.forename: Nikolaus
authors.initials: N
authors.lastname: Heinrich
authors.forename: Klaus-Robert
authors.initials: KR
authors.lastname: Müller
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001499:Bayes Theorem; D008956:Models, Chemical; D015233:Models, Statistical; D015394:Molecular Structure; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D012995:Solubility
chemical_list: D004364:Pharmaceutical Preparations