NETWORK PHARMACOLOGY AND MOLECULAR DOCKING-BASED PREDICTIONS OF PHARMACOLOGICAL EFFECTS OF FERULIC ACID

Abstract

Objectives: The main objective of this study is to reveal new possible pharmacological effects of ferulic acid. This is achieved by network pharmacology by discovering potential target genes for ferulic acid, along with constructing a PPI network for those targets and performing gene enrichment analysis to understand possible diseases or disorders being affected due to the target genes. The study involves the molecular docking of target genes with ferulic acid to understand the interactions between them. Methods: ADMETlab 2.0 was used for the pharmacokinetics study of ferulic acid. Using SwissTargetPrediction and STITCH database 79 target genes were retrieved which were used to construct a PPI network using the STRING database and for gene enrichment analysis using the ShinyGo tool. Analyzing the clusters generated by k-means clustering in the STRING database, three target gene proteins were further used to perform molecular docking with ferulic acid using PyRx software, and 2D and 3D visualization was done using Biovia Discovery Studio Visualizer. Results: The ADMET analysis ferulic acid showed drug-likeliness. SwissTargetPrediction and STITCH database revealed 79 potential target genes. Three proteins (RELA, ALOX15, and STAT3) were selected from the PPI network analysis using the STRING database for molecular docking and visualization. ALOX15 showed the least binding energy among all three target proteins. Gene enrichment analysis suggests the target proteins are involved in cancer, neurological disorders, psychiatric disorders, Alzheimer’s disease, etc. Conclusion: The findings of this research suggest that ferulic acid may have a wide range of pharmacological effects and gives a new perspective on its application in the field of drug discovery.