Identification of hot regions in protein-protein interactions by sequential pattern mining
2007

Finding Important Areas in Protein Interactions

Sample size: 218 publication Evidence: moderate

Author Information

Author(s): Hsu Chen-Ming, Chen Chien-Yu, Liu Baw-Jhiune, Huang Chih-Chang, Laio Min-Hung, Lin Chien-Chieh, Wu Tzung-Lin

Primary Institution: Yuan Ze University and National Taiwan University

Hypothesis

Can sequential pattern mining effectively identify hot regions in protein-protein interactions?

Conclusion

The study shows that important residues related to protein-protein interactions can be automatically identified using sequential pattern mining.

Supporting Evidence

  • The methodology discovered 900 sequential blocks across 218 proteins.
  • About 66% of the blocks were found near protein-protein interaction interfaces.
  • Approximately 83% of the tested proteins had at least two interacting blocks identified.

Takeaway

This study helps scientists find important parts of proteins that stick together, which can help in understanding how proteins work and in drug discovery.

Methodology

The study used a pattern mining approach to analyze protein sequences and identify conserved residues associated with protein-protein interactions.

Limitations

The study does not address the recall issue of identifying all interacting residues in a single mining process.

Digital Object Identifier (DOI)

10.1186/1471-2105-8-S5-S8

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