Dissecting protein architecture with communication blocks and communicating segment pairs

Area of Science:

• Structural biology
• Computational biophysics
• Protein dynamics

Background:

• Protein function is intrinsically linked to conformational dynamics and motions.
• Understanding these dynamics is crucial for deciphering protein mechanisms.
• Computational tools are needed to systematically analyze protein conformational ensembles.

Purpose of the Study:

• To present a novel method, Communication Mapping (COMMA), for deciphering protein dynamical architecture.
• To provide a systematic approach for extracting biological information from protein dynamics.

Main Methods:

• Extracting residue-based dynamic properties from all-atom molecular dynamics simulations.
• Integrating dynamic properties into a graph theoretic framework.
• Identifying and characterizing mediating residue groups and protein regions.

Main Results:

• COMMA identifies communication blocks and communicating segment pairs, detailing their roles.
• The method quantifies connections and communication strengths within proteins.
• Demonstrated utility on archetypal proteins: protein A, tyrosine kinase KIT, and p53.

Conclusions:

• COMMA enables direct comparison of protein dynamics across different proteins or conditions.
• Facilitates identification of key residues in allosteric regulation and mechanistic explanation of mutations.
• COMMA is an automated, broadly applicable tool available at www.lcqb.upmc.fr/COMMA.