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Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding
Published on: September 15, 2010
The evolution of catalytic function in the HIV-1 protease
Manoj Kumar Singh1, Kristina Streu, Andrew J McCrone
1Department of Chemistry, Clemson University, Clemson, SC 29634, USA.
Journal of Molecular Biology
|March 8, 2011
Summary
Understanding HIV-1 protease evolution involves analyzing molecular fitness. This study reveals that destabilizing the enzyme-substrate binding may optimize its activity, suggesting independent evolutionary paths for specificity and catalysis.
Area of Science:
- Biomolecular evolution
- Enzyme kinetics
- Computational biophysics
Background:
- Species evolution relies on optimizing fitness functions, which at the molecular level relate to physiochemical properties.
- HIV-1 protease's evolution is crucial for understanding viral replication and developing inhibitors.
Purpose of the Study:
- Investigate the physical-chemical mechanisms driving HIV-1 protease evolution.
- Analyze the impact of single amino acid mutations on enzyme activity and binding affinity.
- Explore the relationship between substrate binding, transition state binding, and catalytic efficiency.
Main Methods:
- Employed molecular simulation techniques.
- Utilized the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) approach.
- Analyzed thermodynamic properties and binding affinities for 40 single amino acid mutations.
Main Results:
- The MM/PBSA approach accurately predicted experimentally determined catalytic activity.
- No correlation was found between mutation effects on substrate binding and transition state binding.
- Ground-state destabilization (reduced substrate binding) emerged as a potential evolutionary optimization mechanism.
Conclusions:
- HIV-1 protease evolution may involve independent pathways for optimizing substrate specificity and catalytic activity.
- Ground-state destabilization is a plausible mechanism for enhancing enzyme activity in vivo.
- Computational methods can provide significant insights into biomolecular evolution and enzyme function.
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