Quantitative structure-activity relationship (QSAR) models relate the chemical structure of compounds to their biological activity, including IC50 values. By analyzing a dataset of known inhibitors with experimental IC50 values, QSAR models can be used to predict the IC50 values of new compounds. Molecular descriptors such as molecular weight, lipophilicity, hydrogen bonding capacity, and electronic properties are used to characterize the compounds and correlate them with their IC50 values. In structure-based drug design molecular docking simulations predict the binding mode and affinity of small molecules to the target protein's active site. Compounds with favorable docking scores are more likely to have lower IC50 values. Molecular dynamics simulations can further refine the binding poses and assess the stability of the protein-ligand complex, providing insights into the dynamic behavior that may influence IC50 values. In ligand-based drug design pharmacophore modeling identifies the essential structural features required for binding to the target protein. Compounds that match the pharmacophore features are likely to exhibit activity, including potency measured by IC50 values. Similarity searching compares the chemical features of potential drug candidates to known active compounds with known IC50 values, enabling the prediction of potency based on structural similarity.