@article{
author = "Nikolić, Katarina and Mavridis, Lazaros and Bautista-Aguilera, Oscar M. and Marco-Contelles, Jose and Stark, Holger and Carreiras, Maria do Carmo and Rossi, Ilaria and Massarelli, Paola and Agbaba, Danica and Ramsay, Rona R. and Mitchell, John B. O.",
year = "2015",
abstract = "Recently developed multi-targeted ligands are novel drug candidates able to interact with monoamine oxidase A and B; acetylcholinesterase and butyrylcholinesterase; or with histamine N-methyltransferase and histamine H-3-receptor (H3R). These proteins are drug targets in the treatment of depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease. A probabilistic method, the Parzen-Rosenblatt window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Molecular structures were represented based on the circular fingerprint methodology. The same approach was used to build a "predictor" model from the DrugBank dataset to determine the main pharmacological groups of the compound. The study of off-target interactions is now recognised as crucial to the understanding of both drug action and toxicology. Primary pharmaceutical targets and off-targets for the novel multi-target ligands were examined by use of the developed cheminformatic method. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. The cheminformatic targets identifications were in agreement with four 3D-QSAR (H3R/D1R/D2R/5-HT2aR) models and by in vitro assays for serotonin 5-HT1a and 5-HT2a receptor binding of the most promising ligand (71/MBA-VEG8).",
publisher = "Springer, Dordrecht",
journal = "Journal of Computer-Aided Molecular Design",
title = "Predicting targets of compounds against neurological diseases using cheminformatic methodology",
volume = "29",
number = "2",
pages = "183-198",
doi = "10.1007/s10822-014-9816-1"
}