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PDB-based protein loop prediction: parameters for selection and methods for optimization

H W van Vlijmen¹, M Karplus

¹Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA.

Journal of Molecular Biology

|April 11, 1997

Summary

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This study presents a database search method for protein loop prediction, improving accuracy by analyzing stem residue correlations and using energy functions for optimization. The approach effectively predicts antibody loops and shows promise for other protein structures.

Area of Science:

Structural Biology
Computational Biology
Bioinformatics

Background:

Protein loop prediction is crucial for understanding protein structure and function.
Existing methods often struggle with accuracy and computational efficiency.

Purpose of the Study:

To develop and analyze a novel database search approach for protein loop prediction.
To assess the correlation between loop conformation and neighboring stem residues.
To optimize loop prediction accuracy using energy minimization techniques.

Main Methods:

Database searching using interatomic distances of stem residues to select template loops.
Ranking candidate loops with CHARMM non-bonded energy function (backbone and C(beta) atoms).
Constrained energy minimization for optimizing loop orientation.

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Main Results:

The method predicted 8 out of 18 loops with RMSD < 1.07 Å.
For 17 out of 18 loops, a top-ranked template loop had RMSD < 1.79 Å.
Antibody loop prediction was more effective, with accurate predictions even for H3 loops without canonical structures.

Conclusions:

Database searching combined with energy-based ranking and optimization is an effective strategy for protein loop prediction.
The method demonstrates high accuracy, particularly for antibody loops.
This approach offers a computationally efficient alternative to direct conformational space searches.