Perturbation response scanning specifies key regions in subtilisin serine protease for both function and stability

Area of Science:

• Computational enzymology
• Biophysics
• Protein dynamics

Background:

• Understanding enzyme stability and catalytic activity is crucial for drug design and biotechnology.
• Identifying specific amino acid residues responsible for these properties remains a challenge.
• Enzyme-inhibitor complexes offer a model system to study these effects.

Purpose of the Study:

• To computationally infer amino acids critical for enzyme stability and catalytic activity.
• To validate these inferences using molecular dynamics simulations and coarse-grained methodologies.
• To investigate the enzyme-inhibitor complex of subtilisin serine protease.

Main Methods:

• Designing molecular dynamics simulations of the enzyme-inhibitor complex.
• Devising coarse-grained methodologies based on the elastic network model.
• Analyzing cross-correlations of residue fluctuations and applying perturbation scanning.

Main Results:

• Both computational methods successfully identified key regions responsible for enzyme properties.
• The identified regions (50-61, 155-164, and 192-194) are consistent between the two methods.
• These computationally predicted regions align with experimentally validated important sites in subtilisin.

Conclusions:

• Computational approaches, including molecular dynamics and coarse-grained modeling, can reliably predict amino acids influencing enzyme stability and activity.
• The cross-correlation of residue fluctuations is a valuable metric for identifying functionally important regions within enzyme-inhibitor complexes.
• This study validates computational predictions against experimental data, highlighting their utility in enzymology research.