Integrating network pharmacology and molecular docking for the identification of key genes and therapeutic targets of Nigella sativa in multiple sclerosis treatment

Abstract

Introduction and Aim: Multiple sclerosis (MS) is a chronic neurodegenerative disease affecting around 2.8 million people worldwide. MS pathophysiology is not yet explained up to the mark, which is the cause of difficulty and complexity in treating the illness. Most present-day scenarios are engrossed in inhibiting central nervous system (CNS) inflammation. However, this is not enough, hence the present study aims at finding best neuroprotective treatment without adverse effects.   Materials and Methods: In silico attempt to validate the phytocompounds from Nigella sativa and showcase their use for targeting the neuroprotective mechanism involved in management of MS by finding the key potential genes which were derived from mRNA datasets of previous research. Various bioinformatics tools and software such as GEO, String, ShinyGO, PyRx were used to carry out the current study. The leading steps involve retrieval of targets from mRNA datasets, molecular docking of phytocompounds with the targets and pharmacological analysis.   Results: These phytocompounds from seeds of N. sativa showed promising results as therapeutic agents against target genes RPL27, RPS14 and FAU for management of MS during current in silico study, but any treatment prior its clinical practice should validate with large robust data, which lies as the future prospective here.   Conclusion: In summary notable progress in management of MS with better understanding of pathology has been made and many disease modifying therapies (DMT) are made available but the question of safety and efficacy is still challenging due to adverse effects associated with these therapies. Hence properties of N. sativa must be explored as a therapeutic agent that can reduce the neuronal degeneration.