Modeling Protein Conformational Transition Pathways Using Collective Motions and the LASSO Method

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• Proteins exist in multiple conformational states, crucial for their diverse functions.
• Protein topology influences the global dynamics governing transitions between these states.

Purpose of the Study:

• To develop a method for generating transition pathways between protein conformational states.
• To identify the most efficient routes along collective motions for conformational changes.

Main Methods:

• Perturbing proteins toward target states along thermally accessible collective motions.
• Utilizing the least absolute shrinkage and selection operator (LASSO) to find parsimonious routes.
• Calculating soft modes using the anisotropic network model.

Main Results:

• A method was developed to generate transition pathways between protein conformational states.
• Analysis of 436 protein-protein interactions revealed such paths exist for most cases.
• Identified pathways were found to be low in energy, suggesting efficient transitions.

Conclusions:

• The method provides insights into atomic modeling for protein recognition.
• Identified pathways can constrain sampling in computational protein modeling.
• The findings have implications for understanding protein dynamics and function.