QSAR analysis of thiolactone derivatives using HQSAR, CoMFA and CoMSIA

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Parasitology

Background:

• Drug resistance and high mortality rates in malaria necessitate novel therapeutic agents.
• Thiolactone emerged as a promising lead structure for antimalarial drug development.
• Understanding structure-activity relationships is key to designing effective antimalarial compounds.

Purpose of the Study:

• To explore the antimalarial potential of thiolactone derivatives.
• To develop predictive quantitative structure-activity relationship (QSAR) models for antimalarial activity.
• To investigate the binding interactions of designed thiolactones with Plasmodium falciparum Kas I/II.

Main Methods:

• Hologram quantitative structure-activity relationship (HQSAR)
• Comparative molecular field analysis (CoMFA)
• Comparative molecular similarity indices analysis (CoMSIA)
• Molecular docking studies

Main Results:

• QSAR models (HQSAR, CoMFA, CoMSIA) demonstrated good predictive power with cross-validated q(2) values of 0.791, 0.737, and 0.753, respectively.
• HQSAR identified hydrogen bond donors and acceptors as critical for antimalarial activity.
• Molecular docking revealed favorable binding modes of designed thiolactones within the pf KAS I/II active site.

Conclusions:

• QSAR models and molecular docking provide a robust framework for designing novel antimalarial agents based on the thiolactone scaffold.
• The study successfully identified key structural features contributing to antimalarial activity.
• These computational approaches can accelerate the discovery of new drugs to combat malaria.