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Updated: Jun 13, 2025
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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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Computational design of conformation-biasing mutations to alter protein functions
Peter E Cavanagh1, Andrew G Xue2, Shizhong Dai3
1Department of Biochemistry, Stanford University.
Biorxiv : the Preprint Server for Biology
|June 12, 2025
Summary
A new computational method called Conformational Biasing (CB) predicts protein variants with desired functions by controlling their conformational states. This approach enhances protein engineering for biotechnology and medicine.
Area of Science:
- Protein engineering
- Computational biology
- Biophysics
Background:
- Proteins exist in multiple functional states.
- Controlling protein conformations can alter function.
- Existing methods for protein engineering are limited.
Purpose of the Study:
- To develop a computational method for predicting protein variants with biased conformational states.
- To validate the method across diverse protein systems.
- To explore the application of this method in protein labeling technologies.
Main Methods:
- Conformational Biasing (CB) uses contrastive scoring with inverse folding models.
- The method was tested on seven deep mutational scanning datasets.
- CB was applied to K-Ras, SARS-CoV-2 spike, β2 adrenergic receptor, Src kinase, and lipoic acid ligase.
Main Results:
- CB successfully predicted variants with improved conformation-specific functions.
- Enhanced effector binding and enzymatic activity were observed.
- A novel mechanism of conformational gating in lipoic acid ligase sequence-specificity was discovered.
- Variants biased towards specific conformations showed altered promiscuity and specificity.
Conclusions:
- Conformational Biasing is a rapid, simple, and versatile tool for engineering protein dynamics.
- The method has broad applicability in basic research, biotechnology, and medicine.
- CB offers new possibilities for understanding and manipulating protein function.
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