2D QSAR of Novel hybrid motifs of 4-nitroimidazole-piperazinyl tagged 1,2,3-triazoles for Anti-cancer Activity against Breast Cancer cell line MCF-7
Objective: To develop and validate a two‑dimensional quantitative structure–activity relationship (2D‑QSAR) model for novel 4‑nitroimidazole‑piperazinyl tagged 1,2,3‑triazole derivatives and to identify key physicochemical descriptors governing their anticancer activity against the human breast cancer cell line MCF‑7. Results and Discussion: Several statistically acceptable QSAR models were obtained; among them, Model 1, incorporating Molar Refractivity, partition coefficient, Henry’s law constant, mass, and molecular weight, showed the most favorable balance of correlation and error (r ≈ 0.45, r² ≈ 0.20, standard deviation ≈ 0.50) with a single outlier. Descriptor analysis indicated that Molar Refractivity is positively correlated with MCF‑7 inhibitory activity, suggesting that bulkier or more polarizable substituents enhance cytotoxic potency, while the partition coefficient term supports a beneficial role of less polar, more lipophilic groups. The results demonstrate that the thermodynamic and electronic nature of substituents strongly influences activity and that even a moderate‑fit 2D‑QSAR model can serve as a useful predictive tool for prioritizing new analogues. Conclusion: The 2D‑QSAR study established that MCF‑7 cell inhibitory activity of 4‑nitroimidazole‑piperazinyl tagged 1,2,3‑triazole derivatives is primarily governed by Molar Refractivity, lipophilicity‑related parameters, and other thermodynamic–electronic descriptors of the substituents. The optimized Model 1 provides a rational basis for designing new hybrids with higher molecular refractivity and appropriately tuned hydrophobic and electronic profiles to achieve improved anticancer potency, and the proposed QSAR framework can be applied to further scaffold optimization against breast cancer targets. Keywords: Quantitative Structure Activity Relationship (QSAR), Anti-Cancer,imidazole, ChemDraw, MCF-7 Cell.
Authors
- Nitin Singh Rajput (ORCID: https://orcid.org/0000-0003-2730-6467)
- Megha Mishra
- Pradeep Kumar Singour
- Shabnam Yadav
- Pranay Raikwar
- Arun Kumar Rai
- Shivraj Pandey
Institutions
- Bharat Heavy Electricals (India) (IN)
- AISECT University (IN)
Publication Details
- Journal
- Journal of Drug Delivery and Therapeutics
- Published
- 2026-04-15
- DOI
- https://doi.org/10.22270/jddt.v16i4.7662
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00