pKa Values Of Ionizable Residues Research Articles

Thermodynamic stability as a determinant of the pKa values of ionizable residues in hydrophobic environments in proteins

Thermodynamic stability as a determinant of the pKa values of ionizable residues in hydrophobic environments in proteins

Q-Canonical Monte Carlo Sampling for Modeling the Linkage between Charge Regulation and Conformational Equilibria of Peptides.

The overall charge content and the patterning of charged residues have a profound impact on the conformational ensembles adopted by intrinsically disordered proteins. These parameters can be altered by charge regulation, which refers to the effects of post-translational modifications, pH-dependent changes to charge, and conformational fluctuations that modify the pKa values of ionizable residues. Although atomistic simulations have played a prominent role in uncovering the major sequence-ensemble relationships of IDPs, most simulations assume fixed charge states for ionizable residues. This may lead to erroneous estimates for conformational equilibria if they are linked to charge regulation. Here, we report the development of a new method we term q-canonical Monte Carlo sampling for modeling the linkage between charge regulation and conformational equilibria. The method, which is designed to be interoperable with the ABSINTH implicit solvation model, operates as follows: For a protein sequence with n ionizable residues, we start with all 2n charge microstates and use a criterion based on model compound pKa values to prune down to a subset of thermodynamically relevant charge microstates. This subset is then grouped into mesostates, where all microstates that belong to a mesostate have the same net charge. Conformational distributions, drawn from a canonical ensemble, are generated for each of the charge microstates that make up a mesostate using a method we designate as proton walk sampling. This method combines Metropolis Monte Carlo sampling in conformational space with an auxiliary Markov process that enables interconversions between charge microstates along a mesostate. Proton walk sampling helps identify the most likely charge microstate per mesostate. We then use thermodynamic integration aided by the multistate Bennett acceptance ratio method to estimate the free energies for converting between mesostates. These free energies are then combined with the per-microstate weights along each mesostate to estimate standard state free energies and pH-dependent free energies for all thermodynamically relevant charge microstates. The results provide quantitative estimates of the probabilities and preferred conformations associated with every thermodynamically accessible charge microstate. We showcase the application of q-canonical sampling using two model systems. The results establish the soundness of the method and the importance of charge regulation in systems characterized by conformational heterogeneity.

A comprehensive analysis of the computed tautomer fractions of the imidazole ring of histidines in Loligo vulgaris

A recently introduced electrostatic-based method to determine the pKa values of ionizable residues and fractions of ionized and tautomeric forms of histidine (His) and acid residues in proteins, at a given fixed pH, is applied here to the analysis of a His-rich protein, namely Loligo vulgaris (pdb id 1E1A), a 314-residue all-β protein. The average tautomeric fractions for the imidazole ring of each of the six histidines in the sequence were computed using an approach that includes, but is not limited to, molecular dynamic simulations coupled with calculations of the ionization states for all 94 ionizable residues of protein 1E1A in water at pH 6.5 and 300 K. The electrostatic-calculated tautomeric fractions of the imidazole ring of His were compared with predictions obtained from an existent NMR-based methodology. Our results indicate that: (i) the averaged electrostatic-based tautomeric predictions for the imidazole ring of all histidines of Loligo vulgaris are dominated by the Nε2-H rather than the Nδ1-H form, although such preferences from the NMR-based methodology are not so well defined; (ii) the computed average absolute difference between the electrostatic- and the NMR-based tautomeric predictions among all six histidines vary among 0% to 17%; (iii) for the His showing the largest fraction of the neutral form (81%), the absolute difference between the NMR- and electrostatic-based computed tautomeric predictions is only 3%; and (iv) the tautomeric predictions for the imidazole ring of His computed with the NMR-based methodology are stable within a certain, well-defined, range of variations of a tautomer-related parameter.

Computational Evaluations of Charge Coupling and Hydrogen Bonding in the Active Site of a Family 7 Cellobiohydrolase

Solution pH and the pKa values of ionizable residues are critical factors known to influence enzyme catalysis, structural stability, and dynamical fluctuations. Presented here is an exhaustive computational study utilizing long time constant pH molecular dynamics, pH replica exchange simulations, and kinetic modeling to evaluate pH-dependent conformations, charge dynamics, residue pKa values, and the catalytic activity-pH profile for cellobiohydrolase Cel7B from Melanocarpus albomyces . The predicted pKa values support the role of Glu212 as the catalytic nucleophile and Glu217 as the acid-base residue. The presence of a charge-correlated active site and an extensive hydrogen bonding network is found to be critical in enabling favorable residue orientations for catalysis and shuttling excess protons around the active site. Clusters of amino acids are identified that act in concert to effectively modulate the optimal pH for catalysis while elevating the overall catalytic rate with respect to a noncoupled system. The work presented here demonstrates the complex and critical role of coupled ionizable residues to the proper functioning of cellobiohydrolase Cel7B, functionally related glycosyl hydrolases, and enzymes in general. The simulations also support the use of the CpHMD for the accurate prediction of residue pKa values and to evaluate the impact of pH on protein structure and charge dynamics.

Backbone Conformational Fluctuations as Determinants of pKa Values of Surface Residues in Proteins

The pKa values of surface ionizable residues in proteins are usually similar to the pKa values of ionizable residues in water. This is still difficult to reproduce using structure-based electrostatics calculations with static structures, which tend to exaggerate the shifts in pKa values because the magnitude of Coulomb effects is exaggerated and the balance between Coulomb and dehydration effects is not reproduced correctly. These problems can be minimized by using artificially high protein dielectric constants, but sometimes the discrepancy persists even when the protein interior is treated with the dielectric constant of water. This suggests that pKa values are affected by the conformational dynamics of the protein, which are not reflected in the crystal structure. Molecular dynamics or Monte Carlo simulations can be used to attempt to reproduce these dynamic effects implicitly, but there are no useful data for testing this approach directly. To examine the role of fluctuations of the backbone in determining pKa values, NMR spectroscopy was used to measure the pKa values of all 20 Asp and Glu residues in variants of staphylococcal nuclease with Gly substituted at select locations. These substitutions were intended to enhance backbone fluctuations without affecting the overall protein structure. Some Gly substitutions detectably shifted the pKa values of some carboxylic groups. Crystal structures of these variants showed no significant changes relative to the structure of the reference protein. Calculations with continuum methods using these crystal structures do not reproduce the measured shifts in pKa values. NMR spectroscopy studies suggest Gly substitutions affect the dynamics of the protein. Efforts are underway to better characterize these changes. Our results suggest that the high apparent polarizability of proteins might be due to subtle structural fluctuations that are difficult to reproduce computationally.

Empirical prediction of protein pKavalues with residue mutation

A fast, empirical method, Mut-pKa, is presented for predicting the pKa values of ionizable residues in proteins based on mutation. The method compares the effect of mutating each residue that may act as a hydrogen bond donor or acceptor for the ionizable residue. The energetic effect of each type of mutation, along with a desolvation measure and the overall background charge, is fit against pKa data for histidine and carboxyl residues. A total of 214 residues from 35 different proteins were used in the dataset. Using 11 parameters for each type of ionizable residue, a root mean squared error (RMSE) of 0.78 and 1.12 pH units were obtained for carboxyl and histidines residues, respectively, using leave one out cross validation (LOOCV). The results were particularly promising for buried residues, which had RMSE values of 0.99 and 1.13 for carboxyl and histidine residues, respectively. A number of desolvation measures were tested. The simplest measure, the number of atoms surrounding the residue, was found to work best. The effect of using dynamics was also studied using short molecular dynamics runs, followed by minimization of the structures. Mut-pKa has significantly fewer parameters than, but similar performance to, other empirical methods. Because of this and the LOOCV results, we believe the model is robust and that overfitting is not a problem.

Graphical analysis of pH-dependent properties of proteins predicted using PROPKA

BackgroundCharge 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.ResultsThe 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.ConclusionsThe 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.

光駆動プロトンポンプの四次元Ｘ線構造解析

Bacteriorhodopsin (bR), a membrane protein found in Halobacterium salinarum, contains retinal as chromophore and functions as a light-driven proton pump. We have carried out four-dimensional X-ray crystallographic studies of bR and its homologous proteins, to elucidate the proton pumping mechanism. A novel crystallization method, called the membrane fusion method, has been developed to prepare a 3D crystal that is stable over a wide pH range. This enabled us to investigate pH-induced as well as light-induced structural changes. Structural analyses of reaction intermediates revealed that water relocation, which affects the pKa values of ionizable residues in the proton channel, takes place in the early stage of the proton pumping cycle. On the basis of this observation, we hypothesized that bR is a water/proton anti-porter. Since some of internal cavities are highly conserved during the evolution, it is suggested that their morphological changes initiated by the retinal photo-isomerization play an important role for water relocation and proton tranlocation across the membrane.

Prediction and Rationalization of Protein pKa Values Using QM and QM/MM Methods

We describe the development and application of a computational method for the prediction and rationalization of pKa values of ionizable residues in proteins, based on ab initio quantum mechanics (QM) and the effective fragment potential (EFPs) method (a hybrid QM/MM method). The theoretical developments include (1) a covalent boundary method based on frozen localized orbitals, (2) divide-and-conquer methods for the ab initio computation of protein EFPs consisting of multipoles up to octupoles and dipole polarizability tensors, (3) a method for computing vibrational free energies for a localized molecular region, and (4) solutions of the polarized continuum model of bulk solvation equations for protein-sized systems. The QM-based pKa prediction method is one of the most accurate methods currently available and can be used in cases where other pKa prediction methods fail. Preliminary analysis of the computed results indicate that many pKa values (1) are primarily determined by hydrogen bonds rather than long-range charge-charge interactions and (2) are relatively insensitive to large-scale dynamical fluctuations of the protein structure.

Application of an integrated MOZYME+DFT method to pKa calculations for proteins

We propose an integrated MOZYME + DFT method for calculation of the pKa values of ionizable residues in a protein. The method is applied to two protein systems, bacteriorhodopsin (bR) and ribonuclease T1. It is shown that the present method reproduces the experimental pKa values of several targeted residues better than other conventional methods. Thus, it is available for pKa calculation for large molecular systems.

Dissection of the pH dependence of inhibitor binding energetics for an aspartic protease: direct measurement of the protonation states of the catalytic aspartic acid residues.

The catalytic activity and inhibitor binding energetics of enzymes are often pH-dependent properties. Aspartic proteases comprise an important class of enzyme targets for structure-based drug design. We have performed a complete thermodynamic study of pepstatin binding to plasmepsin II, an aspartic proteinase found in Plasmodium falciparum, using isothermal titration calorimetry and circular dichroism. Thermodynamic parameters (DeltaG, DeltaH, DeltaCp, and DeltaS) were measured as functions of both pH and temperature. In the pH range from 4.5 to 7.0, pepstatin binding is accompanied by proton transfer between the solvent and the complex. We used thermodynamic proton linkage theory to derive both the pH-independent binding energetics for pepstatin and the number and pKa values of ionizable residues whose pKa values change during ligand binding. These residues were identified as the two catalytic aspartates, with pKas of 6.5 and 3.0, and His 164, with a pKa of 7.5, based on the three-dimensional structure of the pepstatin-plasmepsin II complex. At pH 5.0, where the protease has optimum activity, the proton transfer process contributes almost 40% of the total binding free energy change and the total charge of the active-site aspartic acid residues is -1. These experimental results provide direct measurement for the protonation states of the catalytic aspartates in the presence of bound ligands. Comparison of the thermodynamic and structural data for pepstatin binding with human cathepsin D, a lysosomal aspartic protease that shares 35% sequence identity with plasmepsin II, suggests that the energetic differences between these two proteins are due to a higher interdomain flexibility in plasmepsin II.