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Updated: Jul 18, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
Modeling the evolution of protein domain architectures using maximum parsimony
Jessica H Fong1, Lewis Y Geer, Anna R Panchenko
1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.
Protein domain architectures evolve through gene fusion and fission events. Most architectures gain complexity over time, with fusion being more common than fission, offering insights into protein evolution.
Area of Science:
- Evolutionary biology
- Bioinformatics
- Computational biology
Background:
- Proteins are composed of domains, the basic units of evolution.
- Protein domain architectures link related proteins and their functions.
- Understanding the evolutionary pathways of these architectures is crucial.
Purpose of the Study:
- To identify evolutionary pathways of protein domain architectures.
- To model architecture evolution via rearrangements and domain acquisition.
- To rank evolutionary scenarios using a parsimony principle.
Main Methods:
- Analysis of domain architectures across 159 proteomes.
- Modeling evolution using fission and fusion operations.
- Employing a parsimony principle to infer likely evolutionary pathways.
Main Results:
- Over 85% of known protein architectures' histories were estimated.
- Architecture evolution is robust to alternative parsimony rules.
- 87% of architectures increase in complexity, with fusion events 5.6 times more frequent than fission.
Conclusions:
- Protein domain architectures predominantly evolve towards increased complexity.
- The proposed model accurately estimates evolutionary histories.
- Results enable computation of domain architecture similarities and new functional insights.
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