Quantifying steric hindrance and topological obstruction to protein structure superposition

Area of Science:

• Computational structural biology
• Bioinformatics
• Protein structure analysis

Background:

• Protein structure comparison is crucial for understanding protein evolution and predicting structures.
• Current methods often optimize residue-pair distances during alignment, ignoring steric clashes and topological changes.
• Linear interpolation between aligned protein backbones can lead to unphysical configurations or altered topologies.

Purpose of the Study:

• To analyze linear interpolations between aligned protein backbones for steric clashes and self-intersections.
• To develop a method for detecting significant topological alterations in protein structures during alignment.
• To assess the impact of topological obstructions on protein structure comparisons.

Main Methods:

• Quantification of steric clashes and identification of self-intersections in linear backbone interpolations.
• Development of a path-finding algorithm using a novel interpretation of Reidemeister moves from knot theory.
• The algorithm determines the existence of a self-avoiding path or identifies essential self-intersections.

Main Results:

• The method successfully distinguishes between topologically similar and dissimilar protein structures.
• Essential self-intersections were found separating knotted from unknotted structures and indicating significant fold differences.
• Analysis of 142,068 TM-alignments revealed 42,165 topological obstructions, even with restrictive alignment parameters.

Conclusions:

• The developed program, ProteinAlignmentObstruction, provides crucial topological information beyond traditional distance-based alignment scores.
• Detecting topological obstructions offers a more comprehensive understanding of protein structural relationships and evolutionary pathways.
• This approach enhances the accuracy and reliability of computational protein structure analysis.