Dual aromatase-steroid sulfatase inhibitors (DASI's) for the treatment of breast cancer: a structure guided ligand based designing approach

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2022-12-13T00:00:00

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Taylor and Francis Ltd.

Abstract

Dual aromatase-steroid sulfatase inhibitors (DASIs) lead to significant deprivation of estrogen levels as compared to a single target inhibition and thereby exhibited an additive or synergistic effect in the treatment of hormone-dependent breast cancer (HDBC). Triazole-bearing DASI�s having structural features of clinically available aromatase inhibitors are identified as lead structures for optimization as DASI�s. To identify the spatial fingerprints of target-specific triazole as DASI�s, we have performed molecular docking assisted Gaussian field-based comparative 3D-QSAR studies on a dataset with dual aromatase-STS inhibitory activities. Separate contours were generated for both aromatase and steroid sulphates showing respective pharmacophoric structural requirements for optimal activity. These developed 3D-QSAR models also showed good statistical measures with the excellent predictive ability with PLS-generated validation constraints. Comparative steric, electrostatic, hydrophobic, HBA, and HBD features were elucidated using respective contour maps for selective target-specific favourable activity. Furthermore, the molecular docking was used for elucidating the mode of binding as DASI�s along with the MD simulation of 100 ns revealed that all the protease-ligand docked complexes are overall stable as compared to reference ligand (inhibitor ASD or Irosustat) complex. Further, the MM-GBSA study revealed that compound 24 binds to aromatase as well as STS active site with relatively lower binding energy than reference complex, respectively. A comparative study of these developed multitargeted QSAR models along with molecular docking and dynamics study can be employed for the optimization of drug candidates as DASI�s. Communicated by Ramaswamy H. Sarma. � 2022 Informa UK Limited, trading as Taylor & Francis Group.

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Breast cancer, dual aromatase-sulphatase inhibitors (DASI's), Gaussian field-based 3D-QSAR, ligand-based drug design, triazole

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