Structure-mechanics statistical learning uncovers mechanical relay in proteins.

Area of Science:

• Molecular physics and physical chemistry
• Structural biology
• Biophysics

Background:

• Understanding protein adaptation to substrates is crucial in molecular physics and physical chemistry.
• Proteins undergo conformational changes and exhibit allostery, but the underlying mechanisms are not fully understood.

Purpose of the Study:

• To establish a mechanical perspective on protein adaptive responses to substrates.
• To investigate how mechanical rigidity changes propagate through protein structures.

Main Methods:

• Employed a structure-mechanics statistical learning method.
• Mapped all-atom molecular dynamics simulations to an elastic network model.
• Assembled a rigidity graph representing inter-residue coupling strength using chemical moiety-specific force constants.

Main Results:

• Identified chains of spatially contiguous residues exhibiting significant mechanical rigidity changes upon substrate binding/dissociation in S1A protease and PDZ3 domain.
• Demonstrated that changes in mechanical rigidity propagate through the protein structure.
• Localized responsive mechanical hotspots to residues with important biological functions or high mutation sensitivity.

Conclusions:

• A mechanical-relay mechanism underpins protein conformational changes, long-range communication, and allostery.
• Protein rigidity changes upon substrate interaction provide a mechanistic explanation for these phenomena.
• Key residues acting as mechanical hotspots are critical for protein function and stability.