Integration of the Computational Tools to Decode the Mode of Action of Citrus limon against Alzheimer’s Disease

Abstract

Objective: The study purpose is to identify the potential of Citrus limon in the pharmacotherapy of Alzheimer’s disease (AD) via a network pharmacology approach. Methods: ChEBI database was used to retrieve structural information of C. limon bioactive phytoconstituents. Targets of these compounds were selected by Swiss Target Prediction. Potential targets of AD were downloaded from the DisGeNet database. Phytoconstituents were predicted for their drug-likeness score, probable side effects, and ADMET profile. The interaction between compounds, proteins and pathways were interpreted using edge count from Cytoscape. For the docking research, Maestro software was used. Results: Seven phytoconstituents of C. limon have been found to have the ability to modify pathogenic protein molecules involved in AD. Theophylline exhibited the highest drug-likeness score and the most interacted compound with proteins involved in Alzheimer's disease. In addition, metabolic pathway was majorly regulated. Conclusion: Hence, theophylline was identified as an important AD constituent, which modulated majority of AD proteins.