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Updated: Jun 21, 2026

Microfluidic Mixers for Studying Protein Folding
Published on: April 10, 2012
Sequence optimization for native state stability determines the evolution and folding kinetics of a small protein.
Stefan M Larson1, Vijay S Pande
1Department of Chemistry and Biophysics Program, Stanford University, Stanford, CA 94305-5080, USA.
Protein evolution is driven by native state stability. Computational simulations reveal that optimizing protein sequences for stability closely mimics natural protein evolution, particularly in SH3 domains.
Area of Science:
- Biochemistry
- Molecular Biology
- Computational Biology
Background:
- Understanding protein evolution is challenging due to reliance on comparing existing natural proteins.
- Key evolutionary drivers like stability, function, and folding kinetics are difficult to isolate.
Purpose of the Study:
- To simulate protein evolution computationally to establish a baseline for comparison.
- To investigate the role of native state stability in driving protein sequence evolution.
Main Methods:
- Utilized large-scale all-atom simulations to model protein evolution.
- Generated diverse SH3 domain sequences selected solely for native state stability.
- Employed phi-value analysis to assess transition state structures.
Main Results:
- Computationally evolved sequences showed 17% pairwise identity to natural sequences.
- Residue frequency distributions in evolved sequences matched natural SH3 sequences at 86% of positions.
- Positions critical for transition state stability were also optimized for native state stability.
Conclusions:
- Optimization for native state stability appears to be a dominant factor in natural SH3 domain evolution.
- A significant correlation exists between optimizing for native state stability and conserving transition state structure.
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