Comparing short protein substructures by a method based on backbone torsion angles

Area of Science:

• Structural bioinformatics
• Computational biology
• Protein structure analysis

Background:

• Comparing protein substructures is crucial for understanding protein function and evolution.
• Existing methods may lack sensitivity to subtle conformational changes.

Purpose of the Study:

• To develop and characterize an efficient algorithm for assessing similarity in main chain conformation of short protein substructures.
• To establish reliable similarity thresholds based on torsion angle differences.

Main Methods:

• The algorithm computes delta t, the root mean square difference in phi and psi torsion angles for 3-5 amino acids.
• It correlates delta t with root mean square deviation (delta r) in atomic coordinates.
• Similarity thresholds were determined using measurement noise estimations and distributions from nonhomologous protein comparisons.

Main Results:

• The delta t parameter is sensitive to local protein conformation variations and peptide plane rotations.
• Established similarity thresholds effectively distinguish structurally similar substructures.
• Comparisons of homologous proteins revealed high conservation of active site torsion angles.
• The method successfully identified local structural differences in human hemoglobin's alpha-chain across different ligation states.

Conclusions:

• The delta t algorithm provides an efficient and sensitive method for evaluating protein substructure similarity.
• It offers advantages over methods relying solely on C alpha atoms, capturing peptide plane dynamics.
• The findings highlight the utility of delta t in analyzing protein conformational changes and active site conservation.