Computational titration analysis of a multiprotic HIV-1 protease-ligand complex

Area of Science:

• Biochemistry
• Computational Biology
• Structural Biology

Background:

• Protein-ligand interactions are crucial in biological processes.
• Accurate determination of protonation states is essential for understanding protein function and drug design.
• Existing methods struggle with complexes containing multiple ionizable groups.

Purpose of the Study:

• To introduce and validate a novel computational method for analyzing protonation states in complex protein-ligand systems.
• To apply this method to a specific case: the interaction between Glu-Asp-Leu peptide and HIV-1 protease.
• To correlate computational predictions with experimental data for validation.

Main Methods:

• Development of a new computational approach for analyzing protonation states.
• Application of the method to a protein-ligand complex with eight ionizable groups (peptide and HIV-1 protease).
• Comparison of calculated titration curves with experimental data, assessing accuracy.

Main Results:

• The computational method was successfully applied to the HIV-1 protease-peptide complex.
• A high correlation (error of ~0.6 kcal mol-1) was found between calculated and experimental titration curves.
• Analysis indicated that 4-5 out of 8 ionizable groups were protonated at the crystallization pH.

Conclusions:

• The new computational method provides accurate predictions of protonation states in complex systems.
• The findings offer insights into the specific protonation status of the HIV-1 protease active site at crystallization pH.
• This method has potential applications in drug discovery and understanding enzyme mechanisms.