Docking analysis targeted to the whole enzyme: an application to the prediction of inhibition of PTP1B by thiomorpholine and thiazolyl derivatives^$

^$Presented at the 9th International Symposium on Computational Methods in Toxicology and Pharmacology Integrating Internet Resources, CMTPI-2017, 27–30 October 2017, Goa, India.

Abstract

PTP1b is a protein tyrosine phosphatase involved in the inactivation of insulin receptor. Since inhibition of PTP1b may prolong the action of the receptor, PTP1b has become a drug target for the treatment of type II diabetes. In the present study, prediction of inhibition using docking analysis targeted specifically to the active or allosteric site was performed on 87 compounds structurally belonging to 10 different groups. Two groups, consisting of 15 thiomorpholine and 10 thiazolyl derivatives exhibiting the best prediction results, were selected for in vitro evaluation. All thiomorpholines showed inhibitory action (with IC₅₀ = 4–45 μΜ, Ki = 2–23 μM), while only three thiazolyl derivatives showed low inhibition (best IC₅₀ = 18 μΜ, Ki = 9 μΜ). However, free binding energy (E) was in accordance with the IC₅₀ values only for some compounds. Docking analysis targeted to the whole enzyme revealed that the compounds exhibiting IC₅₀ values higher than expected could bind to other peripheral sites with lower free energy, E_o, than when bound to the active/allosteric site. A prediction factor, E− (Σ_Eo × 0.16), which takes into account lower energy binding to peripheral sites, was proposed and was found to correlate well with the IC₅₀ values following an asymmetrical sigmoidal equation with r² = 0.9692.

Keywords:

• PTP1b inhibitors
• docking analysis
• docking box
• active site
• allosteric site
• competitive inhibitors
• uncompetitive inhibitors
• thiomorpholines
• thiazoles
• diabetes, selectivity, TC-PTP

Acknowledgements

P. Theodosis-Nobelos acknowledges the General Secretariat for Research and Technology (GSRT) of Greece and the Hellenic Foundation for Research and Innovation (HFRI) for a grant supporting his PhD research [grant number 1219].

Notes

^$ Presented at the 9th International Symposium on Computational Methods in Toxicology and Pharmacology Integrating Internet Resources, CMTPI-2017, 27–30 October 2017, Goa, India.