Natural bioactive compounds as a new source of promising G protein-coupled estrogen receptor (GPER) modulators: comprehensive in silico approach

Abstract

Cancer ranks in second place among the cause of death worldwide. Cancer progress in multiple stages of carcinogenesis and metastasis programs through complex pathways. Sex hormones and their receptors are the major factors in promoting cancer progression. Among them, G protein-coupled estrogen receptor-1 (GPER) has shown to mediate cellular signaling pathways and cancer cell proliferation. However, the lack of GPER protein structure limited the search for new modulators. In this study, we curated an extensive database of natural products to discover new potential GPER modulators. We used a combination of virtual screening techniques to generate a homology model of GPER and subsequently used that for the screening of 30,926 natural products from a public database to identify potential active modulators of GPER. The best hits were further screened through the ADMET filter and confirmed by docking analysis. Moreover, molecular dynamics simulations of best hits were also carried out to assess the stability of the ligand-GPER complex. This study predicted several potential GPER modulators with novel scaffolds that could be further investigated and used as the core for the development of novel GPER modulators.

Communicated by Ramaswamy H. Sarma

Keywords:

• Cancer
• breast cancer
• natural products
• G protein-coupled estrogen receptor-1
• GPR30
• GPER1
• GPER
• in silico screening
• SBVS
• virtual screening

Acknowledgements

We are grateful to the Ministry of Higher Education, Malaysia (FRGS, grant no. FRGS/1/2015/ST01/MUSM/03/1) for financial support). Shafi would like to acknowledge the HPC-Europa3 Transnational Access Grant HPC17LSBTX and Dr. Zoe Cournia of the Biomedical Research Foundation of the Academy of Athens (BRFAA) for providing guidance and support in MD simulation training. We also thank OpenEye Scientific for providing a free academic license to perform in silico studies.

Disclosure statement

The authors declare that they have no competing financial interests.