Computational Insights on Migraine and Anxiety in Association with BDNF

Abstract

Background:: Migraine is an unusual piercing headache on one side of the head. It is due to the dysregulation of epigenetic factors associated with the brain. Migraine affects about one percent of the general population. Despite the recent implementation of worldwide diagnostic criteria for migraine, this disorder remains relatively unknown and is frequently underdiagnosed. Migrainous conditions are also associated with anxiety and stress. This pathologic condition affects the daily life and productivity of the patients. Objective:: Hence, there is a need to develop proper treatment and management strategies to cope with migraine and associated anxiety. Through in silico approaches, this work elucidates to identify the effective lead compounds for migraine and anxiety. Methods:: Brain-derived neurotrophic factor (BDNF) was identified as a possible target for treating migraine and anxiety using computational analysis. Virtual screening and molecular dynamics simulation were used to find potential agonists with high affinities for BDNF. Results:: Based on the results of computational analysis (glide XP score, number of interactions, glide energy, and pharmacokinetic factors), four top hit molecules (Asinex_35922, Enamine_44630, Maybridge_1999, and SMMDB_17457) were identified and taken for further analysis. The hydrogen bond interactions between the agonists and the BDNF protein were verified by dynamics analysis Conclusion:: Computational studies support that BDNF agonist molecules could be effective regulating molecules for migraine and anxiety. For further evidence of the effectiveness of lead compounds in treating migraine and related anxiety, more experimental studies are necessary.