Pharmacophore Modeling, 3D QSAR, Molecular Dynamics Studies and Virtual Screening on Pyrazolopyrimidines as anti-Breast Cancer Agents

Abstract

Various targets, such as estrogen receptor (ER), mammalian target ofrapamycin(mTOR), epidermal growth factor receptor (EGFR), androgen receptor (AR) andpoly adenosine diphosphate-ribose polymerase (PARP), are focused on the treatment of breast cancer. In this study, in silico tools such as pharmacophore modeling, 3D QSAR study, molecular docking, binding free energy determination and molecular dynamics were executed on a series of pyrazolopyrimidines derivatives. The pharmacophore modeling of forty-one anticancer derivatives was generated, and atom-based 3D QSAR was applied. Molecular docking, dynamics, binding energy and high-throughput virtual screening (HTVS) were conducted by the software Schrodinger. The best five featured pharmacophore hypotheses AHRRR_1 with a maximum survival score of 5.533 was subjected to rigorous scoring function analysis and 3D QSAR studies. Docking studies and binding free energy were carried out on 41 inhibitors for their anti-breast cancer activity against human estrogen, progesterone receptor, EGFR kinase and mammalian target of rapamycin mTOR. Molecular dynamics simulation of the docked complex-34/4WKQ validated the stability of this complex. HTVS was performed to determine the virtual hits with the best-fitted model AHRRR_1. New EGFR kinase inhibitors were designed based on the active compound templates. Molecular docking was carried out on virtual hits, and newly designed compounds and dynamics studies revealed that the binding modes obtained after MD simulation were more or less similar to that acquired post docking mode. Promiscuity assessments demonstrated that designed compounds would be specific rather than a promiscuous one. Based on these findings, we have designed four novel compounds as anti-breast inhibitors, with potent binding affinity and desirable ADME properties.

Keywords:

• Breast cancer targets
• pharmacophore modeling
• 3D QSAR
• molecular docking and dynamics
• high-throughput virtual screening

Acknowledgements

The authors acknowledge Nitte Deemed to be University, NGSM Institute of Pharmaceutical Sciences (NGSMIPS), Mangaluru, Karnataka, for providing the financial support and NGSMIPS CADD Lab for the facilities to perform this work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

Jainey P. James designed the study and performed molecular docking and other in silico studies. Vinod Devaraji conducted the molecular dynamics simulation studies, and Pradija Sasidharan and Pavan T.S. participated in writing and giving feedback on the manuscript. All authors have read and approved the final manuscript.