Bioinformatics and network pharmacology analysis of drug targets and mechanisms related to the comorbidity of epilepsy and migraine

Abstract

ObjectiveThe present study aimed to explore the mechanisms underlying the comorbidity of epilepsy and migraine, identify potential common targets for drug intervention, and provide insight into new avenues for disease prevention and treatment using an integrated bioinformatic and network pharmacology approach. MethodsDisease targets in epilepsy and migraine were screened using the DisGeNET database to identify intersecting gene targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEEG) enrichment analyses were then performed using the WebGestalt database. Furthermore, the STRING database was used to construct a protein-protein interaction (PPI) network, and Cytoscape software was used to analyze the protein molecular signals at the intersection of epilepsy and migraine. The Drugbank database was used to identify common targets for antiepileptic drugs in epilepsy and migraine to further analyze the disease–gene–target–drug interaction network. Finally, molecular docking simulations were performed to verify the hypothesis that migraine and epilepsy share common diseases and drug targets. ResultsA total of 178 common targets for epilepsy and migraine were identified using the DisGeNET database, and the 24 genes most related to the diseases were screened using the Score_gda gene scoring system. GO enrichment analysis indicated that common targets were mainly enriched in biological processes and molecular functions, including membrane potential regulation, inorganic ion transmembrane transport, axonal signaling, and ion channel activity. KEGG pathway enrichment analysis indicated that the mechanism of action might be related to neuroactive ligand receptors, AGE-RAGE, cAMP, and VEGF signaling pathways. The PPI network construction and analysis results showed that the PPI grid had 23 central nodes and 24 connected edges, with an average node degree of 2.09 and an average clustering coefficient of 0.384. The 10 genes with potentially important roles in epilepsy and migraine were CACNA1A, KCNQ2, KCNA1, SCN1A, PRRT2, SCN8A, KCNQ3, SCN2A, GRIN2A, and GABRG2. Drugbank database results indicated that antiepileptic drugs, including lamotrigine, topiramate, valproic acid, carbamazepine, gabapentin, and perampanel, also had common targets with migraine. The three most important targets exhibited strong binding affinity with drugs in the molecular docking simulations. ConclusionOur systematic and comprehensive analyses of disease–gene–target–drug interaction networks identified several biological processes and molecular functions common to migraine and epilepsy, most of which were related to neuroactive ligand-receptor interactions. These data provide a new theoretical basis and reference for the clinical treatment of comorbid epilepsy and migraine and may aid in the development of novel pharmacological strategies.