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Updated: Jul 14, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

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Multiple methods for protein side chain packing using maximum weight cliques.

J B Brown¹, K C Dukka Bahadur, Etsuji Tomita

¹Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, 611-0011 Kyoto, Japan. jbbrown@kuicr.kyoto-u.ac.jp

Genome Informatics. International Conference on Genome Informatics

|May 16, 2007

Summary

This study introduces new computational methods for protein side chain packing. By dividing proteins and using clique algorithms, these techniques efficiently find optimal protein structures up to 8000 residues.

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Area of Science:

Computational biology
Structural bioinformatics
Protein structure prediction

Background:

The protein side chain packing problem is crucial for determining protein structure and function.
Existing methods may face challenges with large protein molecules.

Purpose of the Study:

To present novel computational methods for solving the protein side chain packing problem.
To evaluate the efficiency and accuracy of these new approaches.

Main Methods:

Decomposition of the protein polymer into smaller subpolymers.
Application of maximum edge weight cliques for search space pruning.
Characterization of graph sizes and comparison of prediction accuracies.

Main Results:

Demonstrated effectiveness for proteins up to approximately 8000 residues.
Comparative analysis of different methods' prediction accuracies.
Updated a previously published result.

Conclusions:

The presented methods offer efficient solutions for protein side chain packing.
The approach scales well for large protein systems.
These advancements contribute to more accurate protein structure prediction.