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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-30
DOI
https://doi.org/10.5281/zenodo.17440726
Primary Topic
Advanced Electron Microscopy Techniques and Applications
Type
article
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article

Group-based QSAR modeling of pyrimidine derivatives for antiviral, antimalarial, and anticancer activities

Zenodo (CERN European Organization for Nuclear Research)
Advanced Electron Microscopy Techniques and Applications
article

Group-based QSAR modeling of pyrimidine derivatives for antiviral, antimalarial, and anticancer activities

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Sri Sathya Sai Institute of Higher Medical Sciences (IN)
Openalex Percentile: Top 32%
Advanced Electron Microscopy Techniques and Applications
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Group-based QSAR modeling of pyrimidine derivatives for antiviral, antimalarial, and anticancer activities · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS