Anticancer activity of nucleoside analogues: a density functional theory based QSAR study.

Area of Science:

• Computational Chemistry
• Medicinal Chemistry
• Drug Discovery

Background:

• Nucleoside analogues are crucial in cancer chemotherapy.
• Developing novel analogues with enhanced efficacy requires predictive models.
• Understanding structure-activity relationships is key to designing effective anticancer agents.

Purpose of the Study:

• To develop Quantitative Structure-Activity Relationship (QSAR) models for carbocyclic nucleoside analogues.
• To identify key molecular descriptors correlating with anticancer activity against leukemia and T-lymphocyte cell lines.
• To design novel nucleoside analogues with predicted high anticancer potential.

Main Methods:

• Multiple linear regression analyses were employed.
• Density Functional Theory (DFT) and Molecular Mechanics (MM+) based descriptors were utilized.
• QSAR models were built using both gas and solvent phase calculations.

Main Results:

• QSAR models explained over 90% of activity variance for tested cell lines.
• Energy of the next lowest unoccupied molecular orbital (E(NL)), electrophilicity (omega), and van der Waals surface area (SA) were identified as key descriptors.
• Solvent inclusion enhanced descriptor-activity correlations.
• Ten new compounds with predicted high anticancer activity were designed.
• Predicted activities for 20 additional analogues showed good agreement with experimental data.

Conclusions:

• Established QSAR models accurately predict anticancer activity of nucleoside analogues.
• Molecular descriptors related to electronic properties and size are critical for anticancer efficacy.
• Theoretical design based on QSAR insights can accelerate the discovery of potent anticancer nucleoside analogues.