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FASSM: enhanced function association in whole genome analysis using sequence and structural motifs
Kumar Gaurav1, Nitin Gupta, Ramanathan Sowdhamini
1National Centre for Biological Sciences, UAS-GKVK campus, Bellary Road, Bangalore 560 065, India.
In Silico Biology
|November 5, 2005
Summary
We developed FASSM, a novel algorithm for detecting remote protein homology, including circular permutations and discontinuous domains. This tool accurately annotates protein sequences and analyzes domains, even at low sequence identities.
Area of Science:
- Bioinformatics
- Computational Biology
- Structural Bioinformatics
Background:
- Detecting remote homology is crucial for understanding protein evolution and function.
- Identifying proteins with circular permutations, discontinuous domains, and few conserved residues presents significant challenges.
- Existing methods may struggle with these complex evolutionary relationships.
Purpose of the Study:
- To introduce FASSM, a new algorithm for detecting remote protein homology.
- To improve the identification of proteins with challenging structural features like discontinuous domains.
- To enhance protein sequence annotation and domain analysis.
Main Methods:
- Developed FASSM (Family Alignment Search using Sequence Motifs) algorithm.
- Input: Multiply aligned protein sequence profiles.
- Algorithm analyzes sequence conservation and motif positions for family signatures.
Main Results:
- FASSM achieves 93% coverage compared to HMM and IMPALA.
- Successfully detects remote homology, including circular permutations and discontinuous domains.
- Accurate family associations identified at sequence identities as low as 15%.
Conclusions:
- FASSM is an effective tool for detecting challenging protein homology relationships.
- The algorithm facilitates accurate protein sequence annotation and domain analysis.
- FASSM is particularly useful for whole-genome surveys and identifying small domain proteins.