Modeling of protein conformational fluctuations in pKa predictions

Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation

Charged and polar groups, through forming ion pairs, hydrogen bonds, and other less specific electrostatic interactions, impart important properties to proteins. Modulation of the charges on the amino acids, e.g., by pH and by phosphorylation and dephosphorylation, have significant effects such as protein denaturation and switch-like response of signal transduction networks. This review aims to present a unifying theme among the various effects of protein charges and polar groups. Simple models will be used to illustrate basic ideas about electrostatic interactions in proteins, and these ideas in turn will be used to elucidate the roles of electrostatic interactions in protein structure, folding, binding, condensation, and related biological functions. In particular, we will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins. Our hope is to capture both important historical developments and recent experimental and theoretical advances in quantifying electrostatic contributions of proteins.

Statistical Mechanical Model for pH-Induced Protein Folding: Application to Apomyoglobin

Despite the major role of pH in protein folding and stability, a quantitative understanding of the pH-induced protein folding mechanism remains elusive. Two conventional models, the Monod-Wyman-Changeux and Linderstrøm-Lang smeared charge models, respectively, have been used to analyze the formation/disruption of specific native structures and fluctuating non-native states. However, there are only a few models that can represent the overall kinetic events of folding/unfolding independent of the properties of relevant molecular species, which has hampered the efforts to systematically analyze pH-induced folding. Here, we constructed a statistical mechanical model that incorporates the protonation mechanism of conventional models along with a combined manual search and least-squares fitting procedure, which was used to investigate the folding of horse apomyoglobin over a wide pH range (2.2-6.7), with a time window ranging from ∼40 μs to ∼100 s, using continuous-/stopped-flow fluorescence at 8 °C. Quantitative analysis assuming a five-state sequential scheme indicated that (1) pH-induced folding/unfolding is represented by both specific binding and Coulombic interactions; (2) kinetic folding/unfolding intermediates share kinetic mechanisms with the equilibrium intermediate, indicating their equivalence; and (3) native-like properties are acquired successively during folding by intermediates and in transition states. This model could also be applied to a variety of association/dissociation processes.

pKa values in proteins determined by electrostatics applied to molecular dynamics trajectories

For a benchmark set of 194 measured pKa values in 13 proteins, electrostatic energy computations are performed in which pKa values are computed by solving the Poisson-Boltzmann equation. In contrast to the previous approach of Karlsberg(+) (KB(+)) that essentially used protein crystal structures with variations in their side chain conformations, the present approach (KB2(+)MD) uses protein conformations from four molecular dynamics (MD) simulations of 10 ns each. These MD simulations are performed with different specific but fixed protonation patterns, selected to sample the conformational space for the different protonation patterns faithfully. The root-mean-square deviation between computed and measured pKa values (pKa RMSD) is shown to be reduced from 1.17 pH units using KB(+) to 0.96 pH units using KB2(+)MD. The pKa RMSD can be further reduced to 0.79 pH units, if each conformation is energy-minimized with a dielectric constant of εmin = 4 prior to calculating the electrostatic energy. The electrostatic energy expressions upon which the computations are based have been reformulated such that they do not involve terms that mix protein and solvent environment contributions and no thermodynamic cycle is needed. As a consequence, conformations of the titratable residues can be treated independently in the protein and solvent environments. In addition, the energy terms used here avoid the so-called intrinsic pKa and can therefore be interpreted without reference to arbitrary protonation states and conformations.

In silico concurrent multisite pH titration in proteins

The concurrent proton binding at multiple sites in macromolecules such as proteins and nucleic acids is an important yet challenging problem in biochemistry. We develop an efficient generalized Hamiltonian approach to attack this issue. Based on the previously developed generalized-ensemble methods, an effective potential energy is constructed which combines the contributions of all (relevant) protonation states of the molecule. The effective potential preserves important phase regions of all states and, thus, allows efficient sampling of these regions in one simulation. The need for intermediate states in alchemical free energy simulations is greatly reduced. Free energy differences between different protonation states can be determined accurately and enable one to construct the grand canonical partition function. Therefore, the complicated concurrent multisite proton titration process of protein molecules can be satisfactorily simulated. Application of this method to the simulation of the pKa of Glu49, Asp50, and C-terminus of bovine pancreatic trypsin inhibitor shows reasonably good agreement with published experimental work. This method provides an unprecedented vivid picture of how different protonation states change their relative population upon pH titration. We believe that the method will be very useful in deciphering the molecular mechanism of pH-dependent biomolecular processes in terms of a detailed atomistic description.

Potential of mean force of water-proton bath and molecular dynamic simulation of proteins at constant pH

An advanced implicit solvent model of water-proton bath for protein simulations at constant pH is presented. The implicit water-proton bath model approximates the potential of mean force of a protein in water solvent in a presence of hydrogen ions. Accurate and fast computational implementation of the implicit water-proton bath model is developed using the continuum electrostatic Poisson equation model for calculation of ionization equilibrium and the corrected MSR6 generalized Born model for calculation of the electrostatic atom-atom interactions and forces. Molecular dynamics (MD) method for protein simulation in the potential of mean force of water-proton bath is developed and tested on three proteins. The model allows to run MD simulations of proteins at constant pH, to calculate pH-dependent properties and free energies of protein conformations. The obtained results indicate that the developed implicit model of water-proton bath provides an efficient way to study thermodynamics of biomolecular systems as a function of pH, pH-dependent ionization-conformation coupling, and proton transfer events.

Progress in the prediction of pKa values in proteins

The pK(a) -cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pK(a) values and protein electrostatics in general. The first round of the pK(a) -cooperative, which challenged computational labs to carry out blind predictions against pK(a) s experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6-10, 2009). This article serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here, we briefly outline existing approaches for pK(a) calculations, emphasizing methods that were used by the participants in calculating the blind pK(a) values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pK(a) calculations.

Chemical frustration in the protein folding landscape: grand canonical ensemble simulations of cytochrome c

A grand canonical formalism is developed to combine discrete simulations for chemically distinct species in equilibrium. Each simulation is based on a perturbed funneled landscape. The formalism is illustrated using the alkaline-induced transitions of cytochrome c as observed by FTIR spectroscopy and with various other experimental approaches. The grand canonical simulation method accounts for the acid/base chemistry of deprotonation, the inorganic chemistry of heme ligation and misligation, and the minimally frustrated folding energy landscape, thus elucidating the physics of protein folding involved with an acid/base titration of a protein. The formalism combines simulations for each of the relevant chemical species, varying by protonation and ligation states. In contrast to models based on perfectly funneled energy landscapes that contain only contacts found in the native structure, this study introduces "chemical frustration" from deprotonation and misligation that gives rise to many intermediates at alkaline pH. While the nature of these intermediates cannot be easily inferred from available experimental data, this study provides specific structural details of these intermediates, thus extending our understanding of how cytochrome c changes with an increase in pH. The results demonstrate the importance of chemical frustration for understanding biomolecular energy landscapes.

Predicting protein pK(a) by environment similarity

A statistical method to predict protein pK(a) has been developed by using the 3D structure of a protein and a database of 434 experimental protein pK(a) values. Each pK(a) in the database is associated with a fingerprint that describes the chemical environment around an ionizable residue. A computational tool, MoKaBio, has been developed to identify automatically ionizable residues in a protein, generate fingerprints that describe the chemical environment around such residues, and predict pK(a) from the experimental pK(a) values in the database by using a similarity metric. The method, which retrieved the pK(a) of 429 of the 434 ionizable sites in the database correctly, was crossvalidated by leave-one-out and yielded root mean square error (RMSE) = 0.95, a result that is superior to that obtained by using the Null Model (RMSE 1.07) and other well-established protein pK(a) prediction tools. This novel approach is suitable to rationalize protein pK(a) by comparing the region around the ionizable site with similar regions whose ionizable site pK(a) is known. The pK(a) of residues that have a unique environment not represented in the training set cannot be predicted accurately, however, the method offers the advantage of being trainable to increase its predictive power.

Electrostatic contributions to the stabilities of native proteins and amyloid complexes

The ability to predict electrostatic contributions to protein stability from structure has been a long-standing goal of experimentalists and theorists. With recent advances in NMR spectroscopy, it is possible to determine pK(a) values of all ionizable residues for at least small proteins, and to use the pK(a) shift between the folded and unfolded states to calculate the thermodynamic contribution from a change in charge to the change in free energy of unfolding. Results for globular proteins and for α-helical coiled coils show that electrostatic contributions to stability are typically small on an individual basis, particularly for surface-exposed residues. We discuss why NMR often suggests smaller electrostatic contributions to stability than X-ray crystallography or site-directed mutagenesis, and discuss the type of information needed to improve structure-based modeling of electrostatic forces. Large pK(a) shifts from random coil values are observed for proteins bound to negatively charged sodium dodecyl sulfate micelles. The results suggest that electrostatic interactions between proteins and charges on the surfaces of membrane lipid bilayers could be a major driving force in stabilizing the structures of peripheral membrane proteins. Finally, we discuss how changes in ionization states affect amyloid-β fibril formation and suggest that electrostatic repulsion may be a common destabilizing force in amyloid fibrils.

FAMBE-pH: a fast and accurate method to compute the total solvation free energies of proteins

A fast and accurate method to compute the total solvation free energies of proteins as a function of pH is presented. The method makes use of a combination of approaches, some of which have already appeared in the literature; (i) the Poisson equation is solved with an optimized fast adaptive multigrid boundary element (FAMBE) method; (ii) the electrostatic free energies of the ionizable sites are calculated for their neutral and charged states by using a detailed model of atomic charges; (iii) a set of optimal atomic radii is used to define a precise dielectric surface interface; (iv) a multilevel adaptive tessellation of this dielectric surface interface is achieved by using multisized boundary elements; and (v) 1:1 salt effects are included. The equilibrium proton binding/release is calculated with the Tanford-Schellman integral if the proteins contain more than approximately 20-25 ionizable groups; for a smaller number of ionizable groups, the ionization partition function is calculated directly. The FAMBE method is tested as a function of pH (FAMBE-pH) with three proteins, namely, bovine pancreatic trypsin inhibitor (BPTI), hen egg white lysozyme (HEWL), and bovine pancreatic ribonuclease A (RNaseA). The results are (a) the FAMBE-pH method reproduces the observed pK a's of the ionizable groups of these proteins within an average absolute value of 0.4 p K units and a maximum error of 1.2 p K units and (b) comparison of the calculated total pH-dependent solvation free energy for BPTI, between the exact calculation of the ionization partition function and the Tanford-Schellman integral method, shows agreement within 1.2 kcal/mol. These results indicate that calculation of total solvation free energies with the FAMBE-pH method can provide an accurate prediction of protein conformational stability at a given fixed pH and, if coupled with molecular mechanics or molecular dynamics methods, can also be used for more realistic studies of protein folding, unfolding, and dynamics, as a function of pH.

Structure-based pKa calculations using continuum electrostatics methods

Electrostatic free energy is useful for correlating structure with function in proteins in which ionizable groups play essential functional roles. To this end, the pK(a) values of ionizable groups must be known and their molecular determinants must be understood. Structure-based calculations of electrostatic energies and pK(a) values are necessary for this purpose. This unit describes protocols for pK(a) calculations with continuum electrostatics methods based on the numerical solution of the linearized Poisson-Boltzmann equation by the method of finite differences. Critical discussion of key parameters, approximations, and shortcomings of these methods is included. Two protocols are described for calculations with methods modified empirically to maximize agreement between measured and calculated pK(a) values. Applied judiciously, these methods can contribute useful and novel insight into properties of surface ionizable groups in proteins.

Electrostatic contribution to the thermodynamic and kinetic stability of the homotrimeric coiled coil Lpp-56: A computational study

The protein moiety of the Braun's E. coli outer membrane lipoprotein (Lpp-56) is an attractive object of biophysical investigation in several aspects. It is a homotrimeric, parallel coiled coil, a class of coiled coils whose stability and folding have been studied only occasionally. Lpp-56 possesses unique structural properties and exhibits extremely low rates of folding and unfolding. It is natural to ask how the specificity of the structure determines the extraordinary physical chemical properties of this protein. Recently, a seemingly controversial data on the stability and unfolding rate of Lpp-56 have been published (Dragan et al., Biochemistry 2004;43: 14891-14900; Bjelic et al., Biochemistry 2006;45:8931-8939). The unfolding rate constant measured using GdmCl as the denaturing agent, though extremely low, was substantially higher than that obtained on the basis of thermal unfolding. If this large difference arises from the effect of screening of electrostatic interactions induced by GdmCl, electrostatic interactions would appear to be an important factor determining the unusual properties of Lpp-56. We present here a computational analysis of the electrostatic properties of Lpp-56 combining molecular dynamics simulations and continuum pK calculations. The pH-dependence of the unfolding free energy is predicted in good agreement with the experimental data: the change in DeltaG between pH 3 and pH 7 is approximately 60 kJ mol(-1). The results suggest that the difference in the stability of the protein observed using different experimental methods is mainly because of the effect of the reduction of electrostatic interactions when the salt (GdmCl) concentration increases. We also find that the occupancy of the interhelical salt bridges is unusually high. We hypothesize that electrostatic interactions, and the interhelical salt bridges in particular, are an important factor determining the low unfolding rate of Lpp-56.

A statistical approach to the prediction of pK(a) values in proteins

We propose a simple model for the calculation of pK(a) values of ionizable residues in proteins. It is based on the premise that the pK(a) shift of ionizable residues is linearly correlated to the interaction between a particular residue and the local environment created by the surrounding residues. Despite its simplicity, the model displays good prediction performance. Under the sixfold cross test prediction over a data set of 405 experimental pK(a) values in 73 protein chains with known structures, the root-mean-square deviation (RMSD) between the experimental and calculated pK(a) was found to be 0.77. The accuracy of this model increases with increasing size of the data set: the RMSD is 0.609 for glutamate (the largest data set with 141 sites) and approximately 1 pH unit for lysine, with a data set containing 45 sites.

Electrostatic contributions to the stability of the GCN4 leucine zipper structure

Ion pairs are ubiquitous in X-ray structures of coiled coils, and mutagenesis of charged residues can result in large stability losses. By contrast, pK(a) values determined by NMR in solution often predict only small contributions to stability from charge interactions. To help reconcile these results we used triple-resonance NMR to determine pK(a) values for all groups that ionize between pH 1 and 13 in the 33 residue leucine zipper fragment, GCN4p. In addition to the native state we also determined comprehensive pK(a) values for two models of the GCN4p denatured state: the protein in 6 M urea, and unfolded peptide fragments of the protein in water. Only residues that form ion pairs in multiple X-ray structures of GCN4p gave large pK(a) differences between the native and denatured states. Moreover, electrostatic contributions to stability were not equivalent for oppositely charged partners in ion pairs, suggesting that the interactions between a charge and its environment are as important as those within the ion pair. The pH dependence of protein stability calculated from NMR-derived pK(a) values agreed with the stability profile measured from equilibrium urea-unfolding experiments as a function of pH. The stability profile was also reproduced with structure-based continuum electrostatic calculations, although contributions to stability were overestimated at the extremes of pH. We consider potential sources of errors in the calculations, and how pK(a) predictions could be improved. Our results show that although hydrophobic packing and hydrogen bonding have dominant roles, electrostatic interactions also make significant contributions to the stability of the coiled coil.

Intracellular pH sensors: design principles and functional significance

Changes in intracellular pH regulate many cell behaviors, including proliferation, migration, and transformation. However, our understanding of how physiological changes in pH affect protein conformations and macromolecular assemblies is limited. We present design principles, current modeling predictions, and examples of pH sensors or proteins that have activities or ligand-binding affinities that are regulated by changes in intracellular pH.

Review modeling the free solution and gel electrophoresis of biopolymers: The bead array-effective medium model

Free solution and gel electrophoresis is an extremely useful tool in the separation of biopolymers. The complex nature of biopolymers, coupled with the usefulness of electrophoretic methods, has stimulated the development of theoretical modeling over the last 30 years. In this work, these developments are first reviewed with emphasis on Boundary Element and bead methodologies that enable the investigator to design realistic models of biopolymers. In the present work, the bead methodology is generalized to include the presence of a gel through the Effective Medium model. The biopolymer is represented as a bead array. A peptide, for example, made up of N amino acids is modeled as 2N beads. Duplex DNA is modeled as a discrete wormlike chain consisting of touching beads. The technical details of the method are placed in three Appendices. To illustrate the accuracy and effectiveness of the approach, two applications are considered. Model studies on both the free solution mobility of 73 peptides ranging in size from 2 to 42 amino acids, and the mobility of short duplex DNA in dilute agarose gels are discussed.

Modeling electrostatic effects in proteins

Electrostatic energies provide what is perhaps the most effective tool for structure-function correlation of biological molecules. This review considers the current state of simulations of electrostatic energies in macromolecules as well as the early developments of this field. We focus on the relationship between microscopic and macroscopic models, considering the convergence problems of the microscopic models and the fact that the dielectric 'constants' in semimacroscopic models depend on the definition and the specific treatment. The advances and the challenges in the field are illustrated considering a wide range of functional properties including pK(a)'s, redox potentials, ion and proton channels, enzyme catalysis, ligand binding and protein stability. We conclude by pointing out that, despite the current problems and the significant misunderstandings in the field, there is an overall progress that should lead eventually to quantitative descriptions of electrostatic effects in proteins and thus to quantitative descriptions of the function of proteins.

Modeling the electrophoretic mobility and diffusion of weakly charged peptides

A bead model to determine the electrophoretic mobilities and translational diffusion constants of weakly charged peptides is developed that is based on a approximate structural model of peptides and is also grounded in electrohydrodynamic theory. A peptide made up of X amino acids is modeled as N=2X beads with 2 beads representing each amino acid in the chain. For the two beads representing a particular amino acid in a peptide, the radius of one bead is set to one-half the nearest neighbor Calpha-Calpha distance, and the radius of the other bead is chosen on the basis of the diffusion constant of the free amino acid. Peptide conformations, which are defined by a set of psi-phi dihedral angles, are randomly generated by using the transformation matrix approach of Flory (Flory, P. Statistical Mechanics of Chain Molecules; John Wiley: New York, 1969) and rejecting conformations which result in bead overlap. The mobility and diffusion constants are computed for each conformation and at least 100 independent conformations are examined for each peptide. In general, the mobility is found to depend only weakly on peptide conformation. Model and experimental mobilities are compared by examining the data of Janini and co-workers (Janini, G.; et al. J. Chromatogr. 1999, 848, 417-433). A total of 58 peptides consisting of from 2 to 39 amino acids are considered. The average relative error between experimental and model mobilities is found to be 1.0% and the rms relative error 7.7%. In specific cases, the discrepancy can be substantial and possible reasons for this are discussed. It should be emphasized that the input parameters of the peptide model are totally independent of experimental mobilities. It is hoped that the peptide model developed here will be useful in the prediction of peptide mobility as well as in using peptide mobilities to extract information about peptide structure, conformation, and charge. Finally, we show how simultaneous measurements of translational diffusion and mobility can be used to estimate peptide charge.

Analysing the pH-dependent properties of proteins using pKa calculations

The results of protein pKa calculations are routinely being analysed to understand the pH-dependence of protein characteristics such as stability and catalysis. Systems of functionally important titratable groups are identified from protein from pKa calculations, but the rationalisation of the behaviour of such systems is inherently problematic due to a lack of theoretical tools and methods. I present a number of novel methods for analysing the results of protein pKa calculations which have been embedded in a graphical user interface (pKaTool). In the present paper I present novel methods for assessing the reliability of protein pKa calculations and for analysing the roles of individual residues in determining active site pKa values and the pH-dependence of protein stability. The methods presented are freely available to academic researchers at http://enzyme.ucd.ie/Science/pKa/pKaTool .

Coupling between conformation and proton binding in proteins

Interest centers here on whether the use of a fixed charge distribution of a protein solute, or a treatment that considers proton-binding equilibria by solving the Poisson equation, is a better approach to discriminate native from non-native conformations of proteins. In this analysis of the charge distribution of 7 proteins, we estimate the solvation free energy contribution to the total free energy by exploring the 2(zeta) possible ionization states of the whole molecule, with zeta being the number of ionizable groups in the amino acid sequence, for every conformation in the ensembles of 7 proteins. As an additional consideration of the role of electrostatic interactions in determining the charge distribution of native folds, we carried out a comparison of alternative charge assignment models for the ionizable residues in a set of 21 native-like proteins. The results of this work indicate that (1) for 6 out of 7 proteins, estimation of solvent polarization based on the Generalized Born model with a fixed charge distribution provides the optimal trade-off between accuracy, with respect to the Poisson equation, and speed when compared to the accessible surface area model; for the seventh protein, consideration of all possible ionization states of the whole molecule appears to be crucial to discriminate the native from non-native conformations; (2) significant differences in the degree of ionization and hence the charge distribution for native folds are found between the different charge models examined; (3) the stability of the native state is determined by a delicate balance of all the energy components, and (4) conformational entropy, and hence the dynamics of folding, may play a crucial role for a successful ab initio protein folding prediction.

Electrokinetic transport of a spherical gel-layer model particle: inclusion of charge regulation and application to polystyrene sulfonate

An electrokinetic gel-layer model of a spherical, highly charged colloid particle developed previously [S. Allison, J. Colloid Interface Sci. 277 (2004) 248], is extended in several ways. The charge of the particle is assumed to arise from deprotonation of acidic groups that are present, in uniform concentration, over a portion (or all) of the gel layer. Free energy considerations coupled with Poisson-Boltzmann theory are used to estimate how the local electrostatic environment of a charged gel layer alters the local pK(a) of the acidic groups. This modulation of the charge of the colloidal particle, or "charge regulation," can be significant even for colloidal particles with strongly acidic groups at moderate pH if the ambient salt concentration is low. The methodology is applied to the viscosity and electrophoretic mobility data of a particular polystyrene sulfonate latex over a broad range of monovalent salt (NaCl) concentration [M.J. Garcia-Salinas, F.J. de las Nieves, Langmuir 16 (2000) 715]. The experimental data can be accounted for by a gel layer model that decreases in thickness, but does not vanish, as the salt concentration is increased. Viscosity data provides valuable information about the degree of solvation of the colloidal particle and the thickness of the gel layer. The mobility data is best explained by a model in which only the outermost portion of the gel layer is charged. Charge regulation is significant at a monovalent salt concentration of 3 x 10(-3) mol/l and increases as the salt concentration decreases.

Molecular mechanisms of pH-driven conformational transitions of proteins: Insights from continuum electrostatics calculations of acid unfolding

The acid unfolding of staphylococcal nuclease (SNase) is very cooperative (Whitten and García-Moreno, Biochemistry 2000;39:14292-14304). As many as seven hydrogen ions (H+) are bound preferentially by the acid-unfolded state relative to the native (N) state in the pH range 3.2-3.9. To investigate the mechanism of acid unfolding, structure-based pKa calculations were performed with a variety of continuum electrostatic methods. The calculations reproduced successfully the H+ binding properties of the N state between pH 5 and 9, but they systematically overestimated the number of H+ bound upon acid unfolding. The calculated pKa values of all carboxylic residues in the N state were more depressed than they should be. The discrepancy between the observed and the calculated H+ uptake upon acid unfolding was not improved by using high protein dielectric constants, structures relaxed with molecular dynamics, or other empirical modifications implemented previously by others to maximize agreement between measured and calculated pKa values. This suggests an important role for conformational fluctuations of the backbone as important determinants of pKa values of carboxylic groups. Because no global or subglobal conformational changes have been observed previously for SNase under acidic conditions above the acid-unfolding region, these fluctuations must be local. The acid unfolding of SNase does not seem to involve the disruption of the N state by accruement of intramolecular repulsive interactions, nor the protonation of key ion paired carboxylic residues. It is more consistent with modest contributions from many H+ binding groups, with an important role for local conformational fluctuations in the coupling between H+ binding and the global structural transition.

Improved pKa calculations through flexibility based sampling of a water-dominated interaction scheme

Ionizable groups play critical roles in biological processes. Computation of pK(a)s is complicated by model approximations and multiple conformations. Calculated and experimental pK(a)s are compared for relatively inflexible active-site side chains, to develop an empirical model for hydration entropy changes upon charge burial. The modification is found to be generally small, but large for cysteine, consistent with small molecule ionization data and with partial charge distributions in ionized and neutral forms. The hydration model predicts significant entropic contributions for ionizable residue burial, demonstrated for components in the pyruvate dehydrogenase complex. Conformational relaxation in a pH-titration is estimated with a mean-field assessment of maximal side chain solvent accessibility. All ionizable residues interact within a low protein dielectric finite difference (FD) scheme, and more flexible groups also access water-mediated Debye-Hückel (DH) interactions. The DH method tends to match overall pH-dependent stability, while FD can be more accurate for active-site groups. Tolerance for side chain rotamer packing is varied, defining access to DH interactions, and the best fit with experimental pK(a)s obtained. The new (FD/DH) method provides a fast computational framework for making the distinction between buried and solvent-accessible groups that has been qualitatively apparent from previous work, and pK(a) calculations are significantly improved for a mixed set of ionizable residues. Its effectiveness is also demonstrated with computation of the pH-dependence of electrostatic energy, recovering favorable contributions to folded state stability and, in relation to structural genomics, with substantial improvement (reduction of false positives) in active-site identification by electrostatic strain.

The triplex-hairpin transition in cytosine-rich DNA

We present a theoretical study of the self-complementary single-stranded 30-mer d(TC*TTC*C*TTTTCCTTCTC*CCGAGAAGGTTTT) (PDB ID: 1b4y) that was designed to form an intramolecular triplex by folding back twice on itself. At neutral pH the molecule exists in a duplex hairpin conformation, whereas at acidic pH the cytosines labeled by an asterisk (*) are protonated, forming Hoogsteen hydrogen bonds with guanine of a GC Watson-Crick basepair to generate a triplex. As a first step in an investigation of the energetics of the triplex-hairpin transition, we applied the Bashford-Karplus multiple site model of protonation to calculate the titration curves for the two conformations. Based on these data, a two-state model is used to study the equilibrium properties of transition. Although this model properly describes the thermodynamics of the protonation-deprotonation steps that drive the folding-unfolding of the oligomer, it cannot provide insight into the time-dependent mechanism of the process. A series of molecular dynamics simulations using the ff94 force field of the AMBER 6.0 package was therefore run to explore the dynamics of the folding/unfolding pathway. The molecular dynamics method was combined with Poisson-Boltzmann calculations to determine when a change in protonation state was warranted during a trajectory. This revealed a sequence of elementary protonation steps during the folding/unfolding transition and suggests a strong coupling between ionization and folding in cytosine-rich triple-helical triplexes.

The determinants of carboxyl pKa values in turkey ovomucoid third domain

A computational methodology for protein pK(a) predictions, based on ab initio quantum mechanical treatment of part of the protein and linear Poisson-Boltzmann equation treatment of the bulk solvent, is presented. The method is used to predict and interpret the pK(a) values of the five carboxyl residues (Asp7, Glu10, Glu19, Asp27, and Glu43) in the serine protease inhibitor turkey ovomucoid third domain. All the predicted pK(a) values are within 0.5 pH units of experiment, with a root-mean-square deviation of 0.31 pH units. We show that the decreased pK(a) values observed for some of the residues are primarily due to hydrogen bonds to the carboxyl oxygens. Hydrogen bonds involving amide protons are shown to be particularly important, and the effect of hydrogen bonding is shown to be nonadditive. Hydrophobic effects are also shown to be important in raising the pK(a). Interactions with charged residues are shown to have relatively little effect on the carboxyl pK(a) values in this protein, in general agreement with experiment.

Specific ion effects: Role of salt and buffer in protonation of cytochrome c

Changes in background salt and buffer are known to influence the properties of proteins. The reasons have remained obscure. The challenge posed by many such problems is this. Can physical chemistry contribute any predictive quantitative insights to what is in effect the simplest macromolecular solution behavior? Or must all remain specific? Our thesis is that it can. For definiteness we consider here as an illustrative example: surface pH and protonation equilibria of cytochrome c. We demonstrate an important role for ionic dispersion forces, missing from previous theoretical treatments. Unlike charge interactions these are different for each ionic species, and act between a protein and both salt and buffer ions. The charge of proteins depends not only on pH, ionic charge, and salt concentration. Taking ionic dispersion forces into account goes some way towards explaining the dependence on ionic species. We demonstrate why the addition of buffer can have profound effects, including reversal of the salt dependence of the protein charge.

Constant-pH molecular dynamics study of protonation-structure relationship in a heptapeptide derived from ovomucoid third domain

Molecular dynamics (MD) simulations with implicit solvent and variable protonation states for titratable residues at constant pH are performed for a short peptide derived from ovomucoid third domain (OMTKY3), acetyl-Ser-Asp-Asn-Lys-Thr-Tyr-Gly-amide (residues 26-32 of OMTKY3). Nuclear magnetic resonance (NMR) measurements indicate that the pK(a) for Asp is 3.6. However, if the charge on Lys is neutralized by acetylation, then the pK(a) for Asp is 4.0. These pK(a)'s, and therefore the Asp-Lys interaction, are insensitive to changes in ionic strength. The constant-pH MD simulations for both variants of the heptapeptide yield Asp pK(a) values that are 0.6-0.9 pH units greater than experimental values, but the difference between the variants that is observed in the NMR experiments is reproduced much better. Moreover, the simulations suggest that Asp-Lys interactions do not dominate the behavior of this heptapeptide, even for normal Lys residue where there is a possibility of forming a salt bridge between negatively charged Asp and positively charged Lys. This is consistent with the experimentally observed independence of Asp pK(a) values with respect to ionic strength. Another important result of the simulations with variable protonation states is that they lead to ensembles of the heptapeptide structures that are different from those derived from simulations with fixed protonation states. It should be stressed that these results are for structures generated entirely by computer simulations without any restrictions imposed by experimental data.

Prediction of secondary ionization of the phosphate group in phosphotyrosine peptides

A computational approach, based on a continuum molecular electrostatics model, for the calculation of the pK(a) values of secondary ionization of the phosphate group in phenyl phosphate derivatives is described. The method uses the ESP atomic charges of the mono-anionic and di-anionic forms of the ionizable phosphate group, computed with the use of the density functional method, and applies a new concept of the model group, being the reference state for the pK(a) calculations. Both conformational flexibility and tautomeric degrees of freedom are taken into account in the calculations. The method was parameterized using experimentally available pK(a) values of four derivatives of phenyl phosphates, and phosphotyrosine. Subsequently this parameterization was used to predict pK(a) of the phosphate group in a short peptide Gly-Gly-Tyr(P)-Ala, and in a longer peptide consisting of 12 residues, the latter in water, and in a complex with a protein-phospholipase. The agreement between the computed and the experimental pK(a) values is better than +/-0.3 pH units for the optimized solute dielectric constant of 11-13. This approach is promising and its extension to other phospho-amino acids is in progress.

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.

Residual charge interactions in unfolded staphylococcal nuclease can be explained by the Gaussian-chain model

The discrepancy of the pH dependence of the unfolding free energy for staphylococcal nuclease from what is expected from an idealized model for the unfolded state is accounted for by the recently developed Gaussian-chain model. Residual electrostatic effects in the unfolded state are attributed to nonspecific interactions dominated by charges close along the sequence. The dominance of nonspecific local interactions appears to be supported by some experimental evidence.

Langevin dynamics of proteins at constant pH

An application of the Langevin dynamics algorithm for simulation of protein conformational equilibria at constant pH is presented. The algorithm is used to compute average protonation of titratable groups in ovomucoid third domain, as functions of pH, resulting in data, basically equivalent to the pH dependencies of chemical shifts obtained from multidimensional nuclear magnetic resonance (NMR) spectroscopy, for the protein titratable residues. The pK(a) values obtained from the simulation are in reasonable agreement with experimental data. Possible improvements of this methodology, using achievements from other fields of mesoscopic biomolecular simulations, are also discussed.

The Poisson-Boltzmann equation for biomolecular electrostatics: a tool for structural biology

Electrostatics plays a fundamental role in virtually all processes involving biomolecules in solution. The Poisson-Boltzmann equation constitutes one of the most fundamental approaches to treat electrostatic effects in solution. The theoretical basis of the Poisson-Boltzmann equation is reviewed and a wide range of applications is presented, including the computation of the electrostatic potential at the solvent-accessible molecular surface, the computation of encounter rates between molecules in solution, the computation of the free energy of association and its salt dependence, the study of pKa shifts and the combination with classical molecular mechanics and dynamics. Theoretical results may be used for rationalizing or predicting experimental results, or for suggesting working hypotheses. An ever-increasing body of successful applications proves that the Poisson-Boltzmann equation is a useful tool for structural biology and complementary to other established experimental and theoretical methodologies.

Combining conformational flexibility and continuum electrostatics for calculating pK(a)s in proteins

Protein stability and function relies on residues being in their appropriate ionization states at physiological pH. In situ residue pK(a)s also provides a sensitive measure of the local protein environment. Multiconformation continuum electrostatics (MCCE) combines continuum electrostatics and molecular mechanics force fields in Monte Carlo sampling to simultaneously calculate side chain ionization and conformation. The response of protein to charges is incorporated both in the protein dielectric constant (epsilon(prot)) of four and by explicit conformational changes. The pK(a) of 166 residues in 12 proteins was determined. The root mean square error is 0.83 pH units, and >90% have errors of <1 pH units whereas only 3% have errors >2 pH units. Similar results are found with crystal and solution structures, showing that the method's explicit conformational sampling reduces sensitivity to the initial structure. The outcome also changes little with protein dielectric constant (epsilon(prot) 4-20). Multiconformation continuum electrostatics titrations show coupling of conformational flexibility and changes in ionization state. Examples are provided where ionizable side chain position (protein G), Asn orientation (lysozyme), His tautomer distribution (RNase A), and phosphate ion binding (RNase A and H) change with pH. Disallowing these motions changes the calculated pK(a).

Experimental pK(a) values of buried residues: analysis with continuum methods and role of water penetration

Lys-66 and Glu-66, buried in the hydrophobic interior of staphylococcal nuclease by mutagenesis, titrate with pK(a) values of 5.7 and 8.8, respectively (Dwyer et al., Biophys. J. 79:1610-1620; García-Moreno E. et al., Biophys. Chem. 64:211-224). Continuum calculations with static structures reproduced the pK(a) values when the protein interior was treated with a dielectric constant (epsilon(in)) of 10. This high apparent polarizability can be rationalized in the case of Glu-66 in terms of internal water molecules, visible in crystallographic structures, hydrogen bonded to Glu-66. The water molecules are absent in structures with Lys-66; the high polarizability cannot be reconciled with the hydrophobic environment surrounding Lys-66. Equilibrium thermodynamic experiments showed that the Lys-66 mutant remained folded and native-like after ionization of the buried lysine. The high polarizability must therefore reflect water penetration, minor local structural rearrangement, or both. When in pK(a) calculations with continuum methods, the internal water molecules were treated explicitly, and allowed to relax in the field of the buried charged group, the pK(a) values of buried residues were reproduced with epsilon(in) in the range 4-5. The calculations show that internal waters can modulate pK(a) values of buried residues effectively, and they support the hypothesis that the buried Lys-66 is in contact with internal waters even though these are not seen crystallographically. When only the one or two innermost water molecules were treated explicitly, epsilon(in) of 5-7 reproduced the pK(a) values. These values of epsilon(in) > 4 imply that some conformational reorganization occurs concomitant with the ionization of the buried groups.