An integrated in silico analysis of drug-binding to human serum albumin.

Approaches such as quantitative structure-activity relationships (QSAR) and molecular modeling are integrated with the study of complex networks to understand drug binding to human serum albumin (HSA). A robust QSAR model using the topological substructural molecular descriptors/design (TOPS-MODE) approach has been derived and shows good predictability and interpretability in terms of structural contribution to drug binding to HSA. A perfect agreement exists between the group/fragment contributions found by TOPS-MODE and the specific interactions of drugs with HSA. These results indicate a preponderant contribution of hydrophobic regions of drugs to the specific binding to drug-binding sites 1 and 2 in HSA and specific roles of polar groups which anchor drugs to HSA binding sites. The occurrence of fragments contributing to drug binding to HSA can be represented by complex networks. The fragment-to-fragment complex network displays "small-world" and "scale-free" characteristics and in this way is similar to other complex networks including biological, social, and technological networks. A small number of fragments appear very frequently in most drugs. These molecular "empathic" fragments are good candidates for guiding future drug discovery research.