Sparse networks of directly coupled, polymorphic, and functional side chains in allosteric proteins

Area of Science:

• Computational Biology
• Structural Biology
• Biophysics

Background:

• Allosteric behavior in proteins is increasingly linked to coupled side-chain fluctuations.
• X-ray crystallography reveals prevalent alternate side-chain conformations (conformational polymorphism).
• Existing computational methods need enhancement to address side-chain conformational polymorphism in allostery studies.

Purpose of the Study:

• To develop a novel computational approach for analyzing allosteric proteins that incorporates side-chain conformational polymorphism.
• To extract direct couplings of side chains and represent them as sparse networks.
• To provide a more accurate understanding of information transmission and functional interactions in proteins.

Main Methods:

• A novel approach to generate an ensemble of protein conformations.
• An efficient computational method to extract direct side-chain couplings in allosteric proteins.
• Construction of sparse network representations of side-chain couplings, accounting for conformational polymorphism.

Main Results:

• A method to construct networks of functionally crucial residues by studying the intrinsic dynamics of inactive protein structures.
• The proposed method reveals couplings between alternate conformations of residue pairs.
• Demonstration of a magnified view of coupled and conformationally polymorphic residues.

Conclusions:

• This is the first computational method for extracting networks of side chains' alternate conformations.
• The developed networks offer a detailed view of side-chain dynamics in functionally important and polymorphic sites.
• The approach enhances understanding of allosteric mechanisms by considering side-chain conformational diversity.