Integrated CADD, Molecular Docking and ADMET Prediction in Anti-Inflammatory Lead Discovery: A Review
Inflammation involves coordinated activation of vascular, immune, lipid mediator, cytokine, transcriptional and inflammasome pathways. Modern anti-inflammatory lead discovery increasingly uses computer-aided drug design to identify plausible protein-ligand interactions before costly laboratory studies. This review summarizes the rationale for target selection, molecular docking, ADMET prediction, toxicity screening and Quality by Design-based documentation in anti-inflammatory computational pharmacology. The article emphasizes that docking scores are hypothesis-generating outputs and must be interpreted with binding-pose quality, residue relevance, pharmacokinetic feasibility and safety prediction. Selected natural scaffolds such as curcumin, quercetin, luteolin, apigenin, resveratrol, berberine, boswellic acid, andrographolide, withaferin A, gallic acid and ellagic acid are discussed as examples of chemically diverse candidates for pathway-based screening