Pharmacophore Optimization Using 3D QSAR, Virtual Screening, Docking, and ADMET Studies for the Design of Novel Pyrimidinyl‐imidazothiazole Derivatives as p38α Inhibitor

ABSTRACT The p38α mitogen‐activated protein kinase (MAPK) plays a critical role in chronic inflammatory disorders, making it an attractive therapeutic target. In this study, an integrated computational strategy was employed to design novel pyrimidinyl‐imidazothiazole derivatives as potential p38α inhibitors. The workflow included atom‐based 3D‐QSAR modeling, ligand‐based pharmacophore generation, new chemical entity enumeration, virtual screening, molecular docking, and ADMET profiling. The developed QSAR model demonstrated strong statistical reliability ( R 2 = 0.8892, Q 2 = 0.8480). The QSAR model was validated by internal and external validation. A pharmacophore hypothesis (DHRRR_1) consisting of one hydrogen‐bond donor, one hydrogen‐bond acceptor, and three aromatic ring features identified key structural requirements for activity. Enumeration generated 1170 new compounds, which were combined with the ChEMBL dataset (45,738 compounds) and screened using the pharmacophore model, yielding 1165 hits. These were subjected to XP docking, induced‐fit docking, MM‐GBSA analysis, and ADMET evaluation, leading to the selection of ten promising candidates. To address biological redundancy and compensatory signaling within the MAPK pathway, cross‐docking studies were performed against related kinases. Among the screened compounds, compound 32 exhibited the most favorable selective binding affinity toward p38α, less toxicity, improved metabolism, and emerged as the most promising lead for further anti‐inflammatory drug development.