Deciphering GB1's Single Mutational Landscape: Insights from MuMi Analysis.

Area of Science:

• Structural biology
• Computational biophysics
• Protein engineering

Background:

• Deep mutational scanning (DMS) has mapped mutations affecting Streptococcal protein G (GB1) binding to human IgG-Fc.
• Experimental binding affinities for single mutations are available in the literature.

Purpose of the Study:

• To investigate the molecular basis of GB1-IgG-Fc binding using computational methods.
• To assess the utility of in silico mutational scanning and molecular dynamics for predicting protein fitness landscapes.

Main Methods:

• Performed in silico mutational scanning for all single mutations of GB1.
• Conducted 2 μs molecular dynamics (WT-MD) of wild-type GB1 in unbound and IgG-Fc bound states.
• Analyzed hydrogen bonds, residue solvent accessibility, and binding interface probabilities using WT-MD and Mutation and Minimization (MuMi) conformations.

Main Results:

• Identified dominant hydrogen bonds critical for GB1-IgG-Fc binding.
• Explained the GB1-IgG-Fc binding fitness landscape by analyzing MuMi conformations.
• Investigated binding dynamics, including residue accessibility and interface localization.

Conclusions:

• Mutation and Minimization (MuMi) is a reliable and efficient computational tool for predicting protein fitness landscapes.
• The study provides insights into GB1-IgG-Fc interactions and binding structural features.
• Methodologies advance predictive accuracy in protein stability and interaction studies for drug design and synthetic biology.