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Research Articles

Estrogen receptor potentially stable conformations from molecular dynamics as a structure-based pharmacophore model for mapping, screening, and identifying ligands—a new paradigm shift in pharmacophore screening

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Pages 4939-4948 | Received 18 Feb 2022, Accepted 02 May 2022, Published online: 11 May 2022
 

Abstract

Despite rigorous research on breast cancer has increased in recent decades, only few drugs are in practice to combat against the disease. Due to excessive usage, these drugs attain resistance is an avertable phenomenon resulting from inadequate treatment. A novel, and real-time approaches are expected to overcome to find the solution for the drug resistance. The molecular dynamics based multi-conformational sampling technique via computer-aided drug-designing approach, may be a promising route to identify the lead candidates from real-time generated frames. The estrogenic receptor, being one of the most widely targeted receptors for various breast cancer drugs namely, tamoxifen, raloxifene and GW5 (tamoxifen-resistance inhibitor) was used for simulating the molecular dynamics to obtain various real time frames. The energetically stable frames were funnelled based on Gibbs free binding energy, interaction energy and active site interaction to generate pharmacophores model for virtual screening of compounds. Generated pharmacophores are validated by receiver operating characteristic area under curve greater than 0.8. Further, screening of compounds with validated structure-based pharmacophore model of different estrogen bound drug complex conformations and binding orientations are complement for tamoxifen and tamoxifen-resistance inhibitor frames. Moreover, the best mapped compounds were docked and probed for ADMET, TopKat® and Lipinski’s rule of five is more favourable for compound Andrographidine F sourced from medicinal herbal plant Andrographis paniculata. Hence, this compound had to be further analysed in in-vitro and in-vivo to prove the same.

Communicated by Ramaswamy H. Sarma

Acknowledgements

Authors would like to thank the management of Altem Technologies Pvt. Ltd., Bengaluru, India, for their support in carrying out this research work.

Disclosure statement

The authors would like to report that there is no potential conflict of interest related to the work reported in this paper.

Funding

The author(s) reported there is no funding associated with the work featured in this article.

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