SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules

Author:

Daina Antoine1ORCID,Michielin Olivier12,Zoete Vincent13

Affiliation:

1. Molecular Modeling Group, SIB Swiss Institute of Bioinformatics, University of Lausanne, Quartier UNIL-Sorge, Bâtiment Amphipôle, CH-1015 Lausanne, Switzerland

2. Department of Oncology, University Hospital of Lausanne, Ludwig Cancer Research – Lausanne Branch, CH-1011 Lausanne, Switzerland

3. Department of Fundamental Oncology, University of Lausanne, Ludwig Cancer Research – Lausanne Branch, Route de la Corniche 9A, CH-1066 Epalinges, Switzerland

Abstract

Abstract SwissTargetPrediction is a web tool, on-line since 2014, that aims to predict the most probable protein targets of small molecules. Predictions are based on the similarity principle, through reverse screening. Here, we describe the 2019 version, which represents a major update in terms of underlying data, backend and web interface. The bioactivity data were updated, the model retrained and similarity thresholds redefined. In the new version, the predictions are performed by searching for similar molecules, in 2D and 3D, within a larger collection of 376 342 compounds known to be experimentally active on an extended set of 3068 macromolecular targets. An efficient backend implementation allows to speed up the process that returns results for a druglike molecule on human proteins in 15–20 s. The refreshed web interface enhances user experience with new features for easy input and improved analysis. Interoperability capacity enables straightforward submission of any input or output molecule to other on-line computer-aided drug design tools, developed by the SIB Swiss Institute of Bioinformatics. High levels of predictive performance were maintained despite more extended biological and chemical spaces to be explored, e.g. achieving at least one correct human target in the top 15 predictions for >70% of external compounds. The new SwissTargetPrediction is available free of charge (www.swisstargetprediction.ch).

Funder

Swiss Institute of Bioinformatics

Publisher

Oxford University Press (OUP)

Subject

Genetics

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