A systems-level framework for drug discovery identifies Csf1R as an anti-epileptic drug target

Prashant K. Srivastava, Jonathan van Eyll, Patrice Godard, Manuela Mazzuferi, Andree Delahaye-Duriez, Juliette Van Steenwinckel, Pierre Gressens, Benedicte Danis, Catherine Vandenplas, Patrik Foerch, Karine Leclercq, Georges Mairet-Coello, Alvaro Cardenas, Frederic Vanclef, Liisi Laaniste, Isabelle Niespodziany, James Keaney, Julien Gasser, Gaelle Gillet, Kirill Shkura, Seon-Ah Chong, Jacques Behmoaras, Irena Kadiu, Enrico Petretto (), Rafal M. Kaminski () and Michael R. Johnson ()
Additional contact information
Prashant K. Srivastava: Imperial College London
Jonathan van Eyll: UCB Pharma
Patrice Godard: Clarivate Analytics (formerly the IP & Science Business of Thomson Reuters)
Manuela Mazzuferi: UCB Pharma
Andree Delahaye-Duriez: Imperial College London
Juliette Van Steenwinckel: Université Paris Diderot
Pierre Gressens: Université Paris Diderot
Benedicte Danis: UCB Pharma
Catherine Vandenplas: UCB Pharma
Patrik Foerch: UCB Pharma
Karine Leclercq: UCB Pharma
Georges Mairet-Coello: UCB Pharma
Alvaro Cardenas: UCB Pharma
Frederic Vanclef: UCB Pharma
Liisi Laaniste: Imperial College London
Isabelle Niespodziany: UCB Pharma
James Keaney: UCB Pharma
Julien Gasser: UCB Pharma
Gaelle Gillet: UCB Pharma
Kirill Shkura: Imperial College London
Seon-Ah Chong: UCB Pharma
Jacques Behmoaras: Imperial College London
Irena Kadiu: UCB Pharma
Enrico Petretto: Centre for Computational Biology
Rafal M. Kaminski: UCB Pharma
Michael R. Johnson: Imperial College London

Nature Communications, 2018, vol. 9, issue 1, 1-15

Abstract: Abstract 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.

Date: 2018
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DOI: 10.1038/s41467-018-06008-4

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