Identification of key structural features of phosphate and thiophosphate tricyclic coumarin analogs as STS inhibitors

Abstract

Steroidal sulfatase (STS) is a group of arylsulfatase C enzymes that are involved in the metabolism of steroids. The increase in the circulation of the steroidogenic hormone Estradiol (E2) is responsible for causing breast cancer. Therefore, inhibitors of STS are proved to be an attractive target in the development of lead molecules against breast malignancy. In this work, Quantitative Structural Activity Relationship (QSAR) studies were performed on a dataset of 72 molecules of tricyclic coumarin analogs using random selection in QSARINS software and the statistical technique Genetic Algorithm coupled Multiple Linear Regression (MLR) was employed with the best model prediction R2 = 0.86 and Q2loo = 0.7913. The inclusion of descriptors Mor15m and Mor18v has developed a well-fitted and highly predictable model. Furthermore, the molecular docking and dynamics simulations helped us identify the binding interactions and estimate the stability of the complexes respectively. The binding analysis of the compounds into human sulfatase protein (PDB code: 1P49) resulted in prominent hydrophobic interactions with Arg98, Val486, Phe488, Gly100, Val101, and Lys368. The top-scoring compound 9o and compound 41 were studied for stability analysis in comparison with the standard Irosustat and the RMSD was found to be 5.4 Å. Based on our findings, we report the inclusion of the necessary structural features of coumarin derivatives leads to the development of potent candidates for further development.

Keywords

• Tricyclic coumarin analogs
• QSARINS
• Molecular docking
• Molecular dynamics