Neuroprotective drug for nerve trauma revealed using artificial intelligence

Here we used a systems biology approach and artificial intelligence to identify a neuroprotective agent for the treatment of peripheral nerve root avulsion. Based on accumulated knowledge of the neurodegenerative and neuroprotective processes that occur in motoneurons after root avulsion, we built up protein networks and converted them into mathematical models. Unbiased proteomic data from our preclinical models were used for machine learning algorithms and for restrictions to be imposed on mathematical solutions. Solutions allowed us to identify combinations of repurposed drugs as potential neuroprotective agents and we validated them in our preclinical models. The best one, NeuroHeal, neuroprotected motoneurons, exerted anti-inflammatory properties and promoted functional locomotor recovery. NeuroHeal endorsed the activation of Sirtuin 1, which was essential for its neuroprotective effect. These results support the value of network-centric approaches for drug discovery and demonstrate the efficacy of NeuroHeal as adjuvant treatment with surgical repair for nervous system trauma.
This work was mainly supported by a grant from Fundació La Marató-TV3 (#110432, CC, AB & VP) that funded the work and contracts of TLR and MHG and partially by the Ministerio de Economía y Competitividad of Spain (#SAF 2014-59701, CC, DRG, & TLR). We are also grateful for support from CIBERNED and funding from the European Union Seventh Framework Programme for research, technological development, and demonstration (#306240, XN, FRP & CC). Part of the research leading to these results has also received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 306240.