An algorithm for determining the conformation of polypeptide segments in proteins by systematic search

Area of Science:

• Structural biology
• Computational chemistry
• Protein science

Background:

• Determining protein structure is crucial for understanding function.
• Predicting local polypeptide chain conformation is a key challenge in structural biology.
• Existing methods may struggle with accuracy in approximate protein models.

Purpose of the Study:

• To investigate the feasibility of predicting local polypeptide chain conformations (up to six residues).
• To develop a systematic computational approach for conformational analysis in globular proteins.
• To validate the method against experimental data.

Main Methods:

• Generating trial conformations using representative phi, psi, and chi angles from refined protein structures.
• Applying filters for chain integrity and van der Waals contacts to manage conformational space.
• Constructing main and side chains, then evaluating electrostatic energy and exposed hydrophobic area.
• Testing the method on segments of a trypsin-like enzyme from Streptomyces griseus.

Main Results:

• The method successfully reduces the number of possible conformations using defined filters.
• A wide range of energies was observed among accepted conformations.
• The lowest energy conformations showed small root mean square deviations from the X-ray structure.

Conclusions:

• The developed systematic search method is feasible for determining local polypeptide chain conformations.
• The approach effectively identifies low-energy conformations consistent with experimental data.
• This method can be applied to approximate protein models, accounting for potential errors.