Rationalizing protein-ligand interactions for PTP1B inhibitors using computational methods.

Protein tyrosine phosphatase 1B inhibitors were reported to have anti-diabetic properties and hence this enzyme has become interesting drug target in the recent time. Huge amount of data is available in public domain about the PTP1B inhibitors in the form of X-ray structures. This study is an attempt to transform this data into useful knowledge which can be directly used to design more effective protein tyrosine phosphatase inhibitors. In this study, we have built quantitative models for activity of co-crystallized protein tyrosine phosphatase inhibitors using two new approaches developed in our group, i.e. receptor-ligand interaction and Structure-based compound optimization, prioritization and evolution based on receptor-ligand interaction descriptors and residue-wise interaction energies as descriptors, respectively. These models have given insights into the receptor-ligand interactions essential for modulating the activity of PTP1B inhibitors. An external validation set of 22 molecules was used to test predictive power of these models on external set molecules.