Structure-based drug design-guided identification of estrogen receptor binders

Area of Science:

• Medicinal Chemistry
• Computational Biology
• Pharmacology

Background:

• Cancer is a leading global cause of death, with estrogen receptors (ERs) as significant therapeutic targets.
• Phytochemicals are a rich source of anticancer drugs, and Datura sp. extracts have shown potential ER inhibition.
• Estrogen receptor-positive cancers represent a substantial proportion of cancer diagnoses.

Purpose of the Study:

• To computationally screen natural products from Datura sp. for estrogen receptor inhibitory activity.
• To identify and design novel compounds with high binding affinity and favorable drug-like properties against estrogen receptors.
• To evaluate the stability and binding energy of potential drug candidates using molecular dynamics simulations.

Main Methods:

• Molecular docking of reported Datura sp. natural products against estrogen receptors.
• Selection of top-scoring compounds based on binding orientation and docking scores.
• Molecular dynamics simulations and binding energy calculations for lead compounds.
• Knowledge-based de novo design and similarity screening for novel ligand development.

Main Results:

• A specific ligand, [(1S,5R)-8-Methyl-8-Azabicyclo [3.2.1] Octan-3-yl] (2R)-3-Hydroxy-2-Phenylpropanoate, demonstrated favorable molecular dynamics simulation outcomes and drug-likeness.
• The designed de novo ligand, DL-50, exhibited satisfactory binding affinity, drug-likeness, and an acceptable ADMET profile.
• DL-50 also showed ease of synthetic accessibility, suggesting its viability for further research.

Conclusions:

• Computational screening and design identified DL-50 as a promising novel inhibitor targeting estrogen receptors.
• The identified compound possesses favorable pharmacological and pharmacokinetic properties, warranting experimental investigation.
• This study highlights the potential of Datura sp. natural products and computational approaches in anticancer drug discovery.