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Predicting targets of compounds against neurological diseases using cheminformatic methodology

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nov19revised_JCAM_D_14_00189R2.pdf (2.295Mb)
Date
02/2015
Author
Nikolic, Katarina
Mavridis, Lazaros
Bautista-Aguilera, Oscar M.
Marco-Contelles, Jose
Stark, Holger
Carreiras, Maria do Carmo
Rossi, Ilaria
Massarelli, Paola
Agbaba, Danica
Ramsay, Rona R.
Mitchell, John B. O.
Keywords
Multi-targeted ligands
Circular fingerprints
Off-target study
ChE
MAO
Histamine H3 receptor
HMT
QR Microbiology
QA76 Computer software
R Medicine (General)
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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 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).
Citation
Nikolic , K , Mavridis , L , Bautista-Aguilera , O M , Marco-Contelles , J , Stark , H , Carreiras , M D C , Rossi , I , Massarelli , P , Agbaba , D , Ramsay , R R & Mitchell , J B O 2015 , ' Predicting targets of compounds against neurological diseases using cheminformatic methodology ' , Journal of Computer-Aided Molecular Design , vol. 29 , no. 2 , pp. 183-198 . https://doi.org/10.1007/s10822-014-9816-1
Publication
Journal of Computer-Aided Molecular Design
Status
Peer reviewed
DOI
https://doi.org/10.1007/s10822-014-9816-1
ISSN
0920-654X
Type
Journal article
Rights
Copyright 2014. Springer International Publishing Switzerland. The final publication is available at Springer via http://dx.doi.org/10.1007/s10822-014-9816-1
Description
The authors acknowledge financial support from the Scottish Universities Life Sciences Alliance (SULSA). OMBA and JMC thank MINECO (Spain) for a fellowship, and support (SAF2012-33304), respectively. KN and DA acknowledge project supported by the Ministry of Education and Science of the Republic of Serbia, Contract No. 172033. Further supports by Else Kroner-Fresenius-Stiftung, Translational Research Innovation—Pharma (TRIP), Fraunhofer-Projektgruppe fur Translationale Medizin und Pharmakologie (TMP) (to HS) and the European COST Actions BM1007, CM1103 (including STSM 10295 to KN), and CM1207 are also gratefully acknowledged.
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/7849

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