Are acidic and basic groups in buried proteins predicted to be ionized?

Protein dynamics govern the oxyferrous state lifetime of an artificial oxygen transport protein

It has long been known that the alteration of protein side chains that occlude or expose the heme cofactor to water can greatly affect the stability of the oxyferrous heme state. Here, we demonstrate that the rate of dynamically driven water penetration into the core of an artificial oxygen transport protein also correlates with oxyferrous state lifetime by reducing global dynamics, without altering the structure of the active site, via the simple linking of the two monomers in a homodimeric artificial oxygen transport protein using a glycine-rich loop. The tethering of these two helices does not significantly affect the active site structure, pentacoordinate heme-binding affinity, reduction potential, or gaseous ligand affinity. It does, however, significantly reduce the hydration of the protein core, as demonstrated by resonance Raman spectroscopy, backbone amide hydrogen exchange, and pKa shifts in buried histidine side chains. This further destabilizes the charge-buried entatic state and nearly triples the oxyferrous state lifetime. These data are the first direct evidence that dynamically driven water penetration is a rate-limiting step in the oxidation of these complexes. It furthermore demonstrates that structural rigidity that limits water penetration is a critical design feature in metalloenzyme construction and provides an explanation for both the failures and successes of earlier attempts to create oxygen-binding proteins.

Tools for analyzing protonation states and for tracing proton transfer pathways with examples from the Rb. sphaeroides photosynthetic reaction centers

Protons participate in many reactions. In proteins, protons need paths to move in and out of buried active sites. The vectorial movement of protons coupled to electron transfer reactions establishes the transmembrane electrochemical gradient used for many reactions, including ATP synthesis. Protons move through hydrogen bonded chains of waters and hydroxy side chains via the Grotthuss mechanism and by proton binding and release from acidic and basic residues. MCCE analysis shows that proteins exist in a large number of protonation states. Knowledge of the equilibrium ensemble can provide a rational basis for setting protonation states in simulations that fix them, such as molecular dynamics (MD). The proton path into the Q_B site in the bacterial reaction centers (RCs) of Rb. sphaeroides is analyzed by MD to provide an example of the benefits of using protonation states found by the MCCE program. A tangled web of side chains and waters link the cytoplasm to Q_B. MCCE analysis of snapshots from multiple trajectories shows that changing the input protonation state of a residue in MD biases the trajectory shifting the proton affinity of that residue. However, the proton affinity of some residues is more sensitive to the input structure. The proton transfer networks derived from different trajectories are quite robust. There are some changes in connectivity that are largely restricted to the specific residues whose protonation state is changed. Trajectories with Q_B^•- are compared with earlier results obtained with Q_B [Wei et. al Photosynthesis Research volume 152, pages153-165 (2022)] showing only modest changes. While introducing new methods the study highlights the difficulty of establishing the connections between protein conformation.

A Fast and Interpretable Deep Learning Approach for Accurate Electrostatics-Driven pKa Predictions in Proteins

Existing computational methods for estimating pK_a values in proteins rely on theoretical approximations and lengthy computations. In this work, we use a data set of 6 million theoretically determined pK_a shifts to train deep learning models, which are shown to rival the physics-based predictors. These neural networks managed to infer the electrostatic contributions of different chemical groups and learned the importance of solvent exposure and close interactions, including hydrogen bonds. Although trained only using theoretical data, our pKAI+ model displayed the best accuracy in a test set of ∼750 experimental values. Inference times allow speedups of more than 1000× compared to physics-based methods. By combining speed, accuracy, and a reasonable understanding of the underlying physics, our models provide a game-changing solution for fast estimations of macroscopic pK_a values from ensembles of microscopic values as well as for many downstream applications such as molecular docking and constant-pH molecular dynamics simulations.

Characterizing Protein Protonation Microstates Using Monte Carlo Sampling

Proteins are polyelectrolytes with acidic and basic amino acids Asp, Glu, Arg, Lys, and His, making up ≈25% of the residues. The protonation state of residues, cofactors, and ligands defines a "protonation microstate". In an ensemble of proteins some residues will be ionized and others neutral, leading to a mixture of protonation microstates rather than in a single one as is often assumed. The microstate distribution changes with pH. The protein environment also modifies residue proton affinity so microstate distributions change in different reaction intermediates or as ligands are bound. Particular protonation microstates may be required for function, while others exist simply because there are many states with similar energy. Here, the protonation microstates generated in Monte Carlo sampling in MCCE are characterized in HEW lysozyme as a function of pH and bacterial photosynthetic reaction centers (RCs) in different reaction intermediates. The lowest energy and highest probability microstates are compared. The ΔG, ΔH, and ΔS between the four protonation states of Glu35 and Asp52 in lysozyme are shown to be calculated with reasonable precision. At pH 7 the lysozyme charge ranges from 6 to 10, with 24 accepted protonation microstates, while RCs have ≈50,000. A weighted Pearson correlation analysis shows coupling between residue protonation states in RCs and how they change when the quinone in the Q_B site is reduced. Protonation microstates can be used to define input MD parameters and provide insight into the motion of protons coupled to reactions.

Electronic Polarization Is Essential for the Stabilization and Dynamics of Buried Ion Pairs in Staphylococcal Nuclease Mutants

Buried charged residues play important roles in the modulation of protein stabilities and conformational dynamics and make crucial contributions to protein functions. Considering the generally nonpolar nature of protein interior, a key question concerns the contribution of electronic polarization to the stabilization and properties of buried charges. We answer this question by conducting free energy simulations using the latest polarizable CHARMM force field based on Drude oscillators for a series of Staphylococcal nuclease mutants that involve a buried Glu-Lys pair in different titration states and orientations. While a nonpolarizable model suggests that the ionized form of the buried Glu-Lys pair is more than 40 kcal/mol less stable than the charge-neutral form, the two titration states are comparable in stability when electronic polarization is included explicitly, a result better reconcilable with available experimental data. Analysis of free energy components suggests that additional stabilization of the ionized Glu-Lys pair has contributions from both the enhanced salt-bridge strength and stronger interaction between the ion-pair and surrounding protein residues and penetrated water. Despite the stronger direct interaction between Glu and Lys, the ion-pair exhibits considerably larger and faster structural fluctuations when polarization is included, due to compensation of interactions in the cavity. Collectively, observations from this work provide compelling evidence that electronic polarization is essential to the stability, hydration, dynamics, and therefore function of buried charges in proteins. Therefore, our study advocates for the explicit consideration of electronic polarization for mechanistic and engineering studies that implicate buried charged residues, such as enzymes and ion transporters.

pKPDB: a protein data bank extension database of pKa and pI theoretical values

SUMMARY

pKa values of ionizable residues and isoelectric points of proteins provide valuable local and global insights about their structure and function. These properties can be estimated with reasonably good accuracy using Poisson-Boltzmann and Monte Carlo calculations at a considerable computational cost (from some minutes to several hours). pKPDB is a database of over 12 M theoretical pKa values calculated over 120k protein structures deposited in the Protein Data Bank. By providing precomputed pKa and pI values, users can retrieve results instantaneously for their protein(s) of interest while also saving countless hours and resources that would be spent on repeated calculations. Furthermore, there is an ever-growing imbalance between experimental pKa and pI values and the number of resolved structures. This database will complement the experimental and computational data already available and can also provide crucial information regarding buried residues that are under-represented in experimental measurements.

AVAILABILITY AND IMPLEMENTATION

Gzipped csv files containing p Ka and isoelectric point values can be downloaded from https://pypka.org/pKPDB. To query a single PDB code please use the PypKa free server at https://pypka.org. The pKPDB source code can be found at https://github.com/mms-fcul/pKPDB.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Using Atomic Charges to Describe the pKa of Carboxylic Acids

In this study, we present an accurate protocol for the fast prediction of pK_a's of carboxylic acids based on the linear relationship between computed atomic charges of the anionic form of the carboxylate fragment and their experimental pK_a values. Five charge descriptors, three charge models, three solvent models, gas-phase calculations, several DFT methods (a combination of eight DFT functionals and fifteen basis sets), and four different semiempirical approaches were tested. Among those, the best combination to reproduce experimental pK_a's is to compute the natural population analysis atomic charge using the solvation model based on density model at the M06L/6-311G(d,p) level of theory and selecting the maximum atomic charge on the carboxylic oxygen atoms (R² = 0.955). The applicability of the suggested protocol and its stability along geometrical changes are verified by molecular dynamics simulations performed for a set of aspartate, glutamate, and alanine peptides. By reporting the calculated atomic charge of the carboxylate form into the linear relationship derived in this work, it should be possible to accurately estimate the amino acid's pK_a's in a protein environment.

Electrostatic Environment of Proteorhodopsin Affects the pKa of Its Buried Primary Proton Acceptor

The protonation state of embedded charged residues in transmembrane proteins (TMPs) can control the onset of protein function. It is understood that interactions between an embedded charged residue and other charged or polar residues in the moiety would influence its pKa, but how the surrounding environment in which the TMP resides affects the pKa of these residues is unclear. Proteorhodopsin (PR), a light-responsive proton pump from marine bacteria, was used as a model to examine externally accessible factors that tune the pKa of its embedded charged residue, specifically its primary proton acceptor D97. The pKa of D97 was compared between PR reconstituted in liposomes with different net headgroup charges and equilibrated in buffer with different ion concentrations. For PR reconstituted in net positively charged compared to net negatively charged liposomes in low-salt buffer solutions, a drop of the apparent pKa from 7.6 to 5.6 was observed, whereas intrinsic pKa modeled with surface pH calculated from Gouy-Chapman predictions found an opposite trend for the pKa change, suggesting that surface pH does not account for the main changes observed in the apparent pKa. This difference in the pKa of D97 observed from PR reconstituted in oppositely charged liposome environments disappeared when the NaCl concentration was increased to 150 mM. We suggest that protein-intrinsic structural properties must play a role in adjusting the local microenvironment around D97 to affect its pKa, as corroborated with observations of changes in protein side-chain and hydration dynamics around the E-F loop of PR. Understanding the effect of externally controllable factors in tuning the pKa of TMP-embedded charged residues is important for bioengineering and biomedical applications relying on TMP systems, in which the onset of functions can be controlled by the protonation state of embedded residues.

Standard state free energies, not pKas, are ideal for describing small molecule protonation and tautomeric states

The pK_a is the standard measure used to describe the aqueous proton affinity of a compound, indicating the proton concentration (pH) at which two protonation states (e.g. A^- and AH) have equal free energy. However, compounds can have additional protonation states (e.g. AH₂⁺), and may assume multiple tautomeric forms, with the protons in different positions (microstates). Macroscopic pK_as give the pH where the molecule changes its total number of protons, while microscopic pK_as identify the tautomeric states involved. As tautomers have the same number of protons, the free energy difference between them and their relative probability is pH independent so there is no pK_a connecting them. The question arises: What is the best way to describe protonation equilibria of a complex molecule in any pH range? Knowing the number of protons and the relative free energy of all microstates at a single pH, ∆G°, provides all the information needed to determine the free energy, and thus the probability of each microstate at each pH. Microstate probabilities as a function of pH generate titration curves that highlight the low energy, observable microstates, which can then be compared with experiment. A network description connecting microstates as nodes makes it straightforward to test thermodynamic consistency of microstate free energies. The utility of this analysis is illustrated by a description of one molecule from the SAMPL6 Blind pK_a Prediction Challenge. Analysis of microstate ∆G°s also makes a more compact way to archive and compare the pH dependent behavior of compounds with multiple protonatable sites.

Marginal protein stability drives subcellular proteome isoelectric point

There exists a positive correlation between the pH of subcellular compartments and the median isoelectric point (pI) for the associated proteomes. Proteins in the human lysosome-a highly acidic compartment in the cell-have a median pI of ∼6.5, whereas proteins in the more basic mitochondria have a median pI of ∼8.0. Proposed mechanisms reflect potential adaptations to pH. For example, enzyme active site general acid/base residue pKs are likely evolved to match environmental pH. However, such effects would be limited to a few residues on specific proteins, and might not affect the proteome at large. A protein model that considers residue burial upon folding recapitulates the correlation between proteome pI and environmental pH. This correlation can be fully described by a neutral evolution process; no functional selection is included in the model. Proteins in acidic environments incur a lower energetic penalty for burying acidic residues than basic residues, resulting in a net accumulation of acidic residues in the protein core. The inverse is true under alkaline conditions. The pI distributions of subcellular proteomes are likely not a direct result of functional adaptations to pH, but a molecular spandrel stemming from marginal stability.

Comparing pairwise-additive and many-body generalized Born models for acid/base calculations and protein design

Generalized Born (GB) solvent models are common in acid/base calculations and protein design. With GB, the interaction between a pair of solute atoms depends on the shape of the protein/solvent boundary and, therefore, the positions of all solute atoms, so that GB is a many-body potential. For compute-intensive applications, the model is often simplified further, by introducing a mean, native-like protein/solvent boundary, which removes the many-body property. We investigate a method for both acid/base calculations and protein design that uses Monte Carlo simulations in which side chains can explore rotamers, bind/release protons, or mutate. The fluctuating protein/solvent dielectric boundary is treated in a way that is numerically exact (within the GB framework), in contrast to a mean boundary. Its originality is that it captures the many-body character while retaining the residue-pairwise complexity given by a fixed boundary. The method is implemented in the Proteus protein design software. It yields a slight but systematic improvement for acid/base constants in nine proteins and a significant improvement for the computational design of three PDZ domains. It eliminates a source of model uncertainty, which will facilitate the analysis of other model limitations. © 2017 Wiley Periodicals, Inc.

Polyelectrolyte pKa from experiment and molecular dynamics simulation

The pK_a of a polyelectrolyte has been determined experimentally by potentiometric titration and computed using Molecular Dynamics (MD) constant pH (CpH) methodology, which allows the pK_a of each titratable site along the polymer backbone.

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.

Origin of Asymmetric Solvation Effects for Ions in Water and Organic Solvents Investigated Using Molecular Dynamics Simulations: The Swain Acity-Basity Scale Revisited

The asymmetric solvation of ions can be defined as the tendency of a solvent to preferentially solvate anions over cations or cations over anions, at identical ionic charge magnitudes and effective sizes. Taking water as a reference, these effects are quantified experimentally for many solvents by the relative acity (A) and basity (B) parameters of the Swain scale. The goal of the present study is to investigate the asymmetric solvation of ions using molecular dynamics simulations, and to connect the results to this empirical scale. To this purpose, the charging free energies of alkali and halide ions, and of their hypothetical oppositely charged counterparts, are calculated in a variety of solvents. In a first set of calculations, artificial solvent models are considered that present either a charge or a shape asymmetry at the molecular level. The solvation asymmetry, probed by the difference in charging free energy between the two oppositely charged ions, is found to encompass a term quadratic in the ion charge, related to the different solvation structures around the anion and cation, and a term linear in the ion charge, related to the solvation structure around the uncharged ion-sized cavity. For these simple solvent models, the two terms are systematically counteracting each other, and it is argued that only the quadratic term should be retained when comparing the results of simulations involving physical solvents to experimental data. In a second set of calculations, 16 physical solvents are considered. The theoretical estimates for the acity A are found to correlate very well with the Swain parameters, whereas the correlation for B is very poor. Based on this observation, the Swain scale is reformulated into a new scale involving an asymmetry parameter Σ, positive for acitic solvents and negative for basitic ones, and a polarity parameter Π. This revised scale has the same predictive power as the original scale, but it characterizes asymmetry in an absolute sense, the atomistic simulations playing the role of an extra-thermodynamic assumption, and is optimally compatible with the simulation results. Considering the 55 solvents in the Swain set, it is observed that a moderate basity (Σ between -0.9 and -0.3, related to electronic polarization) represents the baseline for most solvents, while a highly variable acity (Σ between 0.0 and 3.0, related to hydrogen-bond donor capacity modulated by inductive effects) represents a landmark of protic solvents.

Effect of methylation on the side-chain pKa value of arginine

Arginine methylation is important in biological systems. Recent studies link the deregulation of protein arginine methyltransferases with certain cancers. To assess the impact of methylation on interaction with other biomolecules, the pKa values of methylated arginine variants were determined using NMR data. The pKa values of monomethylated, symmetrically dimethylated, and asymmetrically dimethylated arginine are similar to the unmodified arginine (14.2 ± 0.4). Although the pKa value has not been significantly affected by methylation, consequences of methylation include changes in charge distribution and steric effects, suggesting alternative mechanisms for recognition.

Tryptophan 207 is crucial to the unique properties of the human voltage-gated proton channel, hHV1

Part of the "signature sequence" that defines the voltage-gated proton channel (H(V1)) is a tryptophan residue adjacent to the second Arg in the S4 transmembrane helix: RxWRxxR, which is perfectly conserved in all high confidence H(V1) genes. Replacing Trp207 in human HV1 (hH(V1)) with Ala, Ser, or Phe facilitated gating, accelerating channel opening by 100-fold, and closing by 30-fold. Mutant channels opened at more negative voltages than wild-type (WT) channels, indicating that in WT channels, Trp favors a closed state. The Arrhenius activation energy, Ea, for channel opening decreased to 22 kcal/mol from 30-38 kcal/mol for WT, confirming that Trp207 establishes the major energy barrier between closed and open hH(V1). Cation-π interaction between Trp207 and Arg211 evidently latches the channel closed. Trp207 mutants lost proton selectivity at pHo >8.0. Finally, gating that depends on the transmembrane pH gradient (ΔpH-dependent gating), a universal feature of H(V1) that is essential to its biological functions, was compromised. In the WT hH(V1), ΔpH-dependent gating is shown to saturate above pHi or pHo 8, consistent with a single pH sensor with alternating access to internal and external solutions. However, saturation occurred independently of ΔpH, indicating the existence of distinct internal and external pH sensors. In Trp207 mutants, ΔpH-dependent gating saturated at lower pHo but not at lower pHi. That Trp207 mutation selectively alters pHo sensing further supports the existence of distinct internal and external pH sensors. Analogous mutations in H(V1) from the unicellular species Karlodinium veneficum and Emiliania huxleyi produced generally similar consequences. Saturation of ΔpH-dependent gating occurred at the same pHo and pHi in H(V1) of all three species, suggesting that the same or similar group(s) is involved in pH sensing. Therefore, Trp enables four characteristic properties: slow channel opening, highly temperature-dependent gating kinetics, proton selectivity, and ΔpH-dependent gating.

The structure of vanin 1: a key enzyme linking metabolic disease and inflammation

Although part of the coenzyme A pathway, vanin 1 (also known as pantetheinase) sits on the cell surface of many cell types as an ectoenzyme, catalyzing the breakdown of pantetheine to pantothenic acid (vitamin B5) and cysteamine, a strong reducing agent. Vanin 1 was initially discovered as a protein involved in the homing of leukocytes to the thymus. Numerous studies have shown that vanin 1 is involved in inflammation, and more recent studies have shown a key role in metabolic disease. Here, the X-ray crystal structure of human vanin 1 at 2.25 Å resolution is presented, which is the first reported structure from the vanin family, as well as a crystal structure of vanin 1 bound to a specific inhibitor. These structures illuminate how vanin 1 can mediate its biological roles by way of both enzymatic activity and protein-protein interactions. Furthermore, it sheds light on how the enzymatic activity is regulated by a novel allosteric mechanism at a domain interface.

ECMIS: computational approach for the identification of hotspots at protein-protein interfaces

BACKGROUND

Various methods have been developed to computationally predict hotspot residues at novel protein-protein interfaces. However, there are various challenges in obtaining accurate prediction. We have developed a novel method which uses different aspects of protein structure and sequence space at residue level to highlight interface residues crucial for the protein-protein complex formation.

RESULTS

ECMIS (Energetic Conservation Mass Index and Spatial Clustering) algorithm was able to outperform existing hotspot identification methods. It was able to achieve around 80% accuracy with incredible increase in sensitivity and outperforms other existing methods. This method is even sensitive towards the hotspot residues contributing only small-scale hydrophobic interactions.

CONCLUSION

Combination of diverse features of the protein viz. energy contribution, extent of conservation, location and surrounding environment, along with optimized weightage for each feature, was the key for the success of the algorithm. The academic version of the algorithm is available at http://caps.ncbs.res.in/download/ECMIS/ECMIS.zip.

Long-lasting effects of oxy- and sulfoanalogues of L-arginine on enzyme actions

Arginine residues are very important for the structure of proteins and their action. Arginine is essential for many natural processes because it has unique ionizable group under physiological conditions. Numerous mimetics of arginine were synthesized and their biological effects were evaluated, but the mechanisms of actions are still unknown. The aim of this study is to see if oxy- and sulfoanalogues of arginine can be recognized by human arginyl-tRNA synthetase (HArgS)—an enzyme responsible for coupling of L-arginine with its cognate tRNA in a two-step catalytic reaction. We make use of modeling and docking studies of adenylate kinase (ADK) to reveal the effects produced by the incorporation of the arginine mimetics on the structure of ADK and its action. Three analogues of arginine, L-canavanine (Cav), L-norcanavanine (NCav), and L-sulfoarginine (sArg), can be recognized as substrates of HArgS when incorporated in different peptide and protein sequences instead of L-arginine. Mutation in the enzyme active center by arginine mimetics leads to conformational changes, which produce a decrease the rate of the enzyme catalyzed reaction and even a loss of enzymatic action. All these observations could explain the long-lasting nature of the effects of the arginine analogues.

Peregrination of the selectivity filter delineates the pore of the human voltage-gated proton channel hHV1

Extraordinary selectivity is crucial to all proton-conducting molecules, including the human voltage-gated proton channel (hH_V1), because the proton concentration is >10⁶ times lower than that of other cations. Here we use “selectivity filter scanning” to elucidate the molecular requirements for proton-specific conduction in hH_V1. Asp¹¹², in the middle of the S1 transmembrane helix, is an essential part of the selectivity filter in wild-type (WT) channels. After neutralizing Asp¹¹² by mutating it to Ala (D112A), we introduced Asp at each position along S1 from 108 to 118, searching for “second site suppressor” activity. Surprisingly, most mutants lacked even the anion conduction exhibited by D112A. Proton-specific conduction was restored only with Asp or Glu at position 116. The D112V/V116D channel strikingly resembled WT in selectivity, kinetics, and ΔpH-dependent gating. The S4 segment of this mutant has similar accessibility to WT in open channels, because R211H/D112V/V116D was inhibited by internally applied Zn²⁺. Asp at position 109 allowed anion permeation in combination with D112A but did not rescue function in the nonconducting D112V mutant, indicating that selectivity is established externally to the constriction at F150. The three positions that permitted conduction all line the pore in our homology model, clearly delineating the conduction pathway. Evidently, a carboxyl group must face the pore directly to enable conduction. Molecular dynamics simulations indicate reorganization of hydrogen bond networks in the external vestibule in D112V/V116D. At both positions where it produces proton selectivity, Asp frequently engages in salt linkage with one or more Arg residues from S4. Surprisingly, mean hydration profiles were similar in proton-selective, anion-permeable, and nonconducting constructs. That the selectivity filter functions in a new location helps to define local environmental features required to produce proton-selective conduction.

Monte Carlo simulations of proteins at constant pH with generalized Born solvent, flexible sidechains, and an effective dielectric boundary

Titratable residues determine the acid/base behavior of proteins, strongly influencing their function; in addition, proton binding is a valuable reporter on electrostatic interactions. We describe a method for pK(a) calculations, using constant-pH Monte Carlo (MC) simulations to explore the space of sidechain conformations and protonation states, with an efficient and accurate generalized Born model (GB) for the solvent effects. To overcome the many-body dependency of the GB model, we use a "Native Environment" approximation, whose accuracy is shown to be good. It allows the precalculation and storage of interactions between all sidechain pairs, a strategy borrowed from computational protein design, which makes the MC simulations themselves very fast. The method is tested for 12 proteins and 167 titratable sidechains. It gives an rms error of 1.1 pH units, similar to the trivial "Null" model. The only adjustable parameter is the protein dielectric constant. The best accuracy is achieved for values between 4 and 8, a range that is physically plausible for a protein interior. For sidechains with large pKa shifts, ≥2, the rms error is 1.6, compared to 2.5 with the Null model and 1.5 with the empirical PROPKA method.

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.

Molecular mechanisms for generating transmembrane proton gradients

Membrane proteins use the energy of light or high energy substrates to build a transmembrane proton gradient through a series of reactions leading to proton release into the lower pH compartment (P-side) and proton uptake from the higher pH compartment (N-side). This review considers how the proton affinity of the substrates, cofactors and amino acids are modified in four proteins to drive proton transfers. Bacterial reaction centers (RCs) and photosystem II (PSII) carry out redox chemistry with the species to be oxidized on the P-side while reduction occurs on the N-side of the membrane. Terminal redox cofactors are used which have pKas that are strongly dependent on their redox state, so that protons are lost on oxidation and gained on reduction. Bacteriorhodopsin is a true proton pump. Light activation triggers trans to cis isomerization of a bound retinal. Strong electrostatic interactions within clusters of amino acids are modified by the conformational changes initiated by retinal motion leading to changes in proton affinity, driving transmembrane proton transfer. Cytochrome c oxidase (CcO) catalyzes the reduction of O2 to water. The protons needed for chemistry are bound from the N-side. The reduction chemistry also drives proton pumping from N- to P-side. Overall, in CcO the uptake of 4 electrons to reduce O2 transports 8 charges across the membrane, with each reduction fully coupled to removal of two protons from the N-side, the delivery of one for chemistry and transport of the other to the P-side.

Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins

Residue depth accurately measures burial and parameterizes local protein environment. Depth is the distance of any atom/residue to the closest bulk water. We consider the non-bulk waters to occupy cavities, whose volumes are determined using a Voronoi procedure. Our estimation of cavity sizes is statistically superior to estimates made by CASTp and VOIDOO, and on par with McVol over a data set of 40 cavities. Our calculated cavity volumes correlated best with the experimentally determined destabilization of 34 mutants from five proteins. Some of the cavities identified are capable of binding small molecule ligands. In this study, we have enhanced our depth-based predictions of binding sites by including evolutionary information. We have demonstrated that on a database (LigASite) of ∼200 proteins, we perform on par with ConCavity and better than MetaPocket 2.0. Our predictions, while less sensitive, are more specific and precise. Finally, we use depth (and other features) to predict pK_as of GLU, ASP, LYS and HIS residues. Our results produce an average error of just <1 pH unit over 60 predictions. Our simple empirical method is statistically on par with two and superior to three other methods while inferior to only one. The DEPTH server (http://mspc.bii.a-star.edu.sg/depth/) is an ideal tool for rapid yet accurate structural analyses of protein structures.

Improving protein complex classification accuracy using amino acid composition profile

Protein complex prediction approaches are based on the assumptions that complexes have dense protein-protein interactions and high functional similarity between their subunits. We investigated those assumptions by studying the subunits' interaction topology, sequence similarity and molecular function for human and yeast protein complexes. Inclusion of amino acids' physicochemical properties can provide better understanding of protein complex properties. Principal component analysis is carried out to determine the major features. Adopting amino acid composition profile information with the SVM classifier serves as an effective post-processing step for complexes classification. Improvement is based on primary sequence information only, which is easy to obtain.

Emerging approaches to probing ion channel structure and function

Ion channels, as membrane proteins, are the sensors of the cell. They act as the first line of communication with the world beyond the plasma membrane and transduce changes in the external and internal environments into unique electrical signals to shape the responses of excitable cells. Because of their importance in cellular communication, ion channels have been intensively studied at the structural and functional levels. Here, we summarize the diverse approaches, including molecular and cellular, chemical, optical, biophysical, and computational, used to probe the structural and functional rearrangements that occur during channel activation (or sensitization), inactivation (or desensitization), and various forms of modulation. The emerging insights into the structure and function of ion channels by multidisciplinary approaches allow the development of new pharmacotherapies as well as new tools useful in controlling cellular activity.

NMR structure and dynamics of the C-terminal domain from human Rev1 and its complex with Rev1 interacting region of DNA polymerase η

Rev1 is a translesion synthesis (TLS) DNA polymerase essential for DNA damage tolerance in eukaryotes. In the process of TLS stalled high-fidelity replicative DNA polymerases are temporarily replaced by specialized TLS enzymes that can bypass sites of DNA damage (lesions), thus allowing replication to continue or postreplicational gaps to be filled. Despite its limited catalytic activity, human Rev1 plays a key role in TLS by serving as a scaffold that provides an access of Y-family TLS polymerases polη, ι, and κ to their cognate DNA lesions and facilitates their subsequent exchange to polζ that extends the distorted DNA primer-template. Rev1 interaction with the other major human TLS polymerases, polη, ι, κ, and the regulatory subunit Rev7 of polζ, is mediated by Rev1 C-terminal domain (Rev1-CT). We used NMR spectroscopy to determine the spatial structure of the Rev1-CT domain (residues 1157-1251) and its complex with Rev1 interacting region (RIR) from polη (residues 524-539). The domain forms a four-helix bundle with a well-structured N-terminal β-hairpin docking against helices 1 and 2, creating a binding pocket for the two conserved Phe residues of the RIR motif that upon binding folds into an α-helix. NMR spin-relaxation and NMR relaxation dispersion measurements suggest that free Rev1-CT and Rev1-CT/polη-RIR complex exhibit μs-ms conformational dynamics encompassing the RIR binding site, which might facilitate selection of the molecular configuration optimal for binding. These results offer new insights into the control of TLS in human cells by providing a structural basis for understanding the recognition of the Rev1-CT by Y-family DNA polymerases.

Force fields for homology modeling

Accurate all-atom energy functions are crucial for successful high-resolution protein structure prediction. In this chapter, we review both physics-based force fields and knowledge-based potentials used in protein modeling. Because it is important to calculate the energy as accurately as possible given the limitations imposed by sampling convergence, different components of the energy, and force fields representing them to varying degrees of detail and complexity are discussed. Force fields using Cartesian as well as torsion angle representations of protein geometry are covered. Since solvent is important for protein energetics, different aqueous and membrane solvation models for protein simulations are also described. Finally, we summarize recent progress in protein structure refinement using new force fields.

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.

Arginine residues at internal positions in a protein are always charged

Many functionally essential ionizable groups are buried in the hydrophobic interior of proteins. A systematic study of Lys, Asp, and Glu residues at 25 internal positions in staphylococcal nuclease showed that their pK(a) values can be highly anomalous, some shifted by as many as 5.7 pH units relative to normal pK(a) values in water. Here we show that, in contrast, Arg residues at the same internal positions exhibit no detectable shifts in pK(a); they are all charged at pH ≤ 10. Twenty-three of these 25 variants with Arg are folded at both pH 7 and 10. The mean decrease in thermodynamic stability from substitution with Arg was 6.2 kcal/mol at this pH, comparable to that for substitution with Lys, Asp, or Glu at pH 7. The physical basis behind the remarkable ability of Arg residues to remain protonated in environments otherwise incompatible with charges is suggested by crystal structures of three variants showing how the guanidinium moiety of the Arg side chain is effectively neutralized through multiple hydrogen bonds to protein polar atoms and to site-bound water molecules. The length of the Arg side chain, and slight deformations of the protein, facilitate placement of the guanidinium moieties near polar groups or bulk water. This unique capacity of Arg side chains to retain their charge in dehydrated environments likely contributes toward the important functional roles of internal Arg residues in situations where a charge is needed in the interior of a protein, in a lipid bilayer, or in similarly hydrophobic environments.

MCCE analysis of the pKas of introduced buried acids and bases in staphylococcal nuclease

The pK(a)s of 96 acids and bases introduced into buried sites in the staphylococcal nuclease protein (SNase) were calculated using the multiconformation continuum electrostatics (MCCE) program and the results compared with experimental values. The pK(a)s are obtained by Monte Carlo sampling of coupled side chain protonation and position as a function of pH. The dependence of the results on the protein dielectric constant (ε(prot)) in the continuum electrostatics analysis and on the Lennard-Jones non-electrostatics parameters was evaluated. The pK(a)s of the introduced residues have a clear dependence on ε(prot,) whereas native ionizable residues do not. The native residues have electrostatic interactions with other residues in the protein favoring ionization, which are larger than the desolvation penalty favoring the neutral state. Increasing ε(prot) scales both terms, which for these residues leads to small changes in pK(a). The introduced residues have a larger desolvation penalty and negligible interactions with residues in the protein. For these residues, changing ε(prot) has a large influence on the calculated pK(a). An ε(prot) of 8-10 and a Lennard-Jones scaling of 0.25 is best here. The X-ray crystal structures of the mutated proteins are found to provide somewhat better results than calculations carried out on mutations made in silico. Initial relaxation of the in silico mutations by Gromacs and extensive side chain rotamer sampling within MCCE can significantly improve the match with experiment.

Simulating electrostatic energies in proteins: perspectives and some recent studies of pKas, redox, and other crucial functional properties

Electrostatic energies provide what is arguably the most effective tool for structure-function correlation of biological molecules. Here, we provide an overview of the current state-of-the-art simulations of electrostatic energies in macromolecules, emphasizing the microscopic perspective but also relating it to macroscopic approaches. We comment on the convergence issue and other problems of the microscopic models and the ways of keeping the microscopic physics while moving to semi-macroscopic directions. We discuss the nature of the protein dielectric "constants" reiterating our long-standing point that the dielectric "constants" in semi-macroscopic models depend on the definition and the specific treatment. The advances and the challenges in the field are illustrated considering different functional properties including pK(a)'s, redox potentials, ion and proton channels, enzyme catalysis, ligand binding, and protein stability. We emphasize the microscopic overcharging approach for studying pK(a) 's of internal groups in proteins and give a demonstration of power of this approach. We also emphasize recent advances in coarse grained models with a physically based electrostatic treatment and provide some examples including further directions in treating voltage activated ion channels.

Estimating the pKa values of basic and acidic side chains in ion channels using electrophysiological recordings: a robust approach to an elusive problem

As a step toward gaining a better understanding of the physicochemical bases of pK(a)-value shifts in ion channels, we have previously proposed a method for estimating the proton affinities of systematically engineered ionizable side chains from the kinetic analysis of single-channel current recordings. We reported that the open-channel current flowing through mutants of the (cation-selective) muscle nicotinic acetylcholine receptor (AChR) engineered to bear single basic residues in the transmembrane portion of the pore domain fluctuates between two levels of conductance. Our observations were consistent with the idea that these fluctuations track directly the alternate protonation-deprotonation of basic side chains: protonation of the introduced basic group would attenuate the single-channel conductance, whereas its deprotonation would restore the wild-type-like level. Thus, analysis of the kinetics of these transitions was interpreted to yield the pK(a) values of the substituted side chains. However, other mechanisms can be postulated that would also be consistent with some of our findings but according to which the kinetic analysis of the fluctuations would not yield true pK(a)s. Such mechanisms include the pH-dependent interconversion between two conformations of the channel that, while both ion permeable, would support different cation-conduction rates. In this article, we present experimental evidence for the notion that the fluctuations of the open-channel current observed for the muscle AChR result from the electrostatic interaction between fixed charges and the passing cations rather than from a change in conformation. Hence, we conclude that bona fide pK(a) values can be obtained from single-channel recordings.

Statistical analysis of protein structures suggests that buried ionizable residues in proteins are hydrogen bonded or form salt bridges

It is well known that nonpolar residues are largely buried in the interior of proteins, whereas polar and ionizable residues tend to be more localized on the protein surface where they are solvent exposed. Such a distribution of residues between surface and interior is well understood from a thermodynamic point: nonpolar side chains are excluded from the contact with the solvent water, whereas polar and ionizable groups have favorable interactions with the water and thus are preferred at the protein surface. However, there is an increasing amount of information suggesting that polar and ionizable residues do occur in the protein core, including at positions that have no known functional importance. This is inconsistent with the observations that dehydration of polar and in particular ionizable groups is very energetically unfavorable. To resolve this, we performed a detailed analysis of the distribution of fractional burial of polar and ionizable residues using a large set of ˜2600 nonhomologous protein structures. We show that when ionizable residues are fully buried, the vast majority of them form hydrogen bonds and/or salt bridges with other polar/ionizable groups. This observation resolves an apparent contradiction: the energetic penalty of dehydration of polar/ionizable groups is paid off by favorable energy of hydrogen bonding and/or salt bridge formation in the protein interior. Our conclusion agrees well with the previous findings based on the continuum models for electrostatic interactions in proteins.

Distinguishing two groups of flavin reductases by analyzing the protonation state of an active site carboxylic acid

Flavin-containing reductases are involved in a wide variety of physiological reactions such as photosynthesis, nitric oxide synthesis, and detoxification of foreign compounds, including therapeutic drugs. Ferredoxin-NADP(H)-reductase (FNR) is the prototypical enzyme of this family. The fold of this protein is highly conserved and occurs as one domain of several multidomain enzymes such as the members of the diflavin reductase family. The enzymes of this family have emerged as fusion of a FNR and a flavodoxin. Although the active sites of these enzymes are very similar, different enzymes function in opposite directions, that is, some reduce oxidized nicotinamide adenine dinucleotide phosphate (NADP(+)) and some oxidize reduced nicotinamide adenine dinucleotide phosphate (NADPH). In this work, we analyze the protonation behavior of titratable residues of these enzymes through electrostatic calculations. We find that a highly conserved carboxylic acid in the active site shows a different titration behavior in different flavin reductases. This residue is deprotonated in flavin reductases present in plastids, but protonated in bacterial counterparts and in diflavin reductases. The protonation state of the carboxylic acid may also influence substrate binding. The physiological substrate for plastidic enzymes is NADP(+), but it is NADPH for the other mentioned reductases. In this article, we discuss the relevance of the environment of this residue for its protonation and its importance in catalysis. Our results allow to reinterpret and explain experimental data.

Ab initio calculations of deuterium isotope effects on chemical shifts of salt-bridged lysines

Deuterium isotope effects measure the change in chemical shift on substitution of a proton by deuterium. They have been calculated by direct treatment of the H/D nuclear quantum effect using a multicomponent ab initio molecular orbital method based on a non-Born-Oppenheimer approximation. This method enables the determination of both the electronic and the protonic (deuteronic) wave functions simultaneously and can directly calculate the geometrical difference induced by H/D isotope effects. The calculations show that the one-bond deuterium isotope effects on (15)N nuclear shielding, (1)Δ(15)N(D), in ammonium and amines decrease as a counterion or water molecule moves closer to the nitrogen. (1)Δ(15)N(D) and (2)Δ(1)H(D) of the NH(3)(+) groups of lysine residues in the B1 domain of protein G have been calculated using truncated side chains and also determined experimentally by NMR. Comparisons show that the structures in solution are different from those in the crystal and that solvation plays an important role in weakening the hydrogen bonds.

A nuclear magnetic resonance-based structural rationale for contrasting stoichiometry and ligand binding site(s) in fatty acid-binding proteins

Liver fatty acid-binding protein (LFABP) is a 14 kDa cytosolic polypeptide, differing from other family members in the number of ligand binding sites, the diversity of bound ligands, and the transfer of fatty acid(s) to membranes primarily via aqueous diffusion rather than direct collisional interactions. Distinct two-dimensional (1)H-(15)N nuclear magnetic resonance (NMR) signals indicative of slowly exchanging LFABP assemblies formed during stepwise ligand titration were exploited, without determining the protein-ligand complex structures, to yield the stoichiometries for the bound ligands, their locations within the protein binding cavity, the sequence of ligand occupation, and the corresponding protein structural accommodations. Chemical shifts were monitored for wild-type LFABP and an R122L/S124A mutant in which electrostatic interactions viewed as being essential to fatty acid binding were removed. For wild-type LFABP, the results compared favorably with the data for previous tertiary structures of oleate-bound wild-type LFABP in crystals and in solution: there are two oleates, one U-shaped ligand that positions the long hydrophobic chain deep within the cavity and another extended structure with the hydrophobic chain facing the cavity and the carboxylate group lying close to the protein surface. The NMR titration validated a prior hypothesis that the first oleate to enter the cavity occupies the internal protein site. In contrast, (1)H and (15)N chemical shift changes supported only one liganded oleate for R122L/S124A LFABP, at an intermediate location within the protein cavity. A rationale based on protein sequence and electrostatics was developed to explain the stoichiometry and binding site trends for LFABPs and to put these findings into context within the larger protein family.

Multiconformation continuum electrostatics analysis of the effects of a buried Asp introduced near heme a in Rhodobacter sphaeroides cytochrome c oxidase

Cytochrome c oxidase (CcO) reduces O(2) to water via a series of proton-coupled electron transfers, generating a transmembrane electrochemical gradient. Coupling electron and proton transfer requires changing the pK(a) values of buried residues at each stage in the reaction cycle. Heme a is a key cofactor in the CcO electron transfer chain. Mutation of Ser44 to Asp has been reported [Mills, D. A., et al. (2008) Biochemistry 47, 11499-11509], changing the hydrogen bond acceptor from His102, the heme a axial ligand in Rhodobactor sphaeroides CcO. This adds an acidic residue to the CcO interior. The electrochemical behavior of heme a in wild-type and S44D CcO is compared using the continuum electrostatics program MCCE. The introduced, deeply buried Asp remains ionized at physiological pH only when the nearby heme is oxidized. Heme a reduction is now calculated to be strongly coupled to Asp proton binding, while with Ser44, it is weakly coupled to small protonation shifts at multiple sites, increasing the pH dependence in the mutant. At pH 7, the partially ionized Asp 44 is calculated to lower the heme redox potential by 50 mV as expected given the thermodynamics of coupled electron and proton transfers. This highlights an curious finding in the experimental results where a low Asp pK(a) is found together with a stabilized reduced heme. The stabilization of a heme oxidation in a model complex by a hydrogen bond to the axial His ligand calculated with continuum electrostatics and with density functional theory were in good agreement.

MCCE2: improving protein pKa calculations with extensive side chain rotamer sampling

Multiconformation continuum electrostatics (MCCE) explores different conformational degrees of freedom in Monte Carlo calculations of protein residue and ligand pK(a)s. Explicit changes in side chain conformations throughout a titration create a position dependent, heterogeneous dielectric response giving a more accurate picture of coupled ionization and position changes. The MCCE2 methods for choosing a group of input heavy atom and proton positions are described. The pK(a)s calculated with different isosteric conformers, heavy atom rotamers and proton positions, with different degrees of optimization are tested against a curated group of 305 experimental pK(a)s in 33 proteins. QUICK calculations, with rotation around Asn and Gln termini, sampling His tautomers and torsion minimum hydroxyls yield an RMSD of 1.34 with 84% of the errors being <1.5 pH units. FULL calculations adding heavy atom rotamers and side chain optimization yield an RMSD of 0.90 with 90% of the errors <1.5 pH unit. Good results are also found for pK(a)s in the membrane protein bacteriorhodopsin. The inclusion of extra side chain positions distorts the dielectric boundary and also biases the calculated pK(a)s by creating more neutral than ionized conformers. Methods for correcting these errors are introduced. Calculations are compared with multiple X-ray and NMR derived structures in 36 soluble proteins. Calculations with X-ray structures give significantly better pK(a)s. Results with the default protein dielectric constant of 4 are as good as those using a value of 8. The MCCE2 program can be downloaded from http://www.sci.ccny.cuny.edu/~mcce.

Evidence for the adaptation of protein pH-dependence to subcellular pH

BACKGROUND

The availability of genome sequences, and inferred protein coding genes, has led to several proteome-wide studies of isoelectric points. Generally, isoelectric points are distributed following variations on a biomodal theme that originates from the predominant acid and base amino acid sidechain pKas. The relative populations of the peaks in such distributions may correlate with environment, either for a whole organism or for subcellular compartments. There is also a tendency for isoelectric points averaged over a subcellular location to not coincide with the local pH, which could be related to solubility. We now calculate the correlation of other pH-dependent properties, calculated from 3D structure, with subcellular pH.

RESULTS

For proteins with known structure and subcellular annotation, the predicted pH at which a protein is most stable, averaged over a location, gives a significantly better correlation with subcellular pH than does isoelectric point. This observation relates to the cumulative properties of proteins, since maximal stability for individual proteins follows the bimodal isoelectric point distribution. Histidine residue location underlies the correlation, a conclusion that is tested against a background of proteins randomised with respect to this feature, and for which the observed correlation drops substantially.

CONCLUSION

There exists a constraint on protein pH-dependence, in relation to the local pH, that is manifested in the pKa distribution of histidine sub-proteomes. This is discussed in terms of protein stability, pH homeostasis, and fluctuations in proton concentration.

Stability and structure of the membrane protein transporter Ffh is modulated by substrates and lipids

The cytosolic protein Ffh transports membrane proteins from the ribosome to the inner membrane in complex with 4.5S RNA. Here we show that native Ffh binds to the hydrophobic probe ANS in a 1 Ffh:3 ANS stoichiometry, revealing a hydrophobic binding site. Thermal precipitation of Ffh is shifted upwards by approximately 10 degrees C by ANS or substrate protein, suggesting that the hydrophobic binding site makes the protein aggregation prone. Chemical denaturation confirm that Ffh is a rather unstable protein. 4.5S RNA destabilizes Ffh further, suggesting it keeps the protein in a more open conformation than the apoprotein. Escherichia coli lipid and DOPG (and to a smaller extent DOPC) increase Ffh's alpha-helical content, possibly related to Ffh's role in guiding membrane proteins to the membrane. Binding is largely mediated by electrostatic interactions but does not protect Ffh against trypsinolysis. We conclude that Ffh is a structurally flexible and dynamic protein whose stability is significantly modulated by the environment.

Combined computational and biochemical study reveals the importance of electrostatic interactions between the "pH sensor" and the cation binding site of the sodium/proton antiporter NhaA of Escherichia coli

Sodium proton antiporters are essential enzymes that catalyze the exchange of sodium ions for protons across biological membranes. The crystal structure of NhaA has provided a basis to explore the mechanism of ion exchange and its unique regulation by pH. Here, the mechanism of the pH activation of the antiporter is investigated through functional and computational studies of several variants with mutations in the ion-binding site (D163, D164). The most significant difference found computationally between the wild type antiporter and the active site variants, D163E and D164N, are low pK(a) values of Glu78 making them insensitive to pH. Although in the variant D163N the pK(a) of Glu78 is comparable to the physiological one, this variant cannot demonstrate the long-range electrostatic effect of Glu78 on the pH-dependent structural reorganization of trans-membrane helix X and, hence, is proposed to be inactive. In marked contrast, variant D164E remains sensitive to pH and can be activated by alkaline pH shift. Remarkably, as expected computationally and discovered here biochemically, D164E is viable and active in Na(+)/H(+) exchange albeit with increased apparent K(M). Our results unravel the unique electrostatic network of NhaA that connect the coupled clusters of the "pH sensor" with the binding site, which is crucial for pH activation of NhaA.