pharmACOphore: multiple flexible ligand alignment based on ant colony optimization.

Area of Science:

• Computational Chemistry
• Drug Discovery
• Bioinformatics

Background:

• Flexible ligand superposition is vital for ligand-based drug design.
• Existing methods may lack efficiency or robustness in aligning multiple ligands.

Purpose of the Study:

• To introduce pharmACOphore, a novel computational approach for flexible ligand alignment.
• To evaluate pharmACOphore's performance in both pairwise and multiple ligand alignment tasks.

Main Methods:

• Utilized ant colony optimization (ACO) for flexible ligand superposition.
• Developed an empirical scoring function minimizing distances between pharmacophoric features.
• Parametrized the scoring function using ligand sets for cyclooxygenase-2, cyclin-dependent kinase 2, factor Xa, and peroxisome proliferator-activated receptor γ.
• Validated performance using the FlexS dataset and conducted multiple alignment experiments on trypsin and PARP.

Main Results:

• PharmACOphore demonstrated robust performance in pairwise ligand alignment and pose prediction.
• The method proved effective for multiple flexible alignment of pharmacologically relevant targets.
• Achieved efficient and accurate superposition of biologically active ligands.

Conclusions:

• PharmACOphore provides a robust and efficient computational solution for flexible ligand alignment.
• The approach is applicable to both pairwise and multiple ligand superposition tasks.
• Facilitates advancements in ligand-based drug design through improved molecular alignment.