Graphical analysis of pH-dependent properties of proteins predicted using PROPKA
© Rostkowski et al; licensee BioMed Central Ltd. 2011
Received: 29 September 2010
Accepted: 26 January 2011
Published: 26 January 2011
Charge states of ionizable residues in proteins determine their pH-dependent properties through their pKa values. Thus, various theoretical methods to determine ionization constants of residues in biological systems have been developed. One of the more widely used approaches for predicting pKa values in proteins is the PROPKA program, which provides convenient structural rationalization of the predicted pKa values without any additional calculations.
The PROPKA Graphical User Interface (GUI) is a new tool for studying the pH-dependent properties of proteins such as charge and stabilization energy. It facilitates a quantitative analysis of pKa values of ionizable residues together with their structural determinants by providing a direct link between the pKa data, predicted by the PROPKA calculations, and the structure via the Visual Molecular Dynamics (VMD) program. The GUI also calculates contributions to the pH-dependent unfolding free energy at a given pH for each ionizable group in the protein. Moreover, the PROPKA-computed pKa values or energy contributions of the ionizable residues in question can be displayed interactively. The PROPKA GUI can also be used for comparing pH-dependent properties of more than one structure at the same time.
The GUI considerably extends the analysis and validation possibilities of the PROPKA approach. The PROPKA GUI can conveniently be used to investigate ionizable groups, and their interactions, of residues with significantly perturbed pKa values or residues that contribute to the stabilization energy the most. Charge-dependent properties can be studied either for a single protein or simultaneously with other homologous structures, which makes it a helpful tool, for instance, in protein design studies or structure-based function predictions. The GUI is implemented as a Tcl/Tk plug-in for VMD, and can be obtained online at http://propka.ki.ku.dk/~luca/wiki/index.php/GUI_Web.
The pH dependence of important protein properties such as binding affinity, catalytic activity, solubility, charge and stability is determined by ionizable residues [1–3]. Thus, it is of great importance for researches to have access to a reliable description of these residues. Protonation states of ionizable groups can be described with titration curves and ionization constants (pKa values). Because pKa values are difficult to obtain experimentally, especially for large biological systems, several software packages have been developed to predict them based on the protein structure [4–6]. PROPKA [7–9] is one of the popular protein pKa prediction software packages mainly because of its speed and accuracy compared to other methods [4, 6], but also because it offers a structural rationalization of the predicted pKa values.
Here, ΔGU(pHref) is the unfolding free energy at a reference pH, and the latter term is the pH-dependent change in the unfolding free energy related to the change in protein charge Q between two folding states. Thus, the perturbed protein pKa values are used to calculate the charge of the folded protein, whereas pKmodel values are used for the unfolded state.
The results from the PROPKA calculations can be very helpful, and give detailed information about the influence of the protein environment on the ionizable groups. Nevertheless, the PROPKA output does not provide a direct link between obtained pKa values and the three-dimensional structure of the studied system. In order to complete analysis of the ionizable residues one needs to make a separate search of these residues together with the interactions determining their pKa values by hand, using software for visualizing biomolecules. Furthermore, studying raw text data for larger sets of structures can easily become a difficult, complex and time-consuming task.
The PROPKA Graphical User Interface (GUI) presented in this paper is developed to facilitate exploration of the pH-dependent protein properties in a convenient manner by providing a direct link between the structure and the pKa data, predicted by the PROPKA calculations, via the Visual Molecular Dynamics (VMD) program . Our interface is an easy-to-use tool to identify and rationalize residues with unusual pKa values or those significantly contributing to the free energy of unfolding. The PROPKA GUI is designed to facilitate the use of the PROPKA program and interpreting its results both for the user's convenience and to increase accessibility to the PROPKA approach for a wide range of researchers. Additionally, our GUI allows for comparative studies of the pH-dependent properties of many structures together, which can be used to rationalize the differences in these properties between homologous structures.
The PROPKA GUI is written in the Tool Command programming Language with the Tk graphical user interface (Tcl/Tk) as a platform-independent plug-in for the VMD program. The VMD program was chosen as a host application for the PROPKA GUI as it offers a great versatility of options and tools for analyzing biological structures, and also because it provides the Tcl/Tk environment as an extension of the VMD core code functionality without the need of making any additional installations. Besides, Tcl/Tk gives a wide range of users an easy but powerful tool to develop their own programs or scripts, or to extend already existing ones. The PROPKA GUI requires the VMD package to be installed on the user's computer. VMD can be obtained online at http://www.ks.uiuc.edu/Research/vmd/. The current version of our GUI is available as a single file that has to be copied into the VMD plug-ins directory and adding only one line into the VMD starting script makes the PROPKA GUI available from the menu in the main VMD window. The PROPKA GUI source-code, which is freely distributed under the GNU General Public License (GPL), installation instructions, documentation, and a screencast tutorial are available on the web at http://propka.ki.ku.dk/~luca/wiki/index.php/GUI_Web.
All residues and graphical objects displayed using the PROPKA GUI such as ionizable residues, pKa determinants, ligands, etc., depending on their type, are shown using pre-defined sets of VMD settings and representations. These representations can easily be accessed and modified in the "Graphical Representations" window of VMD. In order to make the PROPKA GUI more convenient to use, the user can also easily display the desired VMD selections, or remove previously shown, directly from the GUI. By default, all labels displaying the desired pKa information in the structure display window of VMD are drawn using different sets of colors for each molecule. Moreover, corresponding labels for different loaded structures, depending on their molecule ID in VMD, are shifted relative to each other to increase their readability in the case of overlapping residues, which considerably facilitates using the GUI for comparative protein studies. Additionally, the information shown in the structure display window is also printed in the VMD text console.
Results and Discussion
The PROPKA GUI compares the computed pKa values to pKmodel values and can display residues with the largest pKa shifts. Based on equation 2, the GUI also computes and displays the contribution of each ionizable residue to the pH-dependent part of the free energy of unfolding. The GUI can therefore be used to display residues contributing the most to the unfolding energy. Moreover, it provides an interactive access to the pKa determinants listed in the PROPKA output file through the structure display window of VMD.
After installation of the PROPKA GUI plug-in, its main window (Figure 1A) can be accessed from the "Extensions" → "Analysis" menu in the main VMD window. By default, when the data from the PROPKA calculations and the appropriate PDB file are loaded, the structure is displayed automatically in the structure display window with a simplified-style drawing method (Figure 1B).
More detailed pKa data can be accessed via the structure display window when the mouse picking mode is set to one of its "Label" actions. By default, when an ionizable residue or ionizable ligand atom is selected, all of its pKa determinants are displayed. In addition to the pKa value and the desolvation contribution for the selected residue, contributions to the pKa shift for all determinants are shown with the appropriate labels. Instead of displaying determinants, one can also choose to show only the pKa value or the contribution to the free energy of unfolding at a given pH. When the GUI interactive mode is disabled, VMD can be used in the standard way for analyzing the structure, making measurements of interatomic distances, angles, etc. As an example, we try to rationalize why the pKa value of tyrosine 80 in BCX is so extremely up-shifted compared to its model pKa value (20.7 compared to 10). By "clicking" on the residue with the mouse, we find that tyrosine 80 interacts strongly with three neighboring ionizable residues: glutamic acid 78, tyrosine 69, and second glutamic acid 172 (see Figure 2B). These contribute to raising the pKa value through unfavorable charge-charge interactions (CC) by 2.4, 1.6 and 2.4 pH units, respectively. Increase of the pKa value, but to a smaller extent, is also achieved by charge-charge interaction with tyrosine 65 and by hydrogen bonds to the side chains (SHB) of the mentioned glutamic acids. In addition, tyrosine 80 is buried in the protein, and therefore shielded from the solvent, which raises its pKa value by additional 3 pH units due to the desolvation energy (DS).
Currently, the second version of the PROPKA GUI is under development. The main improvements will extend the basic GUI functionality by automated and user-friendly procedures for protein structure comparisons in order to better understand their pH-dependent properties. It will provide the user with a more advanced, but still convenient tool for a quick and robust analysis of structural differences determining different ionization constants of corresponding residues for large sets of homologous structures. Then, if needed, the tool can be used to suggest and verify desired modifications to the studied structures within seconds.
Our newly developed PROPKA GUI is a powerful and convenient plug-in for VMD providing a direct link between the PROPKA-computed pKa values, their determinants and the three-dimensional structures. The GUI significantly improves ease of use of the PROPKA approach, and facilitates quick and easy investigation of the pH-dependent properties of proteins such as charge and stabilization energy as well as the separate pKa values and interactions determining them. It can easily be used to identify and rationalize ionizable residues with perturbed pKa values or contributing to the pH-dependent stabilization energy the most, either for a single protein or in comparison with other structures. This makes our GUI a helpful tool, for example, in the structure-based function prediction or protein design studies. Moreover, the PROPKA GUI is an open source code written in Tcl/Tk that can easily be customized whenever needed.
Availability and requirements
Project name: PROPKA GUI
Project home page: http://propka.ki.ku.dk/~luca/wiki/index.php/GUI_Web
Operating system(s): Platform independent
Programming language: Tcl/Tk
Other requirements: VMD program installed
License: GNU General Public License
Restrictions to use by non-academics: None
This work was supported by the Danish Council for Strategic Research through a research grant from the Program Commission on Strategic Growth Technologies (2106-07-0030). CRS was supported by the ERUDESP EU collaborative project.
- Sharp KA, Honig B: Electrostatic Interactions in Macromolecules - Theory and Applications. Annu Rev Biophys Biophys Chem 1990, 19: 301–332. 10.1146/annurev.bb.19.060190.001505View ArticlePubMedGoogle Scholar
- Pace CN, Grimsley GR, Scholtz JM: Protein Ionizable Groups: pK Values and Their Contribution to Protein Stability and Solubility. J Biol Chem 2009, 284: 13285–13289. 10.1074/jbc.R800080200PubMed CentralView ArticlePubMedGoogle Scholar
- Nakamura H: Roles of electrostatic interaction in proteins. Q Rev Biophys 1996, 29: 1–90. 10.1017/S0033583500005746View ArticlePubMedGoogle Scholar
- Davies MN, Toseland CP, Moss DS, Flower DR: Benchmarking pK(a) prediction. BMC Biochem 2006, 7: 18. 10.1186/1471-2091-7-18PubMed CentralView ArticlePubMedGoogle Scholar
- Lee AC, Crippen GM: Predicting pKa. J Chem Inf Model 2009, 49: 2013–2033. 10.1021/ci900209wView ArticlePubMedGoogle Scholar
- Stanton CL, Houk KN: Benchmarking pK(a) prediction methods for residues in proteins. J Chem Theory Comput 2008, 4: 951–966. 10.1021/ct8000014View ArticleGoogle Scholar
- Li H, Robertson AD, Jensen JH: Very fast empirical prediction and rationalization of protein pKa values. Proteins 2005, 61: 704–721. 10.1002/prot.20660View ArticlePubMedGoogle Scholar
- Bas DC, Rogers DM, Jensen JH: Very fast prediction and rationalization of pKa values for protein-ligand complexes. Proteins 2008, 73: 765–783. 10.1002/prot.22102View ArticlePubMedGoogle Scholar
- Olsson MHM, Søndergaard CR, Rostkowski M, Jensen JH: PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions. J Chem Theory Comput, in press.
- Yang AS, Honig B: On the Ph-Dependence of Protein Stability. J Mol Biol 1993, 231: 459–474. 10.1006/jmbi.1993.1294View ArticlePubMedGoogle Scholar
- Kongsted J, Ryde U, Wydra J, Jensen JH: Prediction and rationalization of the pH dependence of the activity and stability of family 11 xylanases. Biochem 2007, 46: 13581–13592. 10.1021/bi7016365View ArticleGoogle Scholar
- Humphrey W, Dalke A, Schulten K: VMD: Visual molecular dynamics. J Mol Graph 1996, 14: 33–38. 10.1016/0263-7855(96)00018-5View ArticlePubMedGoogle Scholar
- Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al.: The Protein Data Bank. Nucleic Acids Res 2000, 28: 235–242. 10.1093/nar/28.1.235PubMed CentralView ArticlePubMedGoogle Scholar
- Roberts E, Eargle J, Wright D, Luthey-Schulten Z: MultiSeq: unifying sequence and structure data for evolutionary analysis. BMC Bioinf 2006, 7: 382. 10.1186/1471-2105-7-382View ArticleGoogle Scholar
- Wakarchuk WW, Campbell RL, Sung WL, Davoodi J, Yaguchi M: Mutational and Crystallographic Analyses of the Active-Site Residues of the Bacillus-Circulans Xylanase. Protein Sci 1994, 3: 467–475. 10.1002/pro.5560030312PubMed CentralView ArticlePubMedGoogle Scholar
- Elcock AH: Prediction of functionally important residues based solely on the computed energetics of protein structure. J Mol Biol 2001, 312: 885–896. 10.1006/jmbi.2001.5009View ArticlePubMedGoogle Scholar
- Ondrechen MJ, Clifton JG, Ringe D: THEMATICS: A simple computational predictor of enzyme function from structure. Proc Natl Acad Sci USA 2001, 98: 12473–12478. 10.1073/pnas.211436698PubMed CentralView ArticlePubMedGoogle Scholar
- Torronen A, Rouvinen J: Structural Comparison of two Major Endo-1,4-Xylanases from Trichoderma-Reesei. Biochem 1995, 34: 847–856. 10.1021/bi00003a019View ArticleGoogle Scholar
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