A statistical analysis of side-chain conformations in proteins: comparison with ECEPP predictions

Area of Science:

• Biophysics
• Computational Biology
• Structural Biology

Background:

• Protein structure is determined by amino acid side-chain conformations.
• Computational models like ECEPP/2 are used to predict these conformations.
• Previous studies showed discrepancies between observed and calculated side-chain distributions.

Purpose of the Study:

• To compare observed side-chain conformations in globular proteins with those predicted by computational models.
• To investigate the reasons for discrepancies, particularly for branched amino acid side chains.
• To refine computational models for better prediction of protein structures.

Main Methods:

• Statistical analysis of side-chain conformations from 63 globular proteins (10,832 residues).
• Comparison with distributions calculated using the ECEPP/2 force field for model peptides.
• Recalculation using an improved ECEPP/3 force field with elongated peptide backbones.

Main Results:

• Good agreement was found for residues with linear or unbranched side chains.
• Poor agreement was observed for amino acids with side chains branched at C beta or C gamma.
• Improved ECEPP/3 calculations with longer backbones showed closer agreement with observed distributions.

Conclusions:

• The tendency of branched side chains to interact with the protein backbone or adjacent side chains explains discrepancies.
• Refined computational models, considering longer-range interactions, are crucial for accurate protein structure prediction.
• This study has implications for understanding the balance of short-range versus long-range interactions in protein folding.