Chapter 9 Analyzing Enzymatic pH Activity Profiles and Protein Titration Curves Using Structure-Based pKa Calculations and Titration Curve Fitting. Computer Methods, Part A. Elsevier; 2009. pp. 233-58. [DOI: 10.1016/s0076-6879(08)03809-3]

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.

Native vs Denatured: An in Depth Investigation of Charge State and Isotope Distributions

New tools and techniques have dramatically accelerated the field of structural biology over the past several decades. One potent and relatively new technique that is now being utilized by an increasing number of laboratories is the combination of so-called "native" electrospray ionization (ESI) with mass spectrometry (MS) for the characterization of proteins and their noncovalent complexes. However, native ESI-MS produces species at increasingly higher m/z with increasing molecular weight, leading to substantial differences when compared to traditional mass spectrometric approaches using denaturing ESI solutions. Herein, these differences are explored both theoretically and experimentally to understand the role that charge state and isotopic distributions have on signal-to-noise (S/N) as a function of complex molecular weight and how the reduced collisional cross sections of proteins electrosprayed under native solution conditions can lead to improved data quality in image current mass analyzers, such as Orbitrap and FT-ICR. Quantifying ion signal differences under native and denatured conditions revealed enhanced S/N and a more gradual decay in S/N with increasing mass under native conditions. Charge state and isotopic S/N models, supported by experimental results, indicate that analysis of proteins under native conditions at 100 kDa will be 17 times more sensitive than analysis under denatured conditions at the same mass. Higher masses produce even larger sensitivity gains. Furthermore, reduced cross sections under native conditions lead to lower levels of ion decay within an Orbitrap scan event over long transient acquisition times, enabling isotopic resolution of species with molecular weights well in excess of those typically resolved under denatured conditions.

PKAD: a database of experimentally measured pKa values of ionizable groups in proteins

Ionizable residues play key roles in many biological phenomena including protein folding, enzyme catalysis and binding. We present PKAD, a database of experimentally measured pKas of protein residues reported in the literature or taken from existing databases. The database contains pKa data for 1350 residues in 157 wild-type proteins and for 232 residues in 45 mutant proteins. Most of these values are for Asp, Glu, His and Lys amino acids. The database is available as downloadable file as well as a web server (http://compbio.clemson.edu/pkad). The PKAD database can be used as a benchmarking source for development and improvement of pKa's prediction methods. The web server provides additional information taken from the corresponding structures and amino acid sequences, which allows for easy search and grouping of the experimental pKas according to various biophysical characteristics, amino acid type and others.

Constant-pH MD Simulations Portray the Protonation and Structural Behavior of Four Decapeptides Designed to Coordinate Cu(2+)

The cyclic decapeptide C-Asp, containing one Asp residue and three His residues, was designed by Fragoso et al. (Chem. Eur. J. 2013, 19, 2076) to bind Cu(2+) exclusively through the side chain groups and mimic copper coordination in metalloproteins. A variant of the cyclodecapeptide where Asp is substituted by Asn (C-Asn) has also been synthesized in addition to the linear ("open") counterparts of both forms (O-Asp and O-Asn), testing the importance of cyclization and the presence of Asp in Cu(2+) coordination (Chem. Eur. J. 2013, 19, 2076; Dalton Trans. 2013, 42, 6182). All peptides formed a major species at neutral pH that was able to coordinate Cu(2+) exclusively through the neutral imidazole groups and the Asp side chain, when present, with C-Asp being the most effective. A detailed description of the protonation behavior of each histidine could help understanding the coordination species being formed in the pH range and eventually further optimizing the peptide's design. However, the standard current methods (NMR titrations) are not very suited for proximal groups titrating in the same pH range. In this work, we used the stochastic titration constant-pH molecular dynamics method to calculate the protonation curves and pKa of each titrable residue in the four decapeptides, in the absence of Cu(2+) ions. The global protonation curves obtained in our simulations are in very good agreement with the existing potentiometric titration curves. The histidines are titrating very closely, and the Asp forms abundant salt bridges with the basic residues, displaying an unusually low pKa value. In addition, we could observe that the four peptides are very unstructured in the absence of copper, and not even the cyclic forms exhibit a significant β-sheet, unlike what could be expected from the presence of β-turn inducer units in this type of scaffold.

Site-specific protonation kinetics of acidic side chains in proteins determined by pH-dependent carboxyl (13)C NMR relaxation

Proton-transfer dynamics plays a critical role in many biochemical processes, such as proton pumping across membranes and enzyme catalysis. The large majority of enzymes utilize acid-base catalysis and proton-transfer mechanisms, where the rates of proton transfer can be rate limiting for the overall reaction. However, measurement of proton-exchange kinetics for individual side-chain carboxyl groups in proteins has been achieved in only a handful of cases, which typically have involved comparative analysis of mutant proteins in the context of reaction network modeling. Here we describe an approach to determine site-specific protonation and deprotonation rate constants (kon and koff, respectively) of carboxyl side chains, based on (13)C NMR relaxation measurements as a function of pH. We validated the method using an extensively studied model system, the B1 domain of protein G, for which we measured rate constants koff in the range (0.1-3) × 10(6) s(-1) and kon in the range (0.6-300) × 10(9) M(-1) s(-1), which correspond to acid-base equilibrium dissociation constants (Ka) in excellent agreement with previous results determined by chemical shift titrations. Our results further reveal a linear free-energy relationship between log kon and pKa, which provides information on the free-energy landscape of the protonation reaction, showing that the variability among residues in these parameters arises primarily from the extent of charge stabilization of the deprotonated state by the protein environment. We find that side-chain carboxyls with extreme values of koff or kon are involved in hydrogen bonding, thus providing a mechanistic explanation for the observed stabilization of the protonated or deprotonated state.

Electrostatic contribution of surface charge residues to the stability of a thermophilic protein: benchmarking experimental and predicted pKa values

Optimization of the surface charges is a promising strategy for increasing thermostability of proteins. Electrostatic contribution of ionizable groups to the protein stability can be estimated from the differences between the pKa values in the folded and unfolded states of a protein. Using this pKa-shift approach, we experimentally measured the electrostatic contribution of all aspartate and glutamate residues to the stability of a thermophilic ribosomal protein L30e from Thermococcus celer. The pKa values in the unfolded state were found to be similar to model compound pKas. The pKa values in both the folded and unfolded states obtained at 298 and 333 K were similar, suggesting that electrostatic contribution of ionizable groups to the protein stability were insensitive to temperature changes. The experimental pKa values for the L30e protein in the folded state were used as a benchmark to test the robustness of pKa prediction by various computational methods such as H++, MCCE, MEAD, pKD, PropKa, and UHBD. Although the predicted pKa values were affected by crystal contacts that may alter the side-chain conformation of surface charged residues, most computational methods performed well, with correlation coefficients between experimental and calculated pKa values ranging from 0.49 to 0.91 (p<0.01). The changes in protein stability derived from the experimental pKa-shift approach correlate well (r = 0.81) with those obtained from stability measurements of charge-to-alanine substituted variants of the L30e protein. Our results demonstrate that the knowledge of the pKa values in the folded state provides sufficient rationale for the redesign of protein surface charges leading to improved protein stability.

Dissecting electrostatic interactions in Bacillus circulans xylanase through NMR-monitored pH titrations

NMR-monitored pH titration curves of proteins provide a rich source of structural and electrostatic information. Although relatively straightforward to measure, interpreting pH-dependent chemical shift changes to obtain site-specific acid dissociation constants (pK (A) values) is challenging. In order to analyze the biphasic titrations exhibited by the side chain (13)C(γ) nuclei of the nucleophilic Glu78 and general acid/base Glu172 in Bacillus circulans xylanase, we have revisited the formalism for the ionization equilibria of two coupled acidic residues. In general, fitting NMR-monitored pH titration curves for such a system will only yield the two macroscopic pK (A) values that reflect the combined effects of both deprotonation reactions. However, through the use of mutations complemented with ionic strength-dependent measurements, we are able to extract the four microscopic pK (Ai) values governing the branched acid/base equilibria of Glu78 and Glu172 in BcX. These data, confirmed through theoretical calculations, help explain the pH-dependent mechanism of this model GH11 xylanase by demonstrating that the kinetically determined pK (A) values and hence catalytic roles of these two residues result from their electrostatic coupling.

Electrostatics in proteins and protein-ligand complexes

Accurate computational methods for predicting electrostatic energies are of major importance for our understanding of protein energetics in general for computer-aided drug design as well as for the design of novel biocatalysts and protein therapeutics. Electrostatic energies are of particular importance in such applications as virtual screening, drug design and protein-protein docking due to the high charge density of protein ligands and small-molecule drugs, and the frequent protonation state changes observed when drugs bind to their protein targets. Therefore, the development of a reliable and fast algorithm for the evaluation of electrostatic free energies, as an important contributor to the overall protein energy function, has been the focus for many scientists over the past three decades. In this review we describe the current state-of-the-art in modeling electrostatic effects in proteins and protein-ligand complexes. We focus mainly on the merits and drawbacks of the continuum methodology, and speculate on future directions in refining algorithms for calculating electrostatic energies in proteins using experimental data.

Calculating pKa values in the cAMP-dependent protein kinase: the effect of conformational change and ligand binding

The conformational change observed upon ligand binding and phosphorylation for the cAMP-dependent protein kinase (protein kinase A-PKA) is of high importance for the regulation of its activity. We calculate pKa values and net charges for 18 3D structures of PKA in various conformations and liganded states to examine the role of electrostatics in ligand binding and activation. We find that the conformational change of PKA takes place without any significant net proton uptake/release at all pH values, thus indicating that PKA has evolved to reduce any pH-dependent barriers to the conformational motion. We furthermore find that the binding of ligands induces large changes in the net charge of PKA at most pH values, but significantly, we find that the net charge difference at physiological pH is close to zero, thus indicating that the active-site pKa values have been preorganized for substrate binding. We are unable to unequivocally resolve the identity of the groups responsible for determining the pH-activity profile of PKA but speculate that the titration of Lys 168 or the titration of ATP itself could be responsible for the loss of activity at high pH values. Finally, we examine the effect of point mutations on the pKa values of the PKA catalytic residues and find these to be relatively insensitive to both noncharge-altering and charge-altering mutations.

Evolution of the isoelectric point of mammalian proteins as a consequence of indels and adaptive evolution

Although important shifts in the isoelectric point of prokaryotic proteins, mainly due to adaptation to environmental pH, have been widely reported, such studies have not covered mammalian proteins, where pH changes may relate to changes in subcellular or tissue compartmentalization. We explored the isoelectric point of the proteome of 13 mammalian species. We detected proteins that have shifted their pI the most among 13 mammalian species, and investigated if these differences reflect adaptations of the orthologous proteins to different conditions. We find that proteins exhibiting a high isoelectric point change are enriched in certain GO terms, including immune defense, and mitochondrial proteins. We show that the shift in pI between orthologous proteins is not strongly associated with the overall rate of protein evolution, nor with protein length. Our results reveal that insertions/deletions are the main reason behind the shift of pI. However, for some proteins we find evidence of selection shifting the pI of the protein through amino acid replacement. Finally, we argue that shifts in pI might relate to the gain of additional activities, such as new interacting partners, in one ortholog as opposed to the other, and may potentially relate to functional differences between mammals.

Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations

Site-specific pK(a) values measured by NMR spectroscopy provide essential information on protein electrostatics, the pH-dependence of protein structure, dynamics and function, and constitute an important benchmark for protein pK(a) calculation algorithms. Titration curves can be measured by tracking the NMR chemical shifts of several reporter nuclei versus sample pH. However, careful analysis of these curves is needed to extract residue-specific pK(a) values since pH-dependent chemical shift changes can arise from many sources, including through-bond inductive effects, through-space electric field effects, and conformational changes. We have re-measured titration curves for all carboxylates and His 15 in Hen Egg White Lysozyme (HEWL) by recording the pH-dependent chemical shifts of all backbone amide nitrogens and protons, Asp/Glu side chain protons and carboxyl carbons, and imidazole protonated carbons and protons in this protein. We extracted pK(a) values from the resulting titration curves using standard fitting methods, and compared these values to each other, and with those measured previously by ¹H NMR (Bartik et al., Biophys J 1994;66:1180–1184). This analysis gives insights into the true accuracy associated with experimentally measured pK(a) values. We find that apparent pK(a) values frequently differ by 0.5–1.0 units depending upon the nuclei monitored, and that larger differences occasionally can be observed. The variation in measured pK(a) values, which reflects the difficulty in fitting and assigning pH-dependent chemical shifts to specific ionization equilibria, has significant implications for the experimental procedures used for measuring protein pK(a) values, for the benchmarking of protein pK(a) calculation algorithms, and for the understanding of protein electrostatics in general.

Computational approaches to identifying and characterizing protein binding sites for ligand design

Given the three-dimensional structure of a protein, how can one find the sites where other molecules might bind to it? Do these sites have the properties necessary for high affinity binding? Is this protein a suitable target for drug design? Here, we discuss recent developments in computational methods to address these and related questions. Geometric methods to identify pockets on protein surfaces have been developed over many years but, with new algorithms, their performance is still improving. Simulation methods show promise in accounting for protein conformational variability to identify transient pockets but lack the ease of use of many of the (rigid) shape-based tools. Sequence and structure comparison approaches are benefiting from the constantly increasing size of sequence and structure databases. Energetic methods can aid identification and characterization of binding pockets, and have undergone recent improvements in the treatment of solvation and hydrophobicity. The "druggability" of a binding site is still difficult to predict with an automated procedure. The methodologies available for this purpose range from simple shape and hydrophobicity scores to computationally demanding free energy simulations.

Titration_DB: storage and analysis of NMR-monitored protein pH titration curves

NMR-monitored pH titration experiments are routinely used to measure site-specific protein pKa values. Accurate experimental pKa values are essential in dissecting enzyme catalysis, in studying the pH-dependence of protein stability and ligand binding, in benchmarking pKa prediction algorithms, and ultimately in understanding electrostatic effects in proteins. However, due to the complex ways in which pH-dependent electrostatic and structural changes manifest themselves in NMR spectra, reported apparent pKa values are often dependent on the way that NMR pH-titration curves are analyzed. It is therefore important to retain the raw NMR spectroscopic data to allow for documentation and possible re-interpretation. We have constructed a database of primary NMR pH-titration data, which is accessible via a web interface. Here, we report statistics of the database contents and analyze the data with a global perspective to provide guidelines on best practice for fitting NMR titration curves. Titration_DB is available at http://enzyme.ucd.ie/Titration_DB. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Molecular acidity: A quantitative conceptual density functional theory description

Accurate predictions of molecular acidity using ab initio and density functional approaches are still a daunting task. Using electronic and reactivity properties, one can quantitatively estimate pKa values of acids. In a recent paper [S. B. Liu and L. G. Pedersen, J. Phys. Chem. A 113, 3648 (2009)], we employed the molecular electrostatic potential (MEP) on the nucleus and the sum of valence natural atomic orbital (NAO) energies for the purpose. In this work, we reformulate these relationships on the basis of conceptual density functional theory and compare the results with those from the thermodynamic cycle method. We show that MEP and NAO properties of the dissociating proton of an acid should satisfy the same relationships with experimental pKa data. We employ 27 main groups and first to third row transition metal-water complexes as illustrative examples to numerically verify the validity of these strong linear correlations. Results also show that the accuracy of our approach and that of the conventional method through the thermodynamic cycle are statistically similar.