2024-03-28T20:29:12Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1114682016-02-18T03:07:05Zcom_10261_33com_10261_5com_10261_81col_10261_286col_10261_334
2015-02-27T10:05:08Z
urn:hdl:10261/111468
Predicting targets of compounds against neurological diseases using cheminformatic methodology
Nikolic, Katarina
Mavridis, L.
Bautista-Aguilera, Óscar M.
Marco-Contelles, José
Stark, H.
do Carmo Carreiras, María
Rossi, I.
Massarelli, P.
Agbaba, Danica
Ramsay, Rona R.
Mitchell, J. B. O.
ChE
Circular fingerprints
Off-target study
MAO
Histamine H3 receptor
Multi-targeted ligands
HMT
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 H3-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).
2015-02-27T10:05:08Z
2015-02-27T10:05:08Z
2015
2015-02-27T10:05:08Z
artículo
Journal of Computer-Aided Molecular Design 29: 183- 198 (2015)
http://hdl.handle.net/10261/111468
10.1007/s10822-014-9816-1
eng
closedAccess
Kluwer Academic Publishers