Group-based QSAR modeling of pyrimidine derivatives for antiviral, antimalarial, and anticancer activities
Group-based quantitative structure-activity relationship (GQSAR) modeling was employed on three distinct series of twenty pyrimidine derivatives each for antiviral, antimalarial, and anticancer activities. Models were constructed based on 2D descriptors specific to individual substitution sites within the molecules (R1, R2, R3). For the antiviral series, the best model (r² = 0.923, q² = 0.783, pred_r² = 0.712, F = 59.4) incorporated descriptors R1_SLogP, R2_EState, and R3_Polarizability, indicating a strong role of hydrophobic and electronic properties. The antimalarial model (r² = 0.897, q² = 0.761, pred_r² = 0.685, F = 47.2) revealed significant influence from molecular refractivity and EState indices. The anticancer model (r² = 0.912, q² = 0.775, pred_r² = 0.695, F = 52.8) highlighted the importance of SlogP, ESI, and valence connectivity descriptors. Contribution charts and radar plots provided insights into the relative importance of descriptors, highlighting structural features critical to activity. The findings facilitate a deeper understanding of structure-activity relationships and provide a rational basis for designing improved pyrimidine-based therapeutics.
Authors
- Sushma Somkuwar
- Neelesh Chaubey
Publication Details
- Journal
- World Journal of Biology Pharmacy and Health Sciences
- Published
- 2025-06-18
- DOI
- https://doi.org/10.30574/wjbphs.2025.22.3.0599
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00