Native-state conformational dynamics of GART: a regulatory pH-dependent coil-helix transition examined by electrostatic calculations

pH Effects and Cooperativity among Key Titratable Residues for Escherichia coli Glycinamide Ribonucleotide Transformylase

Human glycinamide ribonucleotide transformylase (GAR Tfase) is a regulatory enzyme in the de novo purine biosynthesis pathway that has been extensively studied as an anticancer target. To some extent, inhibition of GAR Tfase selectively targets cancer cells over normal cells and inhibits purine formation and DNA replication. In this study, we investigated E. coli GAR Tfase, which shares high sequence similarity with the human GAR Tfase, and most functional residues are conserved. Herein, we aim to predict the pH-activity curve through a computational approach. We carried out pH-replica exchange molecular dynamics (pH-REMD) simulations to investigate pH-dependent functions such as structural changes, ligand binding, and catalytic activity. To compute the pH-activity curve, we identified the catalytic residues in specific protonation states, referred to as the catalytic competent protonation states (CCPS), which maintain the structure, keep ligands bound, and facilitate catalysis. Our computed population of CCPS with respect to pH matches well with the experimental pH-activity curve. To compute the microscopic pK_a values in the catalytically active conformation, we devised a thermodynamic model that considers the coupling between protonation states of CCPS residues and conformational states. These results allow us to correctly identify the general acid and base catalysts and interpret the pH-activity curve at an atomistic level.

Anthrax toxin-induced rupture of artificial lipid bilayer membranes

We demonstrate experimentally that anthrax toxin complexes rupture artificial lipid bilayer membranes when isolated from the blood of infected animals. When the solution pH is temporally acidified to mimic that process in endosomes, recombinant anthrax toxin forms an irreversibly bound complex, which also destabilizes membranes. The results suggest an alternative mechanism for the translocation of anthrax toxin into the cytoplasm.

Automated computational framework for the analysis of electrostatic similarities of proteins

Charge plays an important role in protein-protein interactions. In the case of excessively charged proteins, their electrostatic potentials contribute to the processes of recognition and binding with other proteins or ligands. We present an automated computational framework for determining the contribution of each charged amino acid to the electrostatic properties of proteins, at atomic resolution level. This framework involves computational alanine scans, calculation of Poisson-Boltzmann electrostatic potentials, calculation of electrostatic similarity distances (ESDs), hierarchical clustering analysis of ESDs, calculation of solvation free energies of association, and visualization of the spatial distributions of electrostatic potentials. The framework is useful to classify families of mutants with similar electrostatic properties and to compare them with the parent proteins in the complex. The alanine scan mutants introduce perturbations in the local electrostatic properties of the proteins and aim in delineating the contribution of each mutated amino acid in the spatial distribution of electrostatic potential, and in biological function when electrostatics is a dominant contributing factor in protein-protein interactions. The framework can be used to design new proteins with tailored electrostatic properties, such as immune system regulators, inhibitors, and vaccines, and in guiding experimental studies. We present an example for the interaction of the immune system protein C3d (the d-fragment of complement protein C3) with its receptor CR2, and we discuss our data in view of a binding site controversy.

Fast empirical pKa prediction by Ewald summation

pK(a) calculations for macromolecules are normally performed by solving the Poisson-Boltzmann equation, accounting for the different dielectric constants of solvent and solute, as well as the ionic strength. Despite the large number of successful applications, there are some situations where the current algorithms are not suitable: (1) large scale, high-throughput analysis which requires calculations to be completed within a fraction of a second, e.g. when permanently monitoring pK(a) shifts during a molecular dynamics simulation; (2) prediction of pK(a)s in periodic boundaries, e.g. when reconstructing entire protein crystal unit cells from PDB files, including the correct protonation patterns at experimental pH. Such in silico crystals are needed by 'self-parameterizing' molecular dynamics force fields like YASARA YAMBER, that optimize their parameters while energy-minimizing high-resolution protein crystals. To address both problems, we define an empirical equation that expresses the pK(a) as a function of electrostatic potential, hydrogen bonds and accessible surface area. The electrostatic potential is evaluated by Ewald summation, which captures periodic crystal environments and the uncertainty in atom positions using Gaussian charge densities. The empirical proportionality constants are derived from 217 experimentally determined pK(a)s, and despite its simplicity, this pK(a) calculation method reaches a high overall jack-knifed accuracy, and is fast enough to be used during a molecular dynamics simulation. A reliable null-model to judge pK(a) prediction accuracies is also presented.

Proton binding to proteins: a free-energy component analysis using a dielectric continuum model

Proton binding plays a critical role in protein structure and function. We report pK(a) calculations for three aspartates in two proteins, using a linear response approach, as well as a "standard" Poisson-Boltzmann approach. Averaging over conformations from the two endpoints of the proton-binding reaction, the protein's atomic degrees of freedom are explicitly modeled. Treating macroscopically the protein's electronic polarizability and the solvent, a meaningful model is obtained, without adjustable parameters. It reproduces qualitatively the electrostatic potentials, proton-binding free energies, Marcus reorganization free energies, and pK(a) shifts from explicit solvent molecular dynamics simulations, and the pK(a) shifts from experiment. For thioredoxin Asp-26, which has a large pK(a) upshift, we correctly capture the balance between unfavorable carboxylate desolvation and favorable interactions with a nearby lysine; similarly for RNase A Asp-14, which has a large pK(a) downshift. For the unshifted thioredoxin Asp-20, desolvation by the protein cavity is overestimated by 2.9 pK(a) units; several effects could explain this. "Standard" Poisson-Boltzmann methods sidestep this problem by using a large, ad hoc protein dielectric; but protein charge-charge interactions are then incorrectly downscaled, giving an unbalanced description of the reaction and a large error for the shifted pK(a) values of Asp-26 and Asp-14.

The electrostatic nature of C3d-complement receptor 2 association

The association of complement component C3d with B or T cell complement receptor 2 (CR2 or CD21) is a link between innate and adaptive immunity. It has been recognized in experimental studies that the C3d-CR2 association is pH- and ionic strength-dependent. This led us to perform electrostatic calculations to obtain a theoretical understanding of the mechanism of C3d-CR2 association. We used the crystallographic structures of human free C3d, free CR2 (short consensus repeat (SCR)1-2), and the C3d-CR2(SCR1-2) complex, and continuum solvent representation, to obtain a detailed atomic-level picture of the components of the two molecules that contribute to association. Based on the calculation of electrostatic potentials for the free and bound species and apparent pK(a) values for each ionizable residue, we show that C3d-CR2(SCR1-2) recognition is electrostatic in nature and involves not only the association interface, but also the whole molecules. Our results are in qualitative agreement with experimental data that measured the ionic strength and pH dependence of C3d-CR2 association. Also, our results for the native molecules and a number of theoretical mutants of C3d explain experimental mutagenesis studies of amino acid replacements away from the association interface that modulate binding of iC3b with full-length CR2. Finally, we discuss the packing of the two SCR domains. Overall, our data provide global and site-specific explanations of the physical causes that underlie the ionic strength dependence of C3d-CR2 association in a unified model that accounts for all experimental data, some of which were previously thought to be contradictory.

The pH dependence of stability of the activation helix and the catalytic site of GART

We have predicted the free energy of unfolding for the pH-dependent helix-coil transition of the activation helix of GART using continuum electrostatic calculations and structural modeling. We have assigned the contributions of each element of secondary structure and of each ionizable residue, within and in the vicinity of the activation helix, to the stability of several fragments of GART that participate in the formation of the catalytic site. We demonstrate that the interaction of His121-His132 contributes 2.2 kcal/mol to the ionization free energy between pH 0 and approximately 6. We also show that the ionization state of a network of five histidines, His108, His119, His121, His132 and His137, and two aspartic acids Asp141 and Asp144, contributes approximately 12 kcal/mol to the stability of the catalytic site of GART, out of a total stability of 16 kcal/mol of the whole enzyme. These interactions are important for the formation of the catalytic site of GART.

On the evaluation and optimization of protein X-ray structures for pKa calculations

The calculation of the physical properties of a protein from its X-ray structure is of importance in virtually every aspect of modern biology. Although computational algorithms have been developed for calculating everything from the dynamics of a protein to its binding specificity, only limited information is available on the ability of these methods to give accurate results when used with a particular X-ray structure. We examine the ability of a pKa calculation algorithm to predict the proton-donating residue in the catalytic mechanism of hen egg white lysozyme. We examine the correlation between the ability of the pKa calculation method to obtain the correct result and the overall characteristics of 41 X-ray structures such as crystallization conditions, resolution, and the output of structure validation software. We furthermore examine the ability of energy minimizations (EM), molecular dynamics (MD) simulations, and structure-perturbation methods to optimize the X-ray structures such that these give correct results with the pKa calculation algorithm. We propose a set of criteria for identifying the proton donor in a catalytic mechanism, and demonstrate that the application of these criteria give highly accurate prediction results when using unmodified X-ray structures. More specifically, we are able to successfully identify the proton donor in 85% of the X-ray structures when excluding structures with crystal contacts near the active site. Neither the use of the overall characteristics of the X-ray structures nor the optimization of the structure by EM, MD, or other methods improves the results of the pKa calculation algorithm. We discuss these results and their implications for the design of structure-based energy calculation algorithms in general.

Unfolding proteins under external forces: a solvable model under the self-consistent pair contact probability approximation

We extend a model of Micheletti et al. [Phys. Rev. Lett. 87, 088102 (2001)]] used to study protein con-formations to the case in which there is an external force field. Under the self-consistent pair contact probability approximation, this residue-level resolution model can still be solved under pulling forces. We implement the algorithm using heterogeneous parameters and study the force-induced unfolding of a helical segment from the protein transformylase and of the beta-stranded domains from the protein titin. The results are qualitatively consistent with the results from more expensive, atomistic dynamics simulation. Despite the mean-field-like approach, we observed a sharp and cooperative unfolding transition.

Proton transfer dynamics of GART: the pH-dependent catalytic mechanism examined by electrostatic calculations

The enzyme glycinamide ribonucleotide transformylase (GART) catalyzes the transfer of a formyl group from formyl tetrahydrofolate (fTHF) to glycinamide ribonucleotide (GAR), a process that is pH-dependent with pK(a) of approximately 8. Experimental studies of pH-rate profiles of wild-type and site-directed mutants of GART have led to the proposal that His108, Asp144, and GAR are involved in catalysis, with His108 being an acid catalyst, while forming a salt bridge with Asp144, and GAR being a nucleophile to attack the formyl group of fTHF. This model implied a protonated histidine with pK(a) of 9.7 and a neutral GAR with pK(a) of 6.8. These proposed unusual pK(a)s have led us to investigate the electrostatic environment of the active site of GART. We have used Poisson-Boltzmann-based electrostatic methods to calculate the pK(a)s of all ionizable groups, using the crystallographic structure of a ternary complex of GART involving the pseudosubstrate 5-deaza-5,6,7,8-THF (5dTHF) and substrate GAR. Theoretical mutation and deletion analogs have been constructed to elucidate pairwise electrostatic interactions between key ionizable sites within the catalytic site. Also, a construct of a more realistic catalytic site including a reconstructed pseudocofactor with an attached formyl group, in an environment with optimal local van der Waals interactions (locally minimized) that imitates closely the catalytic reactants, has been used for pK(a) calculations. Strong electrostatic coupling among catalytic residues His108, Asp144, and substrate GAR was observed, which is extremely sensitive to the initial protonation and imidazole ring flip state of His108 and small structural changes. We show that a proton can be exchanged between GAR and His108, depending on their relative geometry and their distance to Asp144, and when the proton is attached on His108, catalysis could be possible. Using the formylated locally minimized construct of GART, a high pK(a) for His108 was calculated, indicating a protonated histidine, and a low pK(a) for GAR(NH(2)) was calculated, indicating that GAR is in neutral form. Our results are in qualitative agreement with the current mechanistic picture of the catalytic process of GART deduced from the experimental data, but they do not reproduce the absolute magnitude of the pK(a)s extracted from fits of k(cat)-pH profiles, possibly because the static time-averaged crystallographic structure does not describe adequately the dynamic nature of the catalytic site during binding and catalysis. In addition, a strong effect on the pK(a) of GAR(NH(2)) is produced by the theoretical mutations of His108Ala and Asp144Ala, which is not in agreement with the observed insensitivity of the pK(a) of GAR(NH(2)) modeled from the experimental data using similar mutations. Finally, we show that important three-way electrostatic interactions between highly conserved His137, with His108 and Asp144, are responsible for stabilizing the electrostatic microenvironment of the catalytic site. In conclusion, our data suggest that further detailed computational and experimental work is necessary.