Conjoint analysis of single-cell sequencing and high-throughput virtual screening regarding DDR2 in osteoarthritis...

Osteoarthritis (OA) is a common degenerative joint disease, which is highly prevalent in the elderly, imposes a significant burden on patients and society. Aging, obesity, and inflammation are important factors contributing to the development of osteoarthritis. Currently, there are limited pharmaceutical treatment options for osteoarthritis: non-steroidal anti-inflammatory drugs or COX2 inhibitors are generally used for anti-inflammatory treatment of mild to moderate pain, and corticosteroid joint injections are used for severe pain. Discoidin domain receptor tyrosine kinase 2 (DDR2) is reported to be closely related to OA in recent studies. Single-cell RNA sequencing analysis in this study also proved that DDR2 was strongly expressed in some specific cell subsets. Current DDR2 inhibitor research focuses on developing antagonists to block type II collagen binding and receptor activation, thereby reducing MMP13 expression and promoting cartilage repair. At present, most of DDR2 inhibitors are still at the research stage in the laboratory and further development and improvement of these drug candidates are required. In this study, computer-aided drug design (CADD) techniques were used to screen potential lead compounds targeting DDR2. Candidate compounds were analyzed following different modules, such as Libdock, CDOCKER, TOPKAT, ADMET, and molecular dynamics simulation (MD) etc. Altogether, two natural lead compounds were ultimately identified with characterizations of high affinity and low drug toxicity in this study. One of the compounds ZINC000003874604 were selected for in vitro cell experiments. In-vitro experiments confirmed that the lead compound ZINC000003874604 could protect tBHP-induced primary chondrocytes of OA by inhibiting DDR2 expression. In summary, this study found that ZINC000003874604, as a lead compound, had potential therapeutic activity for OA, which may help provide more drug options in the pharmaceutical market.