A systems-level framework for drug discovery identifies Csf1R as an anti-epileptic drug target.
Prashant K SrivastavaJonathan van EyllPatrice GodardManuela MazzuferiAndrée Delahaye-DuriezJuliette Van SteenwinckelPierre GressensBenedicte DanisCatherine VandenplasPatrik FoerchKarine LeclercqGeorges Mairet-CoelloAlvaro CardenasFrederic VanclefLiisi LaanisteIsabelle NiespodzianyJames KeaneyJulien GasserGaelle GilletKirill ShkuraSeon-Ah ChongJacques BehmoarasIrena KadiuEnrico PetrettoRafal M KaminskiMichael R JohnsonPublished in: Nature communications (2018)
The identification of drug targets is highly challenging, particularly for diseases of the brain. To address this problem, we developed and experimentally validated a general computational framework for drug target discovery that combines gene regulatory information with causal reasoning ("Causal Reasoning Analytical Framework for Target discovery"-CRAFT). Using a systems genetics approach and starting from gene expression data from the target tissue, CRAFT provides a predictive framework for identifying cell membrane receptors with a direction-specified influence over disease-related gene expression profiles. As proof of concept, we applied CRAFT to epilepsy and predicted the tyrosine kinase receptor Csf1R as a potential therapeutic target. The predicted effect of Csf1R blockade in attenuating epilepsy seizures was validated in three pre-clinical models of epilepsy. These results highlight CRAFT as a systems-level framework for target discovery and suggest Csf1R blockade as a novel therapeutic strategy in epilepsy. CRAFT is applicable to disease settings other than epilepsy.
Keyphrases
- tyrosine kinase
- gene expression
- small molecule
- drug discovery
- high throughput
- genome wide
- temporal lobe epilepsy
- epidermal growth factor receptor
- healthcare
- risk assessment
- emergency department
- multiple sclerosis
- drug induced
- transcription factor
- health information
- climate change
- big data
- artificial intelligence
- binding protein
- copy number
- subarachnoid hemorrhage
- cerebral ischemia
- bioinformatics analysis