Stereoelectronic effects in stabilizing protein-N-glycan interactions revealed by experiment and machine learning

Area of Science:

• Biochemistry
• Structural Biology
• Computational Chemistry

Background:

• Protein-carbohydrate interactions are vital in biological processes but poorly understood quantitatively.
• Predicting and manipulating these interactions is challenging due to incomplete knowledge of their thermodynamic basis in solution.

Purpose of the Study:

• To investigate the role of stereoelectronic effects in stabilizing protein-N-glycan interactions within a folding protein context.
• To develop predictive models for protein-carbohydrate interaction energetics.

Main Methods:

• Utilized double-mutant cycle analyses on 52 electronically varied N-glycoproteins.
• Employed quantum mechanical calculations and machine learning for modeling.
• Correlated interaction energies with molecular orbital energy gaps.

Main Results:

• Demonstrated enthalpy-entropy compensation dependent on the electronics of interacting side chains.
• Developed linear and nonlinear models explaining up to 97% of interaction energy variability.
• Found strong correlations between protein-carbohydrate interaction energies and molecular orbital energy gaps.

Conclusions:

• Stereoelectronic effects play a crucial role in stabilizing protein-N-glycan interactions.
• Accurate modeling of short-range van der Waals interactions requires greater consideration of stereoelectronic effects.
• Predictive models based on quantum mechanics and machine learning show high accuracy for interaction energetics.