In Silico Fold-Switching Protein Design Driven by Cα-Based Statistical Potential

Area of Science:

• Protein engineering and computational biology.
• Investigating protein structural plasticity and fold-switching phenomena.

Background:

• Proteins naturally exhibit structural plasticity, altering conformation in response to environmental cues.
• Existing computational methods excel at designing proteins for single stable structures, but designing sequences for multiple distinct folds remains challenging.
• The ability of proteins to adopt divergent structures is crucial for biological functions.

Purpose of the Study:

• To computationally design protein sequences with high sequence similarity that adopt structurally divergent folds.
• To identify and validate fold-switching protein sequences.
• To explore the impact of single point mutations on inducing fold switching.

Main Methods:

• Utilized Monte Carlo simulations to design 28 pairs of protein sequences.
• Sequences were designed to adopt either a 3-alpha (3-α) helix fold or a 4-beta plus alpha (4β + α) fold.
• Rational design and sequence analysis were employed to generate sequence variants and test fold-switching induction via point mutations.

Main Results:

• Successfully designed three sets of fold-switching sequences with high sequence similarity (89.29% and 87.50%).
• Designed sequences exhibited distinct tertiary structures (3-α helix fold and 4β + α fold) despite minimal sequence divergence.
• Single point mutations (e.g., D26C, A39F) in designed sequences induced fold switching from 3-α to 4β + α fold, maintaining 98% sequence similarity.

Conclusions:

• The developed computational design approach successfully generates fold-switching protein sequences.
• Statistical potentials effectively balance competing structural constraints to achieve fold switching.
• The findings demonstrate the feasibility of designing proteins with tunable structural outcomes and highlight the potential for precise control over protein conformation through minimal sequence changes.