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Updated: Jun 23, 2026
09:51
Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
Published on: July 16, 2017
HorA web server to infer homology between proteins using sequence and structural similarity
Bong-Hyun Kim1, Hua Cheng, Nick V Grishin
1Department of Biochemistry, University of Texas, Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390-9050, USA.
Nucleic Acids Research
|May 7, 2009
Summary
The HorA web server distinguishes protein homology from analogy using combined sequence and structure data. This tool accurately identifies remote evolutionary relatives, improving upon existing protein similarity search methods.
Area of Science:
- Computational Biology
- Structural Bioinformatics
- Evolutionary Biology
Background:
- Protein biological properties are often inferred through evolutionary comparisons.
- Distinguishing homology (shared ancestry) from analogy (convergent evolution) in protein structures is crucial but challenging.
- Existing structural similarity search tools often fail to differentiate between homology and analogy.
Purpose of the Study:
- To develop a novel web server, HorA (Homology or Analogy), for identifying likely protein homologs.
- To address the limitation of existing methods in distinguishing homology from analogy.
- To provide a tool for uncovering biologically meaningful evolutionary relationships.
Main Methods:
- Integration of state-of-the-art sequence profile methods with spatial structure similarity measures.
- Development of an advanced computational technique to combine diverse data types.
- Utilizing the curated SCOP database for evaluation.
Main Results:
- The HorA method demonstrates high accuracy, identifying approximately 90% of remote homologs as defined in SCOP.
- HorA effectively combines sequence and structural information for more reliable homolog detection.
- The server successfully identifies biologically meaningful connections beyond mere 3D structural resemblance.
Conclusions:
- HorA provides a significant advancement in identifying remote protein homologs.
- The tool is particularly valuable for discovering evolutionary relationships missed by purely sequence or structure-based methods.
- HorA enhances comparative analysis in protein research by accurately distinguishing homology from analogy.
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