Abstract
A wide variety of cellular mechanisms such as cell division and metabolic processes are maintained by protein-protein interactions (PPIs). The identification of PPI through laboratory techniques is costly, time-consuming, difficult, and challenging. However, computational techniques were generated for PPIs prediction. In alfalfa (Madicago sativa), PPI was predicted among 12 MsMAPKs and 4 MsPP2Cs using a docking approach. For homology modelling, the Swiss model was employed while PROCHECK, ERRAT, and Verify3D were used to validate 3D models. The Ramachandran plots were obtained from PROCHECK which showed value more than 90% (nPP2C1, PP2C1, PP2C, and MSK-3 revealed 92.9%, 94.2%, 92.4%, and 91.1% respectively) for high-quality structures. The HawkDock server and the BIPSPI server were used to analyse protein docking and predict interaction sites, respectively. Our findings demonstrated that MsPP2C docking sites play an important role in the identification and docking of MsMAPKs. The binding free energy ranged from -0.16Kcal/mol to -49.15Kcal/mol for all MsMAPKs and MsPP2Cs, indicating that they interact. Docking site analysis showed that there were 48 pairs of PPIs which indicated that MsPP2Cs can perform a vital role in other signaling pathways. This study found that all MsPP2Cs have docking sites for MsMAPKs, indicating that this method can accurately determine protein-protein interactions.