Improving Protein Sequence Alignment with Structural Information
Author Information
Author(s): Ohlson Tomas, Aggarwal Varun, Elofsson Arne, MacCallum Robert M
Primary Institution: Stockholm University
Hypothesis
Can combining evolutionary information, predicted secondary structure, and self-organizing maps improve protein sequence alignment quality?
Conclusion
The study shows that adding self-organizing map locations to predicted secondary structure can further enhance protein sequence alignment quality.
Supporting Evidence
- The addition of self-organizing map locations improves alignment quality slightly.
- Predicted secondary structure significantly enhances alignment quality.
- Combining self-organizing maps with predicted secondary structure yields complementary information.
Takeaway
This study found that using extra information about protein structure can help scientists better align protein sequences, which is important for understanding how proteins work.
Methodology
The study used self-organizing maps to cluster protein sequence profiles and combined these with predicted secondary structure in alignment algorithms.
Limitations
The improvements in alignment quality were small and primarily observed at the fold level.
Statistical Information
P-Value
1ยท10-5
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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