Folding and Stabilization of Native-Sequence-Reversed Proteins.
Yuanzhao Zhang1,2, Jeffrey K Weber2, Ruhong Zhou1,2,3
1Institute of Quantitative Biology, Department of Physics, Zhejiang University, Hangzhou 310027, China.
Scientific Reports
|April 27, 2016
Summary
Investigating protein folding, this study reveals that reversed native protein sequences fold differently than random sequences. Protein size and core flexibility impact reverse-sequence folding, with mutations aiding beta-hairpin formation.
Area of Science:
- Biophysics
- Computational Biology
- Protein Science
Background:
- The protein folding problem, determining a protein's 3D structure from its amino acid sequence, is complex.
- The folding behavior of reversed native protein sequences remains largely uninvestigated.
- Native protein sequences possess inherent properties that facilitate folding, unlike random sequences.
Purpose of the Study:
- To explore the folding capabilities of reversed native protein sequences.
- To analyze how protein size and hydrophobic core flexibility influence reverse-sequence folding.
- To develop strategies for guiding the folding of reverse sequences that fail to adopt native-like structures.
Main Methods:
- Utilized a tandem protein structure prediction algorithm.
- Employed molecular dynamics simulations to analyze folding pathways.
- Investigated small proteins of increasing structural complexity (alpha-helix, beta-hairpin, alpha-helix bundle, alpha/beta-protein).
- Applied a mutational strategy for beta-hairpins that failed to fold.
Main Results:
- Reverse sequences' ability to form native-like folds depends significantly on protein size.
- Hydrophobic core flexibility is a critical factor in successful reverse-sequence folding.
- Insertion of amino acids into the beta-turn region can guide stable beta-hairpin formation in reverse sequences.
Conclusions:
- Reverse protein sequences exhibit distinct folding behaviors compared to random sequences.
- Protein sequence-structure mapping is influenced by sequence directionality.
- Findings may inform novel protein design and structure prediction methodologies.
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