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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
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Evolutionary selection of proteins with two folds
Joseph W Schafer1, Lauren L Porter2,3
1National Library of Medicine, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, 20894, USA.
Nature Communications
|September 6, 2023
Summary
Researchers discovered a new method to identify dual-protein structures, revealing that fold-switching proteins are evolutionarily advantageous. This finding enables predicting multiple protein conformations from a single sequence.
Area of Science:
- Protein structure and dynamics
- Computational biology
- Evolutionary biology
Background:
- Most proteins adopt a single stable structure, but some can switch folds in response to stimuli.
- Current algorithms fail to predict these alternative folds, missing crucial functional information.
- These algorithms infer protein structure from coevolved amino acid pairs, but may miss signatures.
Purpose of the Study:
- To develop a method to detect missed coevolutionary signatures in fold-switching proteins.
- To investigate the evolutionary significance of proteins adopting multiple conformations.
- To enable accurate prediction of diverse protein structures from single sequences.
Main Methods:
- Developed Alternative Contact Enhancement (ACE) to search protein superfamilies and subfamilies.
- ACE identifies coevolutionary signatures corresponding to multiple protein conformations.
- Applied ACE-derived contacts to predict protein structures and develop a prediction pipeline.
Main Results:
- ACE successfully identified dual-fold coevolution in 56/56 fold-switching proteins across diverse families.
- Predicted two experimentally consistent conformations for a protein with an unsolved structure.
- Developed a blind prediction pipeline for fold-switching proteins.
Conclusions:
- Fold-switching proteins possess widespread dual-fold coevolution, indicating evolutionary preservation.
- The ability to switch folds provides an evolutionary advantage, highlighting functional importance.
- This work paves the way for predicting diverse protein structures from single sequences.
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