10.5061/DRYAD.86088N1
Noori, Hamid R.
Central Institute of Mental Health
Mervin, Lewis H.
University of Cambridge
Bokharaie, Vahid
Max Planck Institute for Biological Cybernetics
Durmus, Özlem
Central Institute of Mental Health
Egenrieder, Lisamon
Central Institute of Mental Health
Fritze, Stefan
Central Institute of Mental Health
Gruhlke, Britta
Central Institute of Mental Health
Reinhardt, Guilia
Central Institute of Mental Health
Schabel, Hans-Hendrik
Central Institute of Mental Health
Staudenmaier, Sabine
Central Institute of Mental Health
Logothetis, Nikos K.
Max Planck Institute for Biological Cybernetics
Bender, Andreas
University of Cambridge
Spanagel, Rainer
Central Institute of Mental Health
Data from: Systemic neurotransmitter responses to clinically approved and
experimental neuropsychiatric drugs
Dryad
dataset
2018
Neurotransmitter response patterns
Neuropsychiatric drugs
2018-11-08T22:06:32Z
2018-11-08T22:06:32Z
en
https://doi.org/10.1038/s41467-018-07239-1
847088 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Neuropsychiatric disorders are the third leading cause of global disease
burden. Current pharmacological treatment for these disorders is
inadequate, with often insufficient efficacy and undesirable side effects.
One reason for this is that the links between molecular drug action and
neurobehavioral drug effects are elusive. We use a big data approach from
the neurotransmitter response patterns of 258 different neuropsychiatric
drugs in rats to address this question. Data from experiments comprising
110,674 rats are presented in the Syphad database [www.syphad.org].
Chemoinformatics analyses of the neurotransmitter responses suggest a
mismatch between the current classification of neuropsychiatric drugs and
spatiotemporal neurostransmitter response patterns at the systems level.
In contrast, predicted drug–target interactions reflect more appropriately
brain region related neurotransmitter response. In conclusion the
neurobiological mechanism of neuropsychiatric drugs are not well reflected
by their current classification or their chemical similarity, but can be
better captured by molecular drug–target interactions.
Supplementary_Data_NooriDownloadable version of syphad database