Charges in the hydrophobic interior of proteins

Molecular Dynamics Driven Design of pH-Stabilized Mutants of MNEI, a Sweet Protein

MNEI is a single chain derivative of monellin, a plant protein that can interact with the human sweet taste receptor, being therefore perceived as sweet. This unusual physiological activity makes MNEI a potential template for the design of new sugar replacers for the food and beverage industry. Unfortunately, applications of MNEI have been so far limited by its intrinsic sensitivity to some pH and temperature conditions, which could occur in industrial processes. Changes in physical parameters can, in fact, lead to irreversible protein denaturation, as well as aggregation and precipitation. It has been previously shown that the correlation between pH and stability in MNEI derives from the presence of a single glutamic residue in a hydrophobic pocket of the protein. We have used molecular dynamics to study the consequences, at the atomic level, of the protonation state of such residue and have identified the network of intramolecular interactions responsible for MNEI stability at acidic pH. Based on this information, we have designed a pH-independent, stabilized mutant of MNEI and confirmed its increased stability by both molecular modeling and experimental techniques.

Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins

Proteins change their charge state through protonation and redox reactions as well as through binding charged ligands. The free energy of these reactions is dominated by solvation and electrostatic energies and modulated by protein conformational relaxation in response to the ionization state changes. Although computational methods for calculating these interactions can provide very powerful tools for predicting protein charge states, they include several critical approximations of which users should be aware. This chapter discusses the strengths, weaknesses, and approximations of popular computational methods for predicting charge states and understanding the underlying electrostatic interactions. The goal of this chapter is to inform users about applications and potential caveats of these methods as well as outline directions for future theoretical and computational research.

MTH1 Substrate Recognition--An Example of Specific Promiscuity

MTH1 (NUDT1) is an oncologic target involved in the prevention of DNA damage. We investigate the way MTH1 recognises its substrates and present substrate-bound structures of MTH1 for 8-oxo-dGTP and 8-oxo-rATP as examples of novel strong and weak binding substrate motifs. Investigation of a small set of purine-like fragments using 2D NMR resulted in identification of a fragment with weak potency. The protein-ligand X-Ray structure of this fragment provides insight into the role of water molecules in substrate selectivity. Wider fragment screening by NMR resulted in three new protein structures exhibiting alternative binding configurations to the key Asp-Asp recognition element of the protein. These inhibitor binding modes demonstrate that MTH1 employs an intricate yet promiscuous mechanism of substrate anchoring through its Asp-Asp pharmacophore. The structures suggest that water-mediated interactions convey selectivity towards oxidized substrates over their non-oxidised counterparts, in particular by stabilization of a water molecule in a hydrophobic environment through hydrogen bonding. These findings may be useful in the design of inhibitors of MTH1.

Photoinduced Electron Transfer Elicits a Change in the Static Dielectric Constant of a de Novo Designed Protein

We provide a direct measure of the change in effective dielectric constant (ε(S)) within a protein matrix after a photoinduced electron transfer (ET) reaction. A linked donor-bridge-acceptor molecule, PZn-Ph-NDI, consisting of a (porphinato)Zn donor (PZn), a phenyl bridge (Ph), and a naphthalene diimide acceptor (NDI), is shown to be a "meter" to indicate protein dielectric environment. We calibrated PZn-Ph-NDI ET dynamics as a function of solvent dielectric, and computationally de novo designed a protein SCPZnI3 to bind PZn-Ph-NDI in its interior. Mapping the protein ET dynamics onto the calibrated ET catalogue shows that SCPZnI3 undergoes a switch in the effective dielectric constant following photoinduced ET, from ε(S) ≈ 8 to ε(S) ≈ 3.

Regulation of Ras Paralog Thermostability by Networks of Buried Ionizable Groups

Protein folding is governed by a variety of molecular forces including hydrophobic and ionic interactions. Less is known about the molecular determinants of protein stability. Here we used a recently developed computer algorithm (pHinder) to investigate the relationship between buried charge and thermostability. Our analysis revealed that charge networks in the protein core are generally smaller in thermophilic organisms as compared to mesophilic organisms. To experimentally test whether core network size influences protein thermostability, we purified 18 paralogous Ras superfamily GTPases from yeast and determined their melting temperatures (Tm, or temperature at which 50% of the protein is unfolded). This analysis revealed a wide range of Tm values (35-63 °C) that correlated significantly (R = 0.87) with core network size. These results suggest that thermostability depends in part on the arrangement of ionizable side chains within a protein core. An improved capacity to predict protein thermostability may be useful for selecting the best candidates for protein crystallography, the development of protein-based therapeutics, as well as for industrial enzyme applications.

Engineering of isoamylase: improvement of protein stability and catalytic efficiency through semi-rational design

Isoamylase catalyzes the hydrolysis of α-1,6-glycosidic linkages in glycogen, amylopectin and α/β-limit dextrins. A semi-rational design strategy was performed to improve catalytic properties of isoamylase from Bacillus lentus. Three residues in vicinity of the essential residues, Arg505, Asn513, and Gly608, were chosen as the mutation sites and were substituted by Ala, Pro, Glu, and Lys, respectively. Thermal stability of the mutant R505P and acidic stability of the mutant R505E were enhanced. The k  cat  /K  m values of the mutant G608V have been promoted by 49 %, and the specific activity increased by 33 %. This work provides an effective strategy for improving the catalytic activity and stability of isoamylase, and the results obtained here may be useful for the improvement of catalytic properties of other α/β barrel enzymes.

Conformational Dynamics and Binding Free Energies of Inhibitors of BACE-1: From the Perspective of Protonation Equilibria

BACE-1 is the β-secretase responsible for the initial amyloidogenesis in Alzheimer’s disease, catalyzing hydrolytic cleavage of substrate in a pH-sensitive manner. The catalytic mechanism of BACE-1 requires water-mediated proton transfer from aspartyl dyad to the substrate, as well as structural flexibility in the flap region. Thus, the coupling of protonation and conformational equilibria is essential to a full in silico characterization of BACE-1. In this work, we perform constant pH replica exchange molecular dynamics simulations on both apo BACE-1 and five BACE-1-inhibitor complexes to examine the effect of pH on dynamics and inhibitor binding properties of BACE-1. In our simulations, we find that solution pH controls the conformational flexibility of apo BACE-1, whereas bound inhibitors largely limit the motions of the holo enzyme at all levels of pH. The microscopic pK_a values of titratable residues in BACE-1 including its aspartyl dyad are computed and compared between apo and inhibitor-bound states. Changes in protonation between the apo and holo forms suggest a thermodynamic linkage between binding of inhibitors and protons localized at the dyad. Utilizing our recently developed computational protocol applying the binding polynomial formalism to the constant pH molecular dynamics (CpHMD) framework, we are able to obtain the pH-dependent binding free energy profiles for various BACE-1-inhibitor complexes. Our results highlight the importance of correctly addressing the binding-induced protonation changes in protein-ligand systems where binding accompanies a net proton transfer. This work comprises the first application of our CpHMD-based free energy computational method to protein-ligand complexes and illustrates the value of CpHMD as an all-purpose tool for obtaining pH-dependent dynamics and binding free energies of biological systems.

Formation of insoluble amyloid plaques in the vascular and hippocampal areas of the brain characterizes Alzheimer’s disease, a devastating neurodegenerative disorder causing dementia. Site-specific hydrolytic catalysis of β-secretase, or BACE-1, is responsible for production of oligomerative amyloid β-peptide. As the catalytic activity of BACE-1 is pH-dependent and its structural dynamics are intrinsic to the catalysis, we examine the dependence of dynamics of BACE-1 on solution pH and its implications on the catalytic mechanism of BACE-1. Also, we highlight the importance of accurate description of protonation states of the titratable groups in computer-aided drug discovery targeting BACE-1. We hope the understanding of pH dependence of the dynamics and inhibitor binding properties of BACE-1 will aid the structure-based inhibitor design efforts against Alzheimer’s disease.

Thermodynamics of Ion Pair Formations Between Charged Poly(Amino Acid)s

Electrostatic interactions between the positively and negatively charged amino acids in proteins play an important role in macromolecular stability, binding, and recognition. Numerous amino acids in proteins are ionizable and may exist in negatively (e.g., Glu, Asp, Cys, Tyr) or positively (e.g., Arg, Lys, His, Orn) charged form dependent on pH and their pKas. In this work, isothermal titration calorimetry was used to determine the average standard values of thermodynamic parameters (the Gibbs free energy, enthalpy, entropy, and the heat capacity) of interaction between the positively charged amino acid homopolymers (polyarginine, polylysine, and polyornithine) and the negatively charged homopolymers (polyaspartic and polyglutamic acids). These values are of potential use in the computational models of interacting proteins and other biological macromolecules. The study showed that oppositely charged poly(amino acid)s bound each other with the stoichiometry of one positive to one negative charge. Arginine bound to the negatively charged amino acids with exothermic enthalpy and higher affinity than lysine. This result also suggests that positive charges in proteins should not be considered entirely equivalent if carried by lysine or arginine. The difference in binding energy of arginine and lysine association with the negatively charged amino acids was attributed to the enthalpy of the second ionic hydrogen bond formation between the guanidine and carboxylic groups. Despite the favorable enthalpic contribution, all such ion pair formation reactions were largely entropy-driven. Consistent with previously observed ionic interactions, the positive heat capacity was always observed during the amino acid ion pair formation.

Selectivity of Protein Ion Channels and the Role of Buried Charges. Analytical Solutions, Numerical Calculations, and MD Simulations

The preference of large protein ion channels for cations or anions is mainly determined by the electrostatic interactions of mobile ions with charged residues of the protein. Here we discuss the widely spread paradigm that the charges determining the channel selectivity are only those that can be considered solvent-accessible because of their location near the permeation pathways of ions and water molecules. Theoretical predictions for the electric potential and average ion densities inside the pore are presented using several approaches of increasing resolution: from analytical and numerical solutions of electrostatic equations in a model channel up to all-atom molecular dynamics simulations and continuum electrostatic calculations performed in a particular biological channel, the bacterial porin OmpF. The results highlight the role of protein dieletric properties and the importance of the initial choice of the residue ionization states in the understanding of the molecular basis of large channel selectivity irrespective of the level of resolution of the computational approach used.

Characterization of the Dielectric Constant in the Trichoderma reesei Cel7B Active Site

An attempt is made to evaluate the dielectric constant of the Trichoderma reesei Cel7B active site. Through kinetic measurements, the pKa value of the catalytic acid E201 is determined. Mutations (away from E201) with net charge changes are introduced to perturb the E201 pKa. It is shown that the mutation with a +1 charge change (including G225R, G230R, and A335R) decreases the pKa of E201, whereas the mutation with a -1 charge change (including Q149E, A222D, G225D, and G230D) increases the pKa. This effect is consistent with the electrostatic interaction between the changed charge and the E201 side chain. The fitting of the experimental data yields an apparent dielectric constant of 25-80. Molecular dynamics simulations with explicit water molecules indicate that the high solvent accessibility of the active site contributes largely to the high dielectric constant. ONIOM calculations show that high dielectric constant benefits the catalysis through decreasing the energy of the transition state relative to that of the enzyme substrate complex.

Evolutionary, Comparative and Functional Analyses of the Brassinosteroid Receptor Gene, BRI1, in Wheat and Its Relation to Other Plant Genomes

Brassinosteroids (BRs) are plant hormones, fundamental for the growth and development of plants. A trans-membrane protein receptor kinase, Brassinosteroid-Insensitive 1 (BRI1), is known to interact with BRs and be directly involved in plant development. This study investigates the structural organization of BRI1 orthologs in several taxa, with a specific interest in Triticum aestivum. True orthologs of Arabidopsis thaliana BRI1 (AtBRI1) from seven-plant species showed sequence identity ranging from 54% to 95% at the protein level. All gene sequences lacked introns, leading to speculation that post-transcriptional processing in TaBRI1 is similar to AtBRI1. Based on in silico analysis, a single copy of BRI1 was present in each of the three wheat genomes on the long arm of chromosome 3. Domain structure of BRI1 orthologs among different taxa showed multiple leucine rich repeats (LRRs), an island domain (ID), a juxtamembrane/transmembrane domain (JTMD), a catalytic kinase domain (KD), C and N-Terminal domains. The KD showed the highest level of conservation while the LRRs and JTMD were most variable. Phosphorylation of residues in the juxtamembrane domain, known to be involved in the activation of the KD, is conserved in TaBRI1. While TaBRI1 has well-defined differences in the ID and LRR domains, many residues involved in ligand binding are conserved. The activation loop present in the KD showed 100% conservation in all taxa. Despite residue differences, hydrophobicity was conserved in the BR binding pocket across taxa, suggesting that function may not differ as drastically as residue identity may suggest. Predicted 3D structure of AtBRI1 and TaBRI1 showed a conserved super helical assembly, a feature essential in protein-protein interactions. An unrooted phylogram showed TaBRI1 in the monocot clade to be distinct from that of dicots. New insight in the structure and functions of BRI1 may help in targeting BR pathway for crop improvement.

Buried ionizable networks are an ancient hallmark of G protein-coupled receptor activation

Seven-transmembrane receptors (7TMRs) have evolved in prokaryotes and eukaryotes over hundreds of millions of years. Comparative structural analysis suggests that these receptors may share a remote evolutionary origin, despite their lack of sequence similarity. Here we used structure-based computations to compare 221 7TMRs from all domains of life. Unexpectedly, we discovered that these receptors contain spatially conserved networks of buried ionizable groups. In microbial 7TMRs these networks are used to pump ions across the cell membrane in response to light. In animal 7TMRs, which include light- and ligand-activated G protein-coupled receptors (GPCRs), homologous networks were found to be characteristic of activated receptor conformations. These networks are likely relevant to receptor function because they connect the ligand-binding pocket of the receptor to the nucleotide-binding pocket of the G protein. We propose that agonist and G protein binding facilitate the formation of these electrostatic networks and promote important structural rearrangements such as the displacement of transmembrane helix-6. We anticipate that robust classification of activated GPCR structures will aid the identification of ligands that target activated GPCR structural states.

Arginine: Its pKa value revisited

Using complementary approaches of potentiometry and NMR spectroscopy, we have determined that the equilibrium acid dissociation constant (pKa value) of the arginine guanidinium group is 13.8 ± 0.1. This is substantially higher than that of ∼ 12 often used in structure-based electrostatics calculations and cited in biochemistry textbooks. The revised intrinsic pKa value helps explains why arginine side chains in proteins are always predominantly charged, even at pH values as great as 10. The high pKa value also reinforces the observation that arginine side chains are invariably protonated under physiological conditions of near neutral pH. This occurs even when the guanidinium moiety is buried in a hydrophobic micro-environment, such as that inside a protein or a lipid membrane, thought to be incompatible with the presence of a charged group.

Frequent side chain methyl carbon-oxygen hydrogen bonding in proteins revealed by computational and stereochemical analysis of neutron structures

The propensity of backbone Cα atoms to engage in carbon-oxygen (CH · · · O) hydrogen bonding is well-appreciated in protein structure, but side chain CH · · · O hydrogen bonding remains largely uncharacterized. The extent to which side chain methyl groups in proteins participate in CH · · · O hydrogen bonding is examined through a survey of neutron crystal structures, quantum chemistry calculations, and molecular dynamics simulations. Using these approaches, methyl groups were observed to form stabilizing CH · · · O hydrogen bonds within protein structure that are maintained through protein dynamics and participate in correlated motion. Collectively, these findings illustrate that side chain methyl CH · · · O hydrogen bonding contributes to the energetics of protein structure and folding.

Carboxyl-peptide plane stacking is important for stabilization of buried E305 of Trichoderma reesei Cel5A

Hydrogen bonds or salt bridges are usually formed to stabilize the buried ionizable residues. However, such interactions do not exist for two buried residues D271 and E305 of Trichoderma reesei Cel5A, an endoglucanase. Mutating D271 to alanine or leucine improves the enzyme thermostability quantified by the temperature T50 due to the elimination of the desolvation penalty of the aspartic acid. However, the same mutations for E305 decrease the enzyme thermostability. Free energy calculations based on the molecular dynamics simulation predict the thermostability of D271A, D271L, and E305A (compared to WT) in line with the experimental observation but overestimate the thermostability of E305L. Quantum mechanical calculations suggest that the carboxyl-peptide plane stacking interactions occurring to E305 but not D271 are important for the carboxyl group stabilization. For the protonated carboxyl group, the interaction energy can be as much as about -4 kcal/mol for parallel stacking and about -7 kcal/mol for T-shaped stacking. For the deprotonated carboxyl group, the largest interaction energies for parallel stacking and T-shaped stacking are comparable, about -7 kcal/mol. The solvation effect generally weakens the interaction, especially for the charged system. A search of the carboxyl-peptide plane stacking in the PDB databank indicates that parallel stacking but not T-shaped stacking is quite common, and the most probable distance between the two stacking fragments is close to the value predicted by the QM calculations. This work highlights the potential role of carboxyl amide π-π stacking in the stabilization of aspartic acid and glutamic acid in proteins.

Crystallographic snapshot of an arrested intermediate in the biomimetic activation of CO2

The design of molecular catalysts that mimic the behavior of enzymes is a topical field of activity in emerging technologies, and can lead to an improved understanding of biological systems. Herein, we report how the bulky arms of the cations in [(n C4 H9 )4 N](+) [HCO3 ](-) give rise to a host scaffold that emulates the substrate binding sites in carbonic anhydrase enzymes, affording a unique glimpse of an arrested intermediate in the base-mediated binding and activation of CO2 .

Photoswitchable red fluorescent protein with a large Stokes shift

A subclass of fluorescent proteins (FPs), large Stokes shift (LSS) FP, are characterized by increased spread between excitation and emission maxima. We report a photoswitchable variant of a red FP with an LSS, PSLSSmKate, which initially exhibits excitation and emission at 445 and 622 nm, but violet irradiation photoswitches PSLSSmKate into a common red form with excitation and emission at 573 and 621 nm. We characterize spectral, photophysical, and biochemical properties of PSLSSmKate in vitro and in mammalian cells and determine its crystal structure in the LSS form. Mass spectrometry, mutagenesis, and spectroscopy of PSLSSmKate allow us to propose molecular mechanisms for the LSS, pH dependence, and light-induced chromophore transformation. We demonstrate the applicability of PSLSSmKate to superresolution photoactivated localization microscopy and protein dynamics in live cells. Given its promising properties, we expect that PSLSSmKate-like phenotype will be further used for photoactivatable imaging and tracking multiple populations of intracellular objects.

Molecular simulation of water and hydration effects in different environments: challenges and developments for DFTB based models

We discuss the description of water and hydration effects that employs an approximate density functional theory, DFTB3, in either a full QM or QM/MM framework. The goal is to explore, with the current formulation of DFTB3, the performance of this method for treating water in different chemical environments, the magnitude and nature of changes required to improve its performance, and factors that dictate its applicability to reactions in the condensed phase in a QM/MM framework. A relatively minor change (on the scale of kBT) in the O-H repulsive potential is observed to substantially improve the structural properties of bulk water under ambient conditions; modest improvements are also seen in dynamic properties of bulk water. This simple change also improves the description of protonated water clusters, a solvated proton, and to a more limited degree, a solvated hydroxide. By comparing results from DFTB3 models that differ in the description of water, we confirm that proton transfer energetics are adequately described by the standard DFTB3/3OB model for meaningful mechanistic analyses. For QM/MM applications, a robust parametrization of QM-MM interactions requires an explicit consideration of condensed phase properties, for which an efficient sampling technique was developed recently and is reviewed here. The discussions help make clear the value and limitations of DFTB3 based simulations, as well as the developments needed to further improve the accuracy and transferability of the methodology.

Protein apparent dielectric constant and its temperature dependence from remote chemical shift effects

A NMR protocol is introduced that permits accurate measurement of minute, remote chemical shift perturbations (CSPs), caused by a mutation-induced change in the electric field. Using protein GB3 as a model system, ¹H^N CSPs in K19A and K19E mutants can be fitted to small changes in the electric field at distal sites in the protein using the Buckingham equation, yielding an apparent dielectric constant ε_a of 8.6 ± 0.8 at 298 K. These CSPs, and their derived ε_a value, scale strongly with temperature. For example, CSPs at 313 K are about ∼30% smaller than those at 278 K, corresponding to an effective ε_a value of about 7.3 at 278 K and 10.5 at 313 K. Molecular dynamics simulations in explicit solvent indicate that solvent water makes a significant contribution to ε_a.

Protein charge ladders reveal that the net charge of ALS-linked superoxide dismutase can be different in sign and magnitude from predicted values

This article utilized "protein charge ladders"-chemical derivatives of proteins with similar structure, but systematically altered net charge-to quantify how missense mutations that cause amyotrophic lateral sclerosis (ALS) affect the net negative charge (Z) of superoxide dismutase-1 (SOD1) as a function of subcellular pH and Zn(2+) stoichiometry. Capillary electrophoresis revealed that the net charge of ALS-variant SOD1 can be different in sign and in magnitude-by up to 7.4 units per dimer at lysosomal pH-than values predicted from standard pKa values of amino acids and formal oxidation states of metal ions. At pH 7.4, the G85R, D90A, and G93R substitutions diminished the net negative charge of dimeric SOD1 by up to +2.29 units more than predicted; E100K lowered net charge by less than predicted. The binding of a single Zn(2+) to mutant SOD1 lowered its net charge by an additional +2.33 ± 0.01 to +3.18 ± 0.02 units, however, each protein regulated net charge when binding a second, third, or fourth Zn(2+) (ΔZ < 0.44 ± 0.07 per additional Zn(2+) ). Both metalated and apo-SOD1 regulated net charge across subcellular pH, without inverting from negative to positive at the theoretical pI. Differential scanning calorimetry, hydrogen-deuterium exchange, and inductively coupled plasma mass spectrometry confirmed that the structure, stability, and metal content of mutant proteins were not significantly affected by lysine acetylation. Measured values of net charge should be used when correlating the biophysical properties of a specific ALS-variant SOD1 protein with its observed aggregation propensity or clinical phenotype.

Structural and thermodynamic consequences of burial of an artificial ion pair in the hydrophobic interior of a protein

An artificial charge pair buried in the hydrophobic core of staphylococcal nuclease was engineered by making the V23E and L36K substitutions. Buried individually, Glu-23 and Lys-36 both titrate with pKa values near 7. When buried together their pKa values appear to be normal. The ionizable moieties of the buried Glu-Lys pair are 2.6 Å apart. The interaction between them at pH 7 is worth 5 kcal/mol. Despite this strong interaction, the buried Glu-Lys pair destabilizes the protein significantly because the apparent Coulomb interaction is sufficient to offset the dehydration of only one of the two buried charges. Save for minor reorganization of dipoles and water penetration consistent with the relatively high dielectric constant reported by the buried ion pair, there is no evidence that the presence of two charges in the hydrophobic interior of the protein induces any significant structural reorganization. The successful engineering of an artificial ion pair in a highly hydrophobic environment suggests that buried Glu-Lys pairs in dehydrated environments can be charged and that it is possible to engineer charge clusters that loosely resemble catalytic sites in a scaffold protein with high thermodynamic stability, without the need for specialized structural adaptations.

Constant pH Molecular Dynamics in Explicit Solvent with Enveloping Distribution Sampling and Hamiltonian Exchange

We present a new computational approach for constant pH simulations in explicit solvent based on the combination of the enveloping distribution sampling (EDS) and Hamiltonian replica exchange (HREX) methods. Unlike constant pH methods based on variable and continuous charge models, our method is based on discrete protonation states. EDS generates a hybrid Hamiltonian of different protonation states. A smoothness parameter s is used to control the heights of energy barriers of the hybrid-state energy landscape. A small s value facilitates state transitions by lowering energy barriers. Replica exchange between EDS potentials with different s values allows us to readily obtain a thermodynamically accurate ensemble of multiple protonation states with frequent state transitions. The analysis is performed with an ensemble obtained from an EDS Hamiltonian without smoothing, s = ∞, which strictly follows the minimum energy surface of the end states. The accuracy and efficiency of this method is tested on aspartic acid, lysine, and glutamic acid, which have two protonation states, a histidine with three states, a four-residue peptide with four states, and snake cardiotoxin with eight states. The pKa values estimated with the EDS-HREX method agree well with the experimental pKa values. The mean absolute errors of small benchmark systems range from 0.03 to 0.17 pKa units, and those of three titratable groups of snake cardiotoxin range from 0.2 to 1.6 pKa units. This study demonstrates that EDS-HREX is a potent theoretical framework, which gives the correct description of multiple protonation states and good calculated pKa values.

Uncovering pH-dependent transient states of proteins with buried ionizable residues

The role of pH in regulating biological activity is ubiquitous, and understanding pH-mediated activity has traditionally relied on analyzing static biomolecular structures of highly populated ground states solved near physiological pH. However, recent advances have shown the increasing importance of transiently populated states, the characterization of which is extremely challenging but made plausible with the development of techniques such as relaxation dispersion NMR spectroscopy. To unlock the pH dependence of these transient states with atomistic-level details, we applied the recently developed explicit solvent constant pH molecular dynamics (CPHMD(MSλD)) framework to a series of staphylococcal nuclease (SNase) mutants with buried ionizable residues and probed their dynamics in different pH environments. Among our key findings is the existence of open states in all SNase mutants containing "buried" residues with highly shifted pKa's, where local solvation around the protonation site was observed. The calculated pKa demonstrated good agreement with experimental pKa's, with a low average unsigned error of 1.3 pKa units and correlation coefficient R(2) = 0.78. Sampling both open and closed states in their respective pH range, where they are expected to be dominant, was necessary to reproduce experimental pKa's, and in the most extreme examples of pKa shifts measured, it can be interpreted that the open-state structures are transient at physiological pH, contributing a small population of 1-2%. This suggests that buried ionizable residues can trigger conformational fluctuations that may be observed as transient-state structures at physiological pH. Furthermore, the coupled relationship of both open and closed states and their role in recapitulating macroscopic experimental observables suggest that structural analysis of buried residues may benefit from looking at structural pairs, as opposed to the conventional approach of looking at a single static ground-state conformation.

Predicting the pKa and stability of organic acids and bases at an oil-water interface

We have used density functional theory and the implicit solvent model, COSMO-RS, to investigate how the acidity constant, pKa, of organic acids and bases adsorbed at the organic compound-aqueous solution interface changes, compared to its value in the aqueous phase. The pKa determine the surface charge density of the molecules that accumulate at the fluid-fluid interface. We have estimated the pKa by comparing the stability of the protonated and unprotonated forms of a series of molecules in the bulk aqueous solution and at an interface where parts of each molecule reside in the hydrophobic phase and the rest remains in the hydrophilic phase. We found that the pKa for acids is shifted by ∼1 pH unit to higher values compared to the bulk water pKa, whereas they are shifted to lower values by a similar amount for bases. Because this pKa shift is similar in magnitude for each of the molecules studied, we propose that the pKa for molecules at a water-organic compound interface can easily be predicted by adding a small shift to the aqueous pKa. This shift is general and correlates with the functional group. We also found that the relative composition of molecules at the fluid-fluid interface is not the same as in the bulk. For example, species such as carboxylic acids are enriched at the interface, where they can dominate surface properties, even when they are a modest component in the bulk fluid. For high surface concentrations of carboxylic acid groups at an interface, such as a self-assembled monolayer, we have demonstrated that the pKa depends on the degree of deprotonation through direct hydrogen bonding between protonated and deprotonated acidic headgroups.

Study of pK values and effective dielectric constants of ionizable residues in pentapeptides and in staphylococcal nuclease (SNase) using a mean-field approach

The determination of pK values of amino acid residues as a function of temperature and ionic concentration is crucial to understanding the dynamics of various biological processes such as adsorption of peptides and their interactions with active sites of enzymes. In this study we developed a mean-field model to calculate the position-dependent dielectric constants of ionizable groups and the mean electrostatic potential on the surface. Such potential, which takes into account the contributions exerted by neighboring groups and ions in solution, is responsible for the fine-tuning of the pK value of each residue. The proposed model was applied to the amino acids Asp, Glu, Lys, His, Tyr, and Cys, and since the results were consistent with experimentally obtained values, the model was extended and applied to computation of pK values of Gly and Ala pentapeptides and of ionizable residues of the enzyme staphylococcal nuclease (SNase). In this latter case, we used an approach similar to a first-neighbors approximation, and the results turned out to be in good agreement with previously reported data when considering only the interactions of charged groups located at distances of maximally 20 Å. These considerations and the little computational cost involved turn the suggested approach into a promising tool for the modeling of force fields in computational simulations.

Functional mapping and implications of substrate specificity of the yeast high-affinity leucine permease Bap2

Leucine is a major amino acid in nutrients and proteins and is also an important precursor of higher alcohols during brewing. In Saccharomyces cerevisiae, leucine uptake is mediated by multiple amino acid permeases, including the high-affinity leucine permease Bap2. Although BAP2 transcription has been extensively analyzed, the mechanisms by which a substrate is recognized and moves through the permease remain unknown. Recently, we determined 15 amino acid residues required for Tat2-mediated tryptophan import. Here we introduced homologous mutations into Bap2 amino acid residues and showed that 7 residues played a role in leucine import. Residues I109/G110/T111 and E305 were located within the putative α-helix break in TMD1 and TMD6, respectively, according to the structurally homologous Escherichia coli arginine/agmatine antiporter AdiC. Upon leucine binding, these α-helix breaks were assumed to mediate a conformational transition in Bap2 from an outward-open to a substrate-binding occluded state. Residues Y336 (TMD7) and Y181 (TMD3) were located near I109 and E305, respectively. Bap2-mediated leucine import was inhibited by some amino acids according to the following order of severity: phenylalanine, leucine>isoleucine>methionine, tyrosine>valine>tryptophan; histidine and asparagine had no effect. Moreover, this order of severity clearly coincided with the logP values (octanol-water partition coefficients) of all amino acids except tryptophan. This result suggests that the substrate partition efficiency to the buried Bap2 binding pocket is the primary determinant of substrate specificity rather than structural amino acid side chain recognition.

Side chain dynamics of carboxyl and carbonyl groups in the catalytic function of Escherichia coli ribonuclease H

Many proteins use Asx and Glx (x = n, p, or u) side chains as key functional groups in enzymatic catalysis and molecular recognition. In this study, NMR spin relaxation experiments and molecular dynamics simulations are used to measure the dynamics of the side chain amide and carboxyl groups, (13)C(γ/δ), in Escherichia coli ribonuclease HI (RNase H). Model-free analysis shows that the catalytic residues in RNase H are preorganized on ps-ns time scales via a network of electrostatic interactions. However, chemical exchange line broadening shows that these residues display significant conformational dynamics on μs-ms time scales upon binding of Mg(2+) ions. Two groups of catalytic residues exhibit differential line broadening, implicating distinct reorganizational processes upon binding of metal ions. These results support the "mobile metal ion" hypothesis, which was inferred from structural studies of RNase H.

Protein dielectric constants determined from NMR chemical shift perturbations

Understanding the connection between protein structure and function requires a quantitative understanding of electrostatic effects. Structure-based electrostatic calculations are essential for this purpose, but their use has been limited by a long-standing discussion on which value to use for the dielectric constants (ε(eff) and ε(p)) required in Coulombic and Poisson-Boltzmann models. The currently used values for ε(eff) and ε(p) are essentially empirical parameters calibrated against thermodynamic properties that are indirect measurements of protein electric fields. We determine optimal values for ε(eff) and ε(p) by measuring protein electric fields in solution using direct detection of NMR chemical shift perturbations (CSPs). We measured CSPs in 14 proteins to get a broad and general characterization of electric fields. Coulomb's law reproduces the measured CSPs optimally with a protein dielectric constant (ε(eff)) from 3 to 13, with an optimal value across all proteins of 6.5. However, when the water-protein interface is treated with finite difference Poisson-Boltzmann calculations, the optimal protein dielectric constant (ε(p)) ranged from 2 to 5 with an optimum of 3. It is striking how similar this value is to the dielectric constant of 2-4 measured for protein powders and how different it is from the ε(p) of 6-20 used in models based on the Poisson-Boltzmann equation when calculating thermodynamic parameters. Because the value of ε(p) = 3 is obtained by analysis of NMR chemical shift perturbations instead of thermodynamic parameters such as pK(a) values, it is likely to describe only the electric field and thus represent a more general, intrinsic, and transferable ε(p) common to most folded proteins.

Bayesian model aggregation for ensemble-based estimates of protein pKa values

This article investigates an ensemble-based technique called Bayesian Model Averaging (BMA) to improve the performance of protein amino acid pKa predictions. Structure-based pKa calculations play an important role in the mechanistic interpretation of protein structure and are also used to determine a wide range of protein properties. A diverse set of methods currently exist for pKa prediction, ranging from empirical statistical models to ab initio quantum mechanical approaches. However, each of these methods are based on a set of conceptual assumptions that can effect a model's accuracy and generalizability for pKa prediction in complicated biomolecular systems. We use BMA to combine eleven diverse prediction methods that each estimate pKa values of amino acids in staphylococcal nuclease. These methods are based on work conducted for the pKa Cooperative and the pKa measurements are based on experimental work conducted by the García-Moreno lab. Our cross-validation study demonstrates that the aggregated estimate obtained from BMA outperforms all individual prediction methods with improvements ranging from 45 to 73% over other method classes. This study also compares BMA's predictive performance to other ensemble-based techniques and demonstrates that BMA can outperform these approaches with improvements ranging from 27 to 60%. This work illustrates a new possible mechanism for improving the accuracy of pKa prediction and lays the foundation for future work on aggregate models that balance computational cost with prediction accuracy.

Protons as second messenger regulators of G protein signaling

In response to environmental stress, cells often generate pH signals that serve to protect vital cellular components and reprogram gene expression for survival. A major barrier to our understanding of this process has been the identification of signaling proteins that detect changes in intracellular pH. To identify candidate pH sensors, we developed a computer algorithm that searches proteins for networks of proton-binding sidechains. This analysis indicates that Gα subunits, the principal transducers of G protein-coupled receptor (GPCR) signals, are pH sensors. Our structure-based calculations and biophysical investigations reveal that Gα subunits contain networks of pH-sensing sidechains buried between their Ras and helical domains. Further, we show that proton binding induces changes in conformation that promote Gα phosphorylation and suppress receptor-initiated signaling. Together, our computational, biophysical, and cellular analyses reveal an unexpected function for G proteins as mediators of stress-response signaling.

Rapid calculation of protein pKa values using Rosetta

We developed a Rosetta-based Monte Carlo method to calculate the pK(a) values of protein residues that commonly exhibit variable protonation states (Asp, Glu, Lys, His, and Tyr). We tested the technique by calculating pK(a) values for 264 residues from 34 proteins. The standard Rosetta score function, which is independent of any environmental conditions, failed to capture pK(a) shifts. After incorporating a Coulomb electrostatic potential and optimizing the solvation reference energies for pK(a) calculations, we employed a method that allowed side-chain flexibility and achieved a root mean-square deviation (RMSD) of 0.83 from experimental values (0.68 after discounting 11 predictions with an error over 2 pH units). Additional degrees of side-chain conformational freedom for the proximal residues facilitated the capture of charge-charge interactions in a few cases, resulting in an overall RMSD of 0.85 pH units. The addition of backbone flexibility increased the overall RMSD to 0.93 pH units but improved relative pK(a) predictions for proximal catalytic residues. The method also captures large pK(a) shifts of lysine and some glutamate point mutations in staphylococcal nuclease. Thus, a simple and fast method based on the Rosetta score function and limited conformational sampling produces pK(a) values that will be useful when rapid estimation is essential, such as in docking, design, and folding.

Biomolecular electrostatics and solvation: a computational perspective

An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

How simple can a model of an empty viral capsid be? Charge distributions in viral capsids

We investigate and quantify salient features of the charge distributions on viral capsids. Our analysis combines the experimentally determined capsid geometry with simple models for ionization of amino acids, thus yielding a detailed description of spatial distribution for positive and negative charges across the capsid wall. The obtained data is processed in order to extract the mean radii of distributions, surface charge densities, as well as dipole moment densities. The results are evaluated and examined in light of previously proposed models of capsid charge distributions, which are shown to have to some extent limited value when applied to real viruses.

Structural reorganization triggered by charging of Lys residues in the hydrophobic interior of a protein

Structural consequences of ionization of residues buried in the hydrophobic interior of proteins were examined systematically in 25 proteins with internal Lys residues. Crystal structures showed that the ionizable groups are buried. NMR spectroscopy showed that in 2 of 25 cases studied, the ionization of an internal Lys unfolded the protein globally. In five cases, the internal charge triggered localized changes in structure and dynamics, and in three cases, it promoted partial or local unfolding. Remarkably, in 15 proteins, the ionization of the internal Lys had no detectable structural consequences. Highly stable proteins appear to be inherently capable of withstanding the presence of charge in their hydrophobic interior, without the need for specialized structural adaptations. The extent of structural reorganization paralleled loosely with global thermodynamic stability, suggesting that structure-based pK(a) calculations for buried residues could be improved by calculation of thermodynamic stability and by enhanced conformational sampling.

H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations

The accuracy of atomistic biomolecular modeling and simulation studies depend on the accuracy of the input structures. Preparing these structures for an atomistic modeling task, such as molecular dynamics (MD) simulation, can involve the use of a variety of different tools for: correcting errors, adding missing atoms, filling valences with hydrogens, predicting pK values for titratable amino acids, assigning predefined partial charges and radii to all atoms, and generating force field parameter/topology files for MD. Identifying, installing and effectively using the appropriate tools for each of these tasks can be difficult for novice and time-consuming for experienced users. H++ (http://biophysics.cs.vt.edu/) is a free open-source web server that automates the above key steps in the preparation of biomolecular structures for molecular modeling and simulations. H++ also performs extensive error and consistency checking, providing error/warning messages together with the suggested corrections. In addition to numerous minor improvements, the latest version of H++ includes several new capabilities and options: fix erroneous (flipped) side chain conformations for HIS, GLN and ASN, include a ligand in the input structure, process nucleic acid structures and generate a solvent box with specified number of common ions for explicit solvent MD.

Highly perturbed pKa values in the unfolded state of hen egg white lysozyme

The majority of pK(a) values in protein unfolded states are close to the amino acid model pK(a) values, thus reflecting the weak intramolecular interactions present in the unfolded ensemble of most proteins. We have carried out thermal denaturation measurements on the WT and eight mutants of HEWL from pH 1.5 to pH 11.0 to examine the unfolded state pK(a) values and the pH dependence of protein stability for this enzyme. The availability of accurate pK(a) values for the folded state of HEWL and separate measurements of mutant-induced effects on the folded state pK(a) values, allows us to estimate the pK(a) values of seven acidic residues in the unfolded state of HEWL. Asp-48 and Asp-66 display pK(a) values of 2.9 and 3.1 in our analysis, thus representing the most depressed unfolded state pK(a) values observed to date. We observe a strong correlation between the folded state pK(a) values and the unfolded state pK(a) values of HEWL, thus suggesting that the unfolded state of HEWL possesses a large degree of native state characteristics.

Proteome adaptation to high temperatures in the ectothermic hydrothermal vent Pompeii worm

Taking advantage of the massive genome sequencing effort made on thermophilic prokaryotes, thermal adaptation has been extensively studied by analysing amino acid replacements and codon usage in these unicellular organisms. In most cases, adaptation to thermophily is associated with greater residue hydrophobicity and more charged residues. Both of these characteristics are positively correlated with the optimal growth temperature of prokaryotes. In contrast, little information has been collected on the molecular 'adaptive' strategy of thermophilic eukaryotes. The Pompeii worm A. pompejana, whose transcriptome has recently been sequenced, is currently considered as the most thermotolerant eukaryote on Earth, withstanding the greatest thermal and chemical ranges known. We investigated the amino-acid composition bias of ribosomal proteins in the Pompeii worm when compared to other lophotrochozoans and checked for putative adaptive changes during the course of evolution using codon-based Maximum likelihood analyses. We then provided a comparative analysis of codon usage and amino-acid replacements from a greater set of orthologous genes between the Pompeii worm and Paralvinella grasslei, one of its closest relatives living in a much cooler habitat. Analyses reveal that both species display the same high GC-biased codon usage and amino-acid patterns favoring both positively-charged residues and protein hydrophobicity. These patterns may be indicative of an ancestral adaptation to the deep sea and/or thermophily. In addition, the Pompeii worm displays a set of amino-acid change patterns that may explain its greater thermotolerance, with a significant increase in Tyr, Lys and Ala against Val, Met and Gly. Present results indicate that, together with a high content in charged residues, greater proportion of smaller aliphatic residues, and especially alanine, may be a different path for metazoans to face relatively 'high' temperatures and thus a novelty in thermophilic metazoans.

Energies and pressures in viruses: contribution of nonspecific electrostatic interactions

We summarize some aspects of electrostatic interactions in the context of viruses. A simplified but, within well defined limitations, reliable approach is used to derive expressions for electrostatic energies and the corresponding osmotic pressures in single-stranded RNA viruses and double-stranded DNA bacteriophages. The two types of viruses differ crucially in the spatial distribution of their genome charge which leads to essential differences in their free energies, depending on the capsid size and total charge in a quite different fashion. Differences in the free energies are trailed by the corresponding characteristics and variations in the osmotic pressure between the inside of the virus and the external bathing solution.

The pKa Cooperative: a collaborative effort to advance structure-based calculations of pKa values and electrostatic effects in proteins

The pK(a) Cooperative (http://www.pkacoop.org) was organized to advance development of accurate and useful computational methods for structure-based calculation of pK(a) values and electrostatic energies in proteins. The Cooperative brings together laboratories with expertise and interest in theoretical, computational, and experimental studies of protein electrostatics. To improve structure-based energy calculations, it is necessary to better understand the physical character and molecular determinants of electrostatic effects. Thus, the Cooperative intends to foment experimental research into fundamental aspects of proteins that depend on electrostatic interactions. It will maintain a depository for experimental data useful for critical assessment of methods for structure-based electrostatics calculations. To help guide the development of computational methods, the Cooperative will organize blind prediction exercises. As a first step, computational laboratories were invited to reproduce an unpublished set of experimental pK(a) values of acidic and basic residues introduced in the interior of staphylococcal nuclease by site-directed mutagenesis. The pK(a) values of these groups are unique and challenging to simulate owing to the large magnitude of their shifts relative to normal pK(a) values in water. Many computational methods were tested in this first Blind Prediction Challenge and critical assessment exercise. A workshop was organized in the Telluride Science Research Center to objectively assess the performance of many computational methods tested on this one extensive data set. This volume of Proteins: Structure, Function, and Bioinformatics introduces the pK(a) Cooperative, presents reports submitted by participants in the Blind Prediction Challenge, and highlights some of the problems in structure-based calculations identified during this exercise.

Predicting extreme pKa shifts in staphylococcal nuclease mutants with constant pH molecular dynamics

Accurate computational methods of determining protein and nucleic acid pK(a) values are vital to understanding pH-dependent processes in biological systems. In this article, we use the recently developed method constant pH molecular dynamics (CPHMD) to explore the calculation of highly perturbed pK(a) values in variants of staphylococcal nuclease (SNase). Simulations were performed using the replica exchange (REX) protocol for improved conformational sampling with eight temperature windows, and yielded converged proton populations in a total sampling time of 4 ns. Our REX-CPHMD simulations resulted in calculated pK(a) values with an average unsigned error (AUE) of 0.75 pK units for the acidic residues in Δ + PHS, a hyperstable variant of SNase. For highly pK(a)-perturbed SNase mutants with known crystal structures, our calculations yielded an AUE of 1.5 pK units and for those mutants based on modeled structures an AUE of 1.4 pK units was found. Although a systematic underestimate of pK shifts was observed in most of the cases for the highly perturbed pK mutants, correlations between conformational rearrangement and plasticity associated with the mutation and error in pK(a) prediction was not evident in the data. This study further extends the scope of electrostatic environments explored using the REX-CPHMD methodology and suggests that it is a reliable tool for rapidly characterizing ionizable amino acids within proteins even when modeled structures are employed.