Abstract
Stroke is the leading cause of death and disability worldwide, with a growing number of incidences in developing countries. However, there are currently few medical therapies for this disease. Emerged as an effective drug discovery strategy, drug repurposing which owns lower cost and shorter time, is able to identify new indications from existing drugs. In this study, we aimed at identifying potential drug candidates for stroke via computationally repurposing approved drugs from Drugbank database. We first developed a drug-target network of approved drugs, employed network-based approach to repurpose these drugs, and altogether identified 185 drug candidates for stroke. To validate the prediction accuracy of our network-based approach, we next systematically searched for previous literature, and found 68 out of 185 drug candidates (36.8 %) exerted therapeutic effects on stroke. We further selected several potential drug candidates with confirmed neuroprotective effects for testing their anti-stroke activity. Six drugs, including cinnarizine, orphenadrine, phenelzine, ketotifen, diclofenac and omeprazole, have exhibited good activity on oxygen-glucose deprivation/reoxygenation (OGD/R) induced BV2 cells. Finally, we showcased the anti-stroke mechanism of actions of cinnarizine and phenelzine via western blot and Olink inflammation panel. Experimental results revealed that they both played anti-stroke effects in the OGD/R induced BV2 cells via inhibiting the expressions of IL-6 and COX-2. In summary, this study provides efficient network-based methodologies for in silico identification of drug candidates toward stroke.