Molecular docking-based interaction studies on imidazo[1,2-a] pyridine ethers and squaramides as anti-tubercular...

Area of Science:

• Medicinal Chemistry
• Computational Chemistry
• Drug Discovery

Background:

• Drug resistance necessitates the development of novel anti-tubercular agents targeting validated pathways like ATP synthase.
• Traditional structure-based drug design (SBDD) often shows poor correlation between docking scores and biological activity.

Purpose of the Study:

• To develop a novel quantitative approach for predicting anti-tubercular activity by correlating amino acid residue interactions with biological activity.
• To identify novel inhibitors of ATP synthase for tuberculosis treatment.

Main Methods:

• Quantitative structure-activity relationship (QSAR) modeling based on amino acid residue interactions with the target protein.
• Prediction of ATP synthase inhibitory activity for imidazo[1,2-a] pyridine ethers and squaramides.
• Molecular dynamics simulations to assess ligand-protein complex stability.

Main Results:

• A novel approach successfully predicted ATP synthase inhibitory activity with high correlation coefficients (e.g., r=0.84 for Glu65b interactions).
• Developed models demonstrated strong predictive power across training, diverse, test, and external datasets.
• Three novel compounds with high inhibitory activity (pIC50 in the 0.0508-0.1494 µM range) were identified.

Conclusions:

• The developed quantitative model overcomes limitations of traditional SBDD, enabling accurate prediction of anti-tubercular activity.
• This approach facilitates the identification and optimization of novel anti-tubercular compounds targeting ATP synthase.
• The findings support the potential utility of this model in accelerating the discovery of new drugs against tuberculosis.