Statistical Coupling Analysis Predicts Correlated Motions in Dihydrofolate Reductase

Area of Science:

• Biochemistry
• Molecular Biology
• Protein Dynamics

Background:

• Dihydrofolate reductase (DHFR) is a model system for protein dynamics research.
• Previous studies identified residue networks involved in DHFR dynamics, with mutations affecting motion and catalysis.
• The influence of dynamically coupled residues on DHFR evolution remains unclear.

Purpose of the Study:

• To investigate the role of coevolving residue networks in DHFR dynamics and evolution.
• To analyze allosteric communication disruption in a specific DHFR mutant.
• To identify potential sites for functional motifs in human DHFR and understand evolutionary dynamics.

Main Methods:

• Statistical coupling analysis
• Molecular dynamic simulations
• Analysis of DHFR mutations (N23PP/S148A) in *E. coli*
• Identification of conserved motifs in human DHFR

Main Results:

• A network of coevolving residues with correlated motions was identified in DHFR.
• Allosteric communication was significantly reduced in the N23PP/S148A *E. coli* DHFR mutant.
• Two potential sites in human DHFR were identified for accommodating the Met20 loop double proline motif.
• Human DHFR exhibits concerted evolutionary changes in allosteric networks, maintaining dynamic communication.

Conclusions:

• Protein dynamics and coevolving residue networks play a critical role in DHFR evolution.
• Allosteric communication pathways are sensitive to mutations and conserved through evolution.
• Dynamic coupling is a significant factor driving the evolutionary trajectory of proteins like DHFR.