Using Multiconformation Continuum Electrostatics to Compare Chloride Binding Motifs in α-Amylase, Human Serum Albumin, and Omp32

https://doi.org/10.1016/j.jmb.2009.01.038Get rights and content

Abstract

Ions are a ubiquitous component of the cellular environment, transferring into cells through membrane-embedded proteins. Ions bind to proteins to regulate their charge and function. Here, using multiconformation continuum electrostatics (MCCE), we show that the changes of chloride binding to α-amylase, human serum albumin (HSA) and Omp32 with pH, and of α-amylase with mutation agree well with experimental data. The three proteins represent three different types of binding. In α-amylase, chloride is bound in a specific buried site. Chloride binding is strongly coupled to the protonation state of a nearby lysine. MCCE calculates an 11-fold change in chloride affinity between the wild-type α-amylase and the K300R mutant, in good agreement with the measured 10-fold change. Without considering the coupled protonation reaction, the calculated affinity change would be more than 106-fold. In HSA, chlorides are distributed on the protein surface. Although HSA has a negative net charge, it binds more anions than cations. There are no highly occupied binding sites in HSA. Rather, there are many partially occupied sites near clusters of basic residues. The relative affinity of bound ions of different charges is shown to depend on the distribution of charged residues on the surface rather than the overall net charge of the protein. The calculated strong pH dependence of the number of chlorides bound and the anion selectivity agree with those of previous experiments. In Omp32, chlorides are stabilized in an anion-selective transmembrane channel in a pH-independent manner. The positive electrostatic potential in Omp32 results in about two chlorides and no cations bound in the transmembrane region of this anion-selective channel. The studies here show that with the ability to sample multiple binding sites and coupled protein protonation states, MCCE provides a powerful tool to analyze and predict ion binding. The calculations overestimate the affinity of surface chloride in HSA and Omp32 relative to the buried ion in amylase. Differences between ion–solvent interactions for buried and surface ions will be discussed.

Introduction

The interior and exterior of living cells contain significant and different concentrations of salts. For example, the chloride concentration is 4 mM in the cell interior and 116 mM in blood.1 Thus, all cells have mechanisms to control ion transport across cell membranes and to sequester different ions. The function of many proteins is dependent on bound ions. Examples include the chloride channels, which are important in muscle function and signal transduction;2 hemoglobin, where oxygen-dependent anion binding helps regulate oxygen affinity;3, 4 the bacterial chloride pump, halorhodopsin,5, 6 which helps maintain the osmotic balance for halobacteria living in a saturated salt solution;7, 8 and the ArsA–ArsB anion ATPase complex, which mediates the resistance to arsenical and antimonial compounds in bacteria.9, 10 Computational methods to study anion binding help illuminate the mechanism of anion action in these proteins.

Ions can be bound in different ways to modulate protein structure and function. They can be bound internally, far from the surface and away from water. These ions interact strongly with the protein, allowing them to play important roles in stabilizing the structure11, 12 or tuning the electrostatic environment at the catalytic site.13 Buried charged ions can induce large pKa shifts in nearby residues, leading to protonation changes and a strong pH dependence of ion binding. Ions can also play important roles by binding to the protein surface. These ions remain well solvated, leading to weak, diffuse binding. Surface ions are important for regulating the overall charge of the macromolecule, mediating salt bridges on the protein surface or between proteins and altering the electrostatic environment surrounding the protein. Diffuse binding of ions on the surface can collectively change the net charge of the protein. However, identifying individual surface binding sites explicitly may be difficult. Ions are transported in and out of cells via transmembrane channels. These ions must have sufficient affinity for the channels but cannot be bound so tightly that they are trapped inside. The ion–protein interactions can be regulated by the electrostatic potential gradient as in the voltage-gated ion channels,14 can be pH independent as in Omp32,15, 16 and can be highly selectively favoring one type of ion.17 In narrow regions of a channel, such as in the selective filter of potassium channel KcsA, where a narrow pore formed by backbone carbonyl groups allows passage of only single K+,18, 19 ions will be highly desolvated; or they can remain solvated, as in the bacterial ion channels OmpF and Omp32, which are large enough to surround ions with water.20

Ions have strong, favorable interactions with water, referred to as their solvation, Born energy, or reaction field energy.21 Ion binding sites need to replace the lost solvation energy with favorable interactions with the protein. The positively charged residues, Arg, Lys, and His, and hydrogen-bond donors, such as Ser and Thr, contribute to form the binding sites. For example, two Arg/Thr pairs and a Ser bind a chloride in the center of halorhodopsin.22, 23, 24 Site-directed mutagenesis removing specific Arg25 or Lys26 reduces the chloride conductance in the chloride channel CLC-0. Several Lys residues are identified in the chloride binding site of hemoglobin.27 However, comparison of these binding sites does not reveal a specific binding motif for chloride. Rather, it seems that a pocket with a sufficiently positive electrostatic potential is enough, without any strong geometric constraints.

Quantum mechanical calculations using Hartree Fock theory have been used to study the volumes, coordination numbers, and hydration energies of simple ions.28 However, it has been suggested that spherically symmetric Lennard–Jones and electrostatic potentials are sufficient to model binding of closed-shell, spherical ions such as chloride.29 NMR measurements give a quadrupole coupling constant for a chloride bound to human serum albumin (HSA) that is consistent with protein–ion association being dominated by electrostatic interactions.30 Classical computational studies have been carried out on ions in solution using molecular dynamics (MD) and Monte Carlo approaches.31, 32, 33, 34, 35, 36, 37, 38 Classical Born theory has been shown to do a good job of accounting for hydration (solvation) enthalpies.39 However, comparisons of different force fields for aqueous sodium chloride showed earlier Lennard–Jones parameters could not consistently model relative free energies and structures of ion association.38, 40 The latest effort by Jensen and Jorgensen38 appears to provide a more self-consistent set of parameters for ions.

A methodology that can explicitly describe ion binding to proteins requires proper consideration of coupled protein protonation or conformational changes, efficient calculation of the Boltzmann distribution of weekly associated ions, and accurate estimation of ion hydration and ion–protein interactions. The Poisson–Boltzmann equation, which uses an implicit solvent and a Debye-Hückel-type ionic solution with a continuum ion density, is often used to describe the averaged, Boltzmann distribution of ions associated with the protein by electrostatic interactions.41 While this provides a good way to account for the ionic strength effect on the macromolecule electrostatic interactions, it cannot account for binding individual ions. Many studies have been devoted to the analysis of the ion–protein interactions in ion channels (for recent reviews, see Refs. 42, 43). MD and Brownian dynamics simulations, with fixed residue protonation states, are the most commonly used for studying ion conductivity and selectivity in gramicidin A,44, 45 OmpF,46, 47, 48, 49, 50 and potassium channels.19, 51, 52, 53 Methods incorporating continuum electrostatics have been used to study the electrostatic basis of ion selectivity18, 54 and the side-chain ionization states in channels.55, 56 Other techniques including grand canonical Monte Carlo48 and free-energy perturbation and umbrella sampling57, 58 have been integrated into these studies.

Multiconformation continuum electrostatics (MCCE) has been developed to calculate the Boltzmann distribution of ionization states of protein residues, cofactors, and substrates using Monte Carlo sampling.59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70 The approach introduced here samples ion binding within pKa calculations. This allows fast sampling of multiple ion binding sites, especially in cases where ion and proton binding are coupled. The chloride binding sites of three proteins are studied: α-amylase, with a single proton-coupled chloride binding site; human serum abumin (HSA), with a diffuse group of weakly pH dependent surface-associated ions; and Omp32, an anion-selective channel. The pH and chloride concentration dependence of chloride binding are calculated and compared to the available experimental data. The calculated difference in chloride affinity between the wild-type α-amylase and the K300R mutant; the pH and chloride concentration dependence of α-amylase activity; the pH dependence of the amount of surface-bound chloride by HSA; and anion selectivity of ion binding in HSA and Omp32 all agree well with the experimental data. Thus, MCCE can provide an effective method for analysis of ion binding. As in standard continuum electrostatics simulations, an additive constant accounting for the ion concentration and its solvation energy is used.71 We find a different offset is needed to recover the absolute chloride affinities for surface-exposed and buried chlorides. This may result from a missing term in the novel mixture of implicit, continuum, and explicit ions used here.

Section snippets

Results and Discussion

The distribution, occupancy, and pH dependence of chloride binding was calculated in α-amylase, HSA, and Omp32. Ions were added to cavities in all three proteins. In addition, a layer of surface chlorides was added to HSA and into the pore in the anion-selective channel Omp32. In each case, the ion positions were optimized with the standard MCCE minimization routines during conformer generation, moving them off grid to make more favorable interactions with the protein. Monte Carlo sampling

Conclusion

The calculated chloride binding in the three proteins presented here highlights different ways proteins can bind ions. In α-amylase, the binding site is deeply buried in the protein, leading to a large desolvation penalty and large compensatory interactions with the protein, while in HSA, chlorides are weakly bound on the surface of the protein, and in Omp32, chlorides are localized in three sites in the transmembrane channel. Interactions of the surface-bound chlorides with the protein are

Materials and Methods

Structures of the wild-type α-amylase (1AQH) and the K300R mutant (1JD7) from P. haloplanktis84 (formerly Alteromonas haloplanktis76) and HSA (1BM0)103 were taken from the Protein Data Bank.104 The trimeric biological unit of Omp32 from Comamonas acidovorans (1E54)94 was obtained from the Macromolecular Structure Database at the European Bioinformatics Institute,105 which uses the crystallographic symmetry information to assemble biological quaternary states†.

Acknowledgements

We gratefully acknowledge financial support of NSF MCB-0517589 and infrastructure support from NIH 5G12 RR03060 from the National Center for Research Resources.

References (120)

  • MaduraJ.D. et al.

    Effects of truncating long-range interactions in aqueous ionic solution simulations

    Chem. Phys. Lett.

    (1988)
  • RouxB.

    Theoretical and computational models of ion channels

    Curr. Opin. Struct. Biol.

    (2002)
  • MackayD. et al.

    Structure and dynamics of ion transport through gramicidin A

    Biophys. J.

    (1984)
  • WoolfT. et al.

    The binding site of sodium in the gramicidin A channel: comparison of molecular dynamics with solid-state NMR data

    Biophys. J.

    (1997)
  • ImW. et al.

    A grand canonical Monte Carlo–Brownian dynamics algorithm for simulating ion channels

    Biophys. J.

    (2000)
  • ZachariaeU. et al.

    Multistep mechanism of chloride translocation in a strongly anion-selective porin channel

    Biophys. J.

    (2003)
  • VarmaS. et al.

    The influence of amino acid protonation states on molecular dynamics simulations of the bacterial porin OmpF

    Biophys. J.

    (2006)
  • LuzhkovV. et al.

    A computational study of ion binding and protonation states in the KcsA potassium channel

    Biochim. Biophys. Acta

    (2000)
  • BernècheS. et al.

    Molecular dynamics of the KcsA K+ channel in a bilayer membrane

    Biophys. J.

    (2000)
  • LuzhkovV. et al.

    K+/Na+ selectivity of the KcsA potassium channel from microscopic free energy perturbation calculations

    Biochim. Biophys. Acta

    (2001)
  • RanatungaK. et al.

    Side-chain ionization states in a potassium channel

    Biophys. J.

    (2001)
  • AlexovE.G. et al.

    Incorporating protein conformational flexibility into the calculation of pH-dependent protein properties

    Biophys. J.

    (1997)
  • GeorgescuR. et al.

    Combining conformational flexibility and continuum electrostatics for calculating pKas in proteins

    Biophys. J.

    (2002)
  • HaasA.H. et al.

    Calculated coupling of transmembrane electron and proton transfer in dihemic quinol:fumarate reductase

    Biophys. J.

    (2004)
  • KimJ. et al.

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

    J. Mol. Biol.

    (2005)
  • TangC.L. et al.

    Calculation of pKas in RNA: on the structural origins and functional roles of protonated nucleotides

    J. Mol. Biol.

    (2007)
  • GunnerM.R. et al.

    Factors influencing the energetics of electron and proton transfers in proteins. What can be learned from calculations

    Biochim. Biophys. Acta

    (2006)
  • ThomaJ.A. et al.

    Plant and animal amylases

  • JanecekS.

    α-Amylase family: molecular biology and evolution

    Prog. Biophys. Mol. Biol.

    (1997)
  • D'AmicoS. et al.

    Structural similarities and evolutionary relationships in chloride-dependent α-amylases

    Gene

    (2000)
  • SvenssonB. et al.

    Mutational analysis of glycosylase function

    J. Biotechnol.

    (1993)
  • McCarterJ. et al.

    Unequivocal identification of Asp-214 as the catalytic nucleophile of Saccharomyces cerevisiae α-glucosidase using 5-fluoro glycosyl fluorides

    J. Biol. Chem.

    (1996)
  • QianM. et al.

    Structure and molecular model refinement of pig pancreatic α-amylase at 2.1 Å resolution

    J. Mol. Biol.

    (1993)
  • LarsonS. et al.

    Refined molecular structure of pig pancreatic α-amylase at 2.1 Å resolution

    J. Mol. Biol.

    (1994)
  • FellerG. et al.

    Structural and functional aspects of chloride binding to Alteromonas haloplanctis α-amylase

    J. Biol. Chem.

    (1996)
  • WiltingJ. et al.

    The effect of albumin conformation on the binding of warfarin to human serum albumin. The dependence of the binding of warfarin to human serum albumin on the hydrogen, calcium, and chloride ion concentrations as studied by circular dichroism, fluorescence, and equilibrium dialysis

    J. Biol. Chem.

    (1980)
  • SchirmerT. et al.

    Brownian dynamics simulation of ion flow through porin channels

    J. Mol. Biol.

    (1999)
  • ZethK. et al.

    Crystal structure of Omp32, the anion-selective porin from Comamonas acidovorans, in complex with a periplasmic peptide at 2.1 Å resolution

    Structure

    (2000)
  • ArchontisG. et al.

    Binding free energies and free energy components from molecular dynamics and Poisson–Boltzmann calculations. Application to amino acid recognition by aspartyl-tRNA synthetase

    J. Mol. Biol.

    (2001)
  • LodishH. et al.
  • JentschT.J. et al.

    Molecular structure and physiological function of chloride channels

    Physiol. Rev.

    (2002)
  • AntoninE. et al.

    Hemoglobin and Myoglobin in their Reactions with Ligands

    (1971)
  • PrangeH.D. et al.

    Physiological consequences of oxygen-dependent chloride binding to hemoglobin

    J. Appl. Physiol.

    (2001)
  • OesterheltD.

    Structure and function of halorhodopsin

    Isr. J. Chem.

    (1995)
  • MobleyH.L. et al.

    Energetics of plasmid-mediated arsenate resistance in Escherichia coli

    Proc. Natl Acad. Sci. USA

    (1982)
  • RosenB.P. et al.

    Calcium, sodium, phosphate and arsenate transport in cells and vesicles of Escherichia coli

    Prog. Clin. Biol. Res.

    (1984)
  • KandelE.R. et al.

    Principles of Neural Science

    (2000)
  • Gerbl-RiegerS. et al.

    Nucleotide and derived amino acid sequences of the major porin of Comamonas acidovorans and comparison of porin primary structures

    J. Bacteriol.

    (1991)
  • RouxB. et al.

    The cavity and pore helices in the KcsA K+ channel: electrostatic stabilization of monovalent cations

    Science

    (1999)
  • NoskovS.Y. et al.

    Control of ion selectivity in potassium channels by electrostatic and dynamic properties of carbonyl ligands

    Nature

    (2004)
  • Cited by (0)

    View full text