Binding of wide variety of drugs and drug like molecules to human serum albumin (HSA) is of great interest to the pharmaceutical industry, as it can significantly affect the free drug concentration at the site of action. Despite the huge volume of available structural and biochemical data, the current computational methods for predicting drug-albumin binding lack high predictive power and fail to explicitly use the structural features of the binding sites on HSA. Presence of multiple binding sites, the delicate architecture and voluminous binding pockets of site I, solvent exposed entrance of site II, effect of fatty acids on drug binding, and water-mediated interactions with the binding site residues and ligands pose formidable challenges. We constructed a rigorous 3D-QSAR model by carefully exploiting available structural information combined with multispecies multimode QM/MM Linear Response method. The challenges and the obtained results will be discussed

Exploring structure-based affinity prediction methods for drugs binding to human serum albumin

243rd National Meeting (2012)

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