Vilar Varela, SantiagoQuezada González, Elías NeftalíUriarte Villares, EugenioCostanzi, StefanoBorges, FernandaViña Castelao, María DoloresHripcsak, George2018-01-122018-01-122016-11-15Vilar, S. et al. Computational Drug Target Screening through Protein Interaction Profiles. Sci. Rep. 6, 36969; doi: 10.1038/srep36969 (2016)2045-2322http://hdl.handle.net/10347/16311The development of computational methods to discover novel drug-target interactions on a large scale is of great interest. We propose a new method for virtual screening based on protein interaction profile similarity to discover new targets for molecules, including existing drugs. We calculated Target Interaction Profile Fingerprints (TIPFs) based on ChEMBL database to evaluate drug similarity and generated new putative compound-target candidates from the non-intersecting targets in each pair of compounds. A set of drugs was further studied in monoamine oxidase B (MAO-B) and cyclooxygenase-1 (COX-1) enzyme through molecular docking and experimental assays. The drug ethoxzolamide and the natural compound piperlongumine, present in Piper longum L, showed hMAO-B activity with IC50 values of 25 and 65μM respectively. Five candidates, including lapatinib, SB-202190, RO-316233, GW786460X and indirubin-3′-monoxime were tested against human COX-1. Compounds SB-202190 and RO-316233 showed a IC50 in hCOX-1 of 24 and 25μM respectively (similar range as potent inhibitors such as diclofenac and indomethacin in the same experimental conditions). Lapatinib and indirubin3′-monoxime showed moderate hCOX-1 activity (19.5% and 28% of enzyme inhibition at 25μM respectively). Our modeling constitutes a multi-target predictor for large scale virtual screening with potential in lead discovery, repositioning and drug safety.eng© The Author(s) 2016. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by/4.0/Computational modelsTarget identificationjournal article10.1038/srep36969open access