Computer-aided drug design applied to a series of pyridinyl imidazole derivatives targeting p38α MAP kinase: 2D-QSAR, docking, MD simulation, and ADMET investigations

Abstract

The p38 mitogen-activated protein kinase (MAPK) is a crucial target for chronic inflammation. Here, 2D-QSAR and molecular docking studies were performed on a new series of pyridinyl imidazole derivatives as p38α MAPK inhibitors. The goal is to find a correlation between the chemical structures and inhibitory activity of the p38α MAPK. The partial least squares (PLS) regression method was used to build the 2D-QSAR model. The results revealed that the generated model yielded 0.85 for the determination coefficient (r²), 0.83 for the adjusted determination coefficient (r_a²), and 0.16 for the root-mean-square error (RMSE). Internal and external validations were used to figure out how well the model could predict the future. The r_cv² and r_test² values were 0.78 and 0.92, indicating that the developed model is robust and capable of predicting the activity of new compounds. The affinity of the ligands (pyridinyl imidazole derivatives) and the binding pocket of the p38α MAP kinase receptor was also determined by molecular docking using autoDock tools. The results revealed the importance of conventional hydrogen bonds in the binding pocket of the p38α MAPK receptor. Based on these results, a novel series of compounds were predicted and evaluated using molecular dynamics (MD) and ADMET prediction investigations. The study's findings might pave the way for the development of new pyridinyl imidazole derivatives that are able to inhibit the enzymatic activity of the p38α MAP kinase.