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Updated: Jul 6, 2026
08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile
1San Diego Supercomputer Center and Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. lxie@sdsc.edu
Summary
A new algorithm accurately compares protein functional sites, revealing distant evolutionary links. This method, sequence order-independent profile-profile alignment (SOIPPA), uncovers hidden relationships across protein superfamilies.
Area of Science:
- Computational biology
- Bioinformatics
- Structural biology
Background:
- Protein functional site comparison is crucial for understanding protein evolution and function.
- Identifying distant evolutionary relationships is challenging with traditional sequence or global structure alignment methods.
Purpose of the Study:
- To present a scalable, accurate, reliable, and robust algorithm for protein functional site comparison.
- To detect distant evolutionary relationships that are obscured by global sequence and structure similarity.
Main Methods:
- Development of a novel algorithm utilizing a reduced representation of protein structure.
- Implementation of sequence order-independent profile-profile alignment (SOIPPA).
Main Results:
- The SOIPPA algorithm successfully detected distant evolutionary relationships.
- Identified evolutionary links across previously distinct protein structure superfamilies.
- Demonstrated robustness and scalability of the protein functional site comparison method.
Conclusions:
- SOIPPA is effective in uncovering hidden evolutionary connections between proteins.
- The algorithm aids in exploring the continuity of protein fold space.
- Advances in structural genomics enhance the utility of SOIPPA for evolutionary studies.
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