Molecular modeling of triazine type MDR modulators using CoMFA and CoMSIA approaches

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Pharmacology

Background:

• Multidrug resistance (MDR) is a major challenge in cancer chemotherapy.
• Triazine derivatives are being investigated as potential MDR modulators.

Purpose of the Study:

• To investigate the MDR reversing activity of 30 triazine derivatives using 3D Quantitative Structure-Activity Relationship (3D QSAR) methods.
• To compare the efficacy of Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) for predicting this activity.

Main Methods:

• 3D QSAR analysis was performed on a series of 30 triazine derivatives.
• Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were employed.
• Steric, electrostatic, and hydrophobic fields were utilized to build predictive models.

Main Results:

• Both CoMFA and CoMSIA models demonstrated good predictive power for MDR reversing activity.
• Electrostatic and hydrophobic fields were identified as dominant factors influencing the activity.
• CoMSIA models showed slightly superior performance and required fewer principal components compared to CoMFA.
• Contour plots provided insights into structural regions affecting anti-MDR activity.

Conclusions:

• The study successfully developed predictive 3D QSAR models for triazine derivatives' MDR reversing activity.
• Electrostatic and hydrophobic interactions are crucial for the efficacy of these compounds.
• CoMSIA offers a slightly more efficient approach for modeling this class of MDR modulators.