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Updated: Aug 11, 2026
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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
The fragment transformation method to detect the protein structural motifs
Chih-Hao Lu1, Yeong-Shin Lin, Yu-Ching Chen
1Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan, Republic of China.
Proteins
|February 14, 2006
Summary
This study introduces an automated algorithm for identifying protein structural motifs, crucial for understanding protein function. The method effectively detects motifs like the beta beta alpha-metal binding motif, aiding in functional annotation.
Area of Science:
- Structural biology
- Bioinformatics
- Computational biology
Background:
- Identifying functional structural motifs in proteins of unknown function is vital for structural genomics.
- Conserved motifs like the Asp-His-Ser catalytic triad are easily detected, but variable motifs, such as the beta beta alpha-metal binding motif, pose a challenge.
- Current motif identification relies on manual, time-consuming procedures using various analysis tools.
Purpose of the Study:
- To develop an automated structural alignment algorithm for identifying local structure motifs.
- To combine both structural and sequence information for enhanced motif detection.
- To provide a tool for automatic functional annotation of proteins.
Main Methods:
- Developed a novel structural alignment algorithm integrating structural and sequence data.
- Applied the algorithm to identify known motifs, including the beta beta alpha-metal binding motif and the treble clef motif.
- Validated the method's effectiveness in automatic motif identification.
Main Results:
- The algorithm successfully identified the beta beta alpha-metal binding motif and the treble clef motif.
- Demonstrated the capability to detect motifs with variable conformations and sequences automatically.
- Achieved encouraging results in identifying structural motifs associated with specific functions.
Conclusions:
- The developed algorithm effectively automates the identification of local structure motifs.
- This method offers a significant advancement over manual procedures for motif discovery.
- The approach holds promise for advancing automatic functional annotation in proteomics.
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