In-silico Identification of Novel Drug Target for Osteoarthritis using Network Biology Approaches

Abstract

Osteoarthritis (OA) is a degenerative joint disease which is the leading cause for physical disability among the adult population and yet the mechanisms responsible for the development and progression are not well understood. Since it has no curative solutions, treatment is limited to symptomatic targeting and improving quality of life. There is a lack of disease-modifying therapeutics and non-surgical intervention options to prevent the progression of disease. Risk factors range from systemic (e.g. age, sex, genetics, obesity) to biochemical (e.g. joint injury, muscle weakness, sport). The prevalence of OA is ever increasing due to the ageing global population and the obesity epidemic. Since OA exhibits strong genetic predisposition and a complex pathogenesis, we applied an in silico network biology approaches to identify a candidate gene using a protein-protein interaction (PPI) network of OA, which may be an important aspect of disease pathogenesis and assist us in furthering our understanding of the development and progression of the disease as well as identify a drug-lead for the treatment of joint-pain associated with OA and improving quality of life in patients without lasting side effects. Our findings suggest that phytochemical compounds may be promising candidates for multi-target application against OA and will assist in development of new molecules.