Identification of novel potential benzimidazole derivatives by pharmacophore generation, 3D-QSAR, virtual screening, molecular docking and ADME/ TOX analysis against breast cancer as targeted estrogen alpha receptor

Aastha Sharma; Nitish Banga; Rakesh Kumar Marwaha; Balasubramanian Narasimhan

doi:10.69857/joapr.v13i2.951

Authors

Aastha Sharma Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak, Haryana, 124001, India
Nitish Banga Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak, Haryana, 124001, India
Rakesh Kumar Marwaha Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak, Haryana, 124001, India
Balasubramanian Narasimhan Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak, Haryana, 124001, India

DOI:

https://doi.org/10.69857/joapr.v13i2.951

Keywords:

Benzimidazole, Cancer, Docking, Pharmacophore, Virtual screening, 3D-QSAR, ADME/Tox

Abstract

Background: The estrogen alpha receptor (ERα) is critical in breast carcinogenesis. Although selective estrogen receptor modulators like tamoxifen are clinically used, their adverse effects highlight the need for safer alternatives. The study uses computational methods to identify potential ERα inhibitors within a benzimidazole scaffold. Methodology: This study employed computational approaches, including pharmacophore generation, 3D-QSAR, virtual screening, molecular docking, and in silico ADME/Tox analysis. The best pharmacophore model (DDRRR_1) identified two hydrogen donors and three aromatic rings as critical features. Moreover, a rigorous external validation was used on decoy databases with optimized metrics (ROC, BEDROC, AUROC). A subsequent atom-based 3D-QSAR model with a high correlation coefficient (R² = 0.9), cross-validated coefficient (Q² = 0.8), and Fisher ratio (F = 80.1) was developed. Benzimidazole scaffolds from PubChem were screened, followed by docking against ERα (PDB ID: 3ERT) and ADMET profiling. Results and Discussion: The pharmacophore model validated the importance of the identified features. The 3D-QSAR model effectively screened benzimidazole scaffolds, with five component PLS factors, supporting the pharmacophore findings. This model effectively screened benzimidazole scaffolds obtained from the PubChem database, followed by molecular docking against the targeted protein ERα (PDB ID: 3ERT) and identified five promising compounds. ADME/Tox profiling revealed PubChem ID 3074802 (2-[2-(1H-indol-3-yl) ethyl]1H-benzimidazole) has favourable pharmacokinetics and a low toxicity profile. Conclusion: These findings indicate that PubChem ID 3074802 is a promising candidate for further therapeutic drug development in breast cancer treatment. It demonstrates the highest binding affinity (-9.842 kcal/mol) compared to the standard drug Tamoxifen (-5.357 kcal/mol) and exhibits a favorable ADME/Tox profile.

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