Computational Discovery and Optimization of a Potent, Selective, and Drug-like Scaffold for p38α Inhibition

Mitogen-activated protein kinase 14 (MAPK14), commonly known as p38α, is a stress-activated kinase involved in various physiological and pathological processes, including inflammation, cancer, and neurodegenerative diseases. Despite extensive research and numerous clinical trials, the development of selective p38α inhibitors with consistent clinical efficacy has remained a challenge due to cellular adaptability, compensatory signaling pathways, and dose-dependent toxicities. In this study, we report the identification and optimization of a novel p38α inhibitor scaffold through an integrated virtual screening and structure-based drug discovery approach. Using ESSENCE-Dock, a consensus virtual screening method combining multiple molecular docking algorithms, we identified several promising hit compounds, from which Compound 24 emerged as the most potent candidate (IC50 = 26.2 nM). Subsequent optimization efforts leveraging consensus fingerprint similarity and Butina clustering led to the discovery of structurally related analogs with enhanced potency, including Compounds 28, 47, 48, 50, and 53, all exhibiting IC50 values below 10 nM. MolSHAP-based SAR analysis highlighted key R-group contributions to potency, while synthetic routes enabled efficient scaffold diversification. Molecular dynamics simulations confirmed stable binding interactions with key residues, and KINOMEscan™ profiling showed high selectivity for Compound 26. ADME profiling demonstrated favorable drug-like properties, including high plasma stability (>120 min) and good solubility. A NanoBRET assay further confirmed potent intracellular target engagement of p38α by Compound 26, with 71.4% inhibition at 10 nM, supporting its suitability for further development. Notably, the core scaffold is structurally distinct from previously reported p38α inhibitors, underscoring its novelty. This study underscores the utility of advanced virtual screening and structure-guided optimization in discovering novel and selective p38α inhibitors with potential relevance to inflammatory and neurodegenerative diseases.