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Updated: Jul 19, 2026
10:58
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
Thoroughly sampling sequence space: large-scale protein design of structural ensembles.
Stefan M Larson1, Jeremy L England, John R Desjarlais
1Chemistry Department and Biophysics Program, Stanford University, California 94305, USA.
Protein Science : a Publication of the Protein Society
|November 21, 2002
Summary
Computational protein design incorporating backbone flexibility reveals vast sequence diversity. This approach, designing to structural ensembles, offers new insights into protein sequence space and evolution.
Area of Science:
- Computational biology
- Protein engineering
- Structural biology
Background:
- Accurate computational protein design requires modeling inherent protein backbone flexibility.
- Exploring protein sequence space necessitates understanding this flexibility.
Purpose of the Study:
- To explore protein sequence space broadly by designing proteins to structural ensembles, incorporating backbone flexibility.
- To investigate the diversity and characteristics of designed protein sequences.
Main Methods:
- Utilized a distributed computing architecture for large-scale protein design.
- Generated hundreds of thousands of diverse sequences for 253 natural proteins by designing to structural ensembles.
- Performed homology searches using designed sequence profiles against the Protein Data Bank.
Main Results:
- Designing to structural ensembles yielded significantly greater sequence diversity compared to previous studies.
- Designed sequences maintained relevance and quality, as confirmed by homology searches.
- Designed sequences exhibited higher overall diversity than natural sequence alignments, with no direct correlation observed.
- Sequence entropies of designed sequences clustered tightly within the same protein fold, separating distinct folds.
Conclusions:
- Protein structure's overall fold primarily determines the diversity of designed sequences.
- The principle of designability, observed in simpler models, holds true for real proteins.
- Findings have significant implications for experimental protein design, engineering, and understanding protein evolution.
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