Abstract
Computational methods for Target Fishing (TF), also known as Target Prediction or Polypharmacology Prediction, can be used to discover new targets for small-molecule drugs. This may result in repositioning the drug in a new indication or improving our current understanding of its efficacy and side effects. While there is a substantial body of research on TF methods, there is still a need to improve their validation, which is often limited to a small part of the available targets and not easily interpretable by the user. Here we discuss how target-centric TF methods are inherently limited by the number of targets that can possibly predict (this number is by construction much larger in ligand-centric techniques). We also propose a new benchmark to validate TF methods, which is particularly suited to analyse how predictive performance varies with the query molecule. On average over approved drugs, we estimate that only five predicted targets will have to be tested to find two true targets with submicromolar potency (a strong variability in performance is however observed). In addition, we find that an approved drug has currently an average of eight known targets, which reinforces the notion that polypharmacology is a common and strong event. Furthermore, with the assistance of a control group of randomly-selected molecules, we show that the targets of approved drugs are generally harder to predict. The benchmark and a simple target prediction method to use as a performance baseline are available at http://ballester.marseille.inserm.fr/TF-benchmark.tar.gz.
Highlights
Target Fishing (TF) (Cereto-Massagué et al, 2015; Lavecchia and Cerchia, 2015), known as Target Prediction or Polypharmacology Prediction, consists in predicting the macromolecular targets of a query molecule
The analysis is based on the performance obtained by the query molecules in the four datasets in Table 2, which will be summarized with boxplots of precision, recall, Matthews Correlation Coefficient (MCC) and Number of Predicted Targets (NPT)
Target-centric methods powered by models requiring at least 40 ligands per target and defining a target with an activity threshold of 10 μM would be predicting whether the query molecule has activity against any of the 917 qualifying single-protein targets
Summary
Target Fishing (TF) (Cereto-Massagué et al, 2015; Lavecchia and Cerchia, 2015), known as Target Prediction or Polypharmacology Prediction, consists in predicting the macromolecular targets of a query molecule. Discovering a new target for a drug could lead to its reposition in a new indication as well as an enhanced understanding of its efficacy and side-effects (Huang et al, 2014) These tools can be used for target deconvolution of phenotypic screening hits (Lee and Bogyo, 2013), which is a prerequisite to gain mechanistic understanding of phenotypic activity and helpful for drug development. This two-stage process, phenotypic screening followed by Ligand-Centric Methods for Target Fishing target deconvolution, constitutes an attractive alternative strategy for the discovery of molecularly targeted therapies
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