A novel method of aligning molecules by local surface shape similarity

Area of Science:

• Computational chemistry
• Structural biology
• Drug discovery

Background:

• Accurate molecular overlay is crucial for understanding structure-activity relationships.
• Existing methods often struggle with detecting local similarities or handling complex binding modes.

Purpose of the Study:

• To develop a novel shape-based method for overlaying molecule surfaces.
• To enable the detection of local, rather than global, molecular similarity.
• To assess the method's utility in predicting experimental binding configurations.

Main Methods:

• Representing molecular surfaces as sets of circular patches with constant curvature.
• Employing a clique-detection algorithm to identify corresponding surface patches between molecules.
• Overlaying molecules based on coincident similar patches.
• Performing consensus overlays for multiple molecules by selecting highest-scoring pairwise alignments.

Main Results:

• The novel method successfully overlaid molecule surfaces into a common reference frame.
• The approach demonstrated the ability to detect local similarities effectively.
• Evaluations using X-ray crystal structures showed generally encouraging overlay results.
• The method correctly predicted the 'reverse orientation' binding of ligands to human rhinovirus coat protein HRV14.

Conclusions:

• The developed shape-based overlay method is a valuable tool for molecular comparison.
• It accurately identifies local structural similarities and predicts binding orientations.
• This technique holds potential for applications in drug discovery and structural biology.