Computational evaluation of leflunomide and ticagrelor combination targeting the A2A receptor for the management of rheumatoid arthritis.

BACKGROUND

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by progressive joint damage and inflammation, which leads to a reduction in patients' quality of life. Traditional therapies are inadequate to eradicate these illnesses. Therefore, cutting-edge therapeutic approaches are required to eradicate these challenges and improve patients' lives.

OBJECTIVES

In the current research work, computational analysis of ticagrelor, a purinergic P2Y G protein-coupled receptor antagonist (P2Y12) that increases extracellular adenosine by blocking equilibrative nucleoside transporter-1 (ENT-1), combined with leflunomide, a traditional disease-modifying anti-rheumatic drug (DMARD), was investigated. Additionally, the study hypothesizes that increased levels of adenosine may activate anti-inflammatory adenosine receptor (A2A) and enhance leflunomide's immunomodulatory effects.

METHODS

Molecular docking was performed using the Python Prescription (PyRx) tool, which integrates with AutoDock Vina and AutoDock 4, providing an optimal balance between computational speed and flexibility.

RESULTS

Molecular docking demonstrates strong affinities to A2AR Leflunomide -8.7Kcal/mol; and Ticagrelor -8.0 Kcal/mol. Both compounds showed low toxicity according to Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) profiling using Swiss-ADME and ADMETSAR.

CONCLUSION

Based on initial in-silico findings, the combination of leflunomide and ticagrelor appears to be a promising treatment approach for RA, which warrants further experimental confirmation.