Review From in silico target prediction to multi-target drug design: Current databases, methods and applications Alexios Koutsoukas a , Benjamin Simms b , Johannes Kirchmair a , Peter J. Bond a , Alan V. Whitmore c , d , Steven Zimmer c , Malcolm P. Young c , e , Jeremy L. Jenkins b , Meir Glick b , Robert C. Glen a, ⁎ , Andreas Bender a, ⁎ a Unilever Centre for Molecular Sciences Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom b Lead Discovery Informatics, Center for Proteomic Chemistry, Novartis Institutes for Biomedical Research Inc., 250 Massachusetts Avenue, Cambridge, MA, 02139, USA c e-Therapeutics plc, Holland Park, Holland Drive, Newcastle upon Tyne, NE2 4LZ, United Kingdom d The School of Pharmacy, 29-39 Brunswick Square, London WC1N 1AX, United Kingdom e Institute of Neuroscience, University of Newcastle, Framlington Place, Newcastle upon Tyne, NE2 4HH, United Kingdom ARTICLE INFO ABSTRACT Article history: Received 21 January 2011 Accepted 6 May 2011 Available online 18 May 2011 Given the tremendous growth of bioactivity databases, the use of computational tools to predict protein targets of small molecules has been gaining importance in recent years. Applications span a wide range, from the ‘designed polypharmacology’ of compounds to mode-of-action analysis. In this review, we firstly survey databases that can be used for ligand-based target prediction and which have grown tremendously in size in the past. We furthermore outline methods for target prediction that exist, both based on the knowledge of bioactivities from the ligand side and methods that can be applied in situations when a protein structure is known. Applications of successful in silico target identification attempts are discussed in detail, which were based partly or in whole on computational target predictions in the first instance. This includes the authors' own experience using target prediction tools, in this case considering phenotypic antibacterial screens and the analysis of high-throughput screening data. Finally, we will conclude with the prospective application of databases to not only predict, retrospectively, the protein targets of a small molecule, but also how to design ligands with desired polypharmacology in a prospective manner. © 2011 Elsevier B.V. All rights reserved. Keywords: Target prediction Polypharmacology Mode of action Target fishing In silico Off targets Contents 1. Introduction ......................................................... 2555 2. Public and proprietary databases making bioactivity data available........................... 2556 JOURNAL OF PROTEOMICS 74 (2011) 2554 – 2574 ⁎ Corresponding authors. Tel.: +44 1223 336 432, +44 1223 762 983. E-mail addresses: rcg28@cam.ac.uk (R.C. Glen), ab454@cam.ac.uk (A. Bender). 1874-3919/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.jprot.2011.05.011 available at www.sciencedirect.com www.elsevier.com/locate/jprot