Calculating pH-dependent free energy of proteins by using Monte Carlo protonation probabilities of ionizable residues.
10.1007/s13238-012-2035-4
- Author:
Qiang HUANG
1
;
Andreas HERRMANN
Author Information
1. State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China. huangqiang@fudan.edu.cn
- Publication Type:Journal Article
- MeSH:
Cathepsin B;
chemistry;
metabolism;
DNA;
metabolism;
Hydrogen-Ion Concentration;
Molecular Dynamics Simulation;
Monte Carlo Method;
Muramidase;
chemistry;
metabolism;
Probability;
Protein Binding;
Proteins;
chemistry;
metabolism;
Protons;
Thermodynamics
- From:
Protein & Cell
2012;3(3):230-238
- CountryChina
- Language:English
-
Abstract:
Protein folding, stability, and function are usually influenced by pH. And free energy plays a fundamental role in analysis of such pH-dependent properties. Electrostatics-based theoretical framework using dielectric solvent continuum model and solving Poisson-Boltzmann equation numerically has been shown to be very successful in understanding the pH-dependent properties. However, in this approach the exact computation of pH-dependent free energy becomes impractical for proteins possessing more than several tens of ionizable sites (e.g. > 30), because exact evaluation of the partition function requires a summation over a vast number of possible protonation microstates. Here we present a method which computes the free energy using the average energy and the protonation probabilities of ionizable sites obtained by the well-established Monte Carlo sampling procedure. The key feature is to calculate the entropy by using the protonation probabilities. We used this method to examine a well-studied protein (lysozyme) and produced results which agree very well with the exact calculations. Applications to the optimum pH of maximal stability of proteins and protein-DNA interactions have also resulted in good agreement with experimental data. These examples recommend our method for application to the elucidation of the pH-dependent properties of proteins.
