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Estrogen receptor is a key feature of many complex disorders. Natural estrogen ligand, estradiol has been investigated in the pharmaceutical aspect of breast cancer, Parkinson’s, Alzheimer’s, risk of stroke in postmenopausal women, and dementia. From the similar manner, synthetic selective estrogen receptor modulators (SERMs) have been investigated, and their pharmaceutical effects have been evaluated in compared to the natural ligand, estradiol, in literature. To design better alternatives to the approved SERMs and to improve the clinical observations, it is crucial to understand the molecular basis of drug-target interactions of estrogen receptor with the natural and synthetic ligands in a comparative manner. We used molecular modeling softwares PyRX, Avogadro, and Arguslab for in silico calculations. The results were analyzed using PyMol. We, in this study, provided a computational binding analysis of the estrogen receptor with the endogenous ligand estradiol and the FDA approved SERMs raloxifene, tamoxifen, and toremifene. We investigated the toxicity profile of the SERMs and estradiol and interpreted the results according to the reported clinical observations. We found that designing new molecules based on the estradiol structure instead of the approved tamoxifen analogs could result in better clinical observations for future estrogen targeting therapeutics.

medicine science

Computational binding analysis and toxicity evaluation of estrogen receptor with estradiol and the approved SERMs raloxifene, tamoxifen, and toremifene