Abstract
The serine/threonine kinase AKT1 (RAC-α protein kinase) functions as a central node of the PI3K/AKT/mTOR signaling pathway, regulating key biological processes such as glucose uptake, lipid metabolism, cell growth, and survival. Persistent activation of this pathway has been strongly implicated in the pathogenesis of metabolic disorders, particularly obesity and metabolic dysfunction-associated steatotic liver disease (MASLD), where it contributes to insulin resistance, hepatic steatosis, and progression toward steatohepatitis. Despite its recognized importance, the development of selective AKT1 inhibitors for metabolic disease applications remains limited. In this study, we implemented an integrated computational pipeline that combines quantitative structure-activity relationship (QSAR) modeling, structure-based virtual screening, molecular docking, Gaussian accelerated molecular dynamics (GaMD) simulations, and MM-GBSA binding free energy analysis to identify novel AKT1 inhibitors. A total of 9361 raw bioactivity records were retrieved from the ChEMBL database and systematically curated to yield a high-quality data set of 2711 compounds with validated IC50 values. QSAR models constructed from this data set demonstrated robust predictive power and were employed to prioritize potential active scaffolds. Subsequent virtual screening and docking identified several promising candidates, with NPC134413, NPC277306, and NPC469442 exhibiting superior binding affinities (-9.42, -9.36, and -9.07 kcal/mol, respectively) compared to the cocrystallized reference ligand (-7.09 kcal/mol). Molecular dynamics simulations confirmed the stability of these complexes, revealing persistent hydrogen bonds and ionic contacts with critical catalytic residues, including Met281, Glu234, Asp292, and Lys277. Structural stability was further supported by RMSD, RMSF, RoG, and PCA analyses, which demonstrated restricted conformational fluctuations in the ligand-bound states. MM-GBSA free energy calculations reinforced these findings, with NPC469442 (-48.54 kcal/mol) displaying the most favorable binding energetics, surpassing the reference complex. Overall, this integrative framework highlights structurally diverse and energetically favorable AKT1 inhibitors with strong therapeutic promise for obesity and MASLD. The results provide a rational basis for advancing these hits toward experimental validation and underscore the utility of combining QSAR-guided screening with GaMD simulations for drug discovery in metabolic diseases.