Modeling of the Zn2+ binding in the 1–16 region of the amyloid β peptide involved in Alzheimer’s disease

Modeling of the Zn2+

binding in the 1–16 region of the amyloid bpeptide involved in Alzheimer’s diseasew

Sara Furlan and Giovanni La Penna

Received 18th December 2008, Accepted 24th April 2009

First published as an Advance Article on the web 27th May 2009

DOI: 10.1039/b822771c

Zinc ions are found at mM concentration in amyloid plaques of Alzheimer’s disease and the role

of zinc in protein oligomerization is the object of intense investigations. As an in vitro model for

studying interactions between Zn2+ and the Ab peptide, that is the main component of plaques,

the N- and C-termini protected Ab(1–16) fragment has been chosen because reliable spectroscopic

studies in water solution are possible due to the low propensity for oligomerization at pH B 6.5,

and because all the Zn binding sites of Ab have been identified in the 1–16 region. In this work

we present the results of first principle simulations of several initial models of Zn-Ab(1–16)complexes. The NMR results about the same system, where His 6, 13, 14 and Glu 11 side-chains

coordinate the Zn ion, are strongly supported by these models. Coordination of Asp 1 to Zn

drives the complex towards the expulsion of one of initially bonded His side-chains. Coordination

of Tyr 10 to Zn is possible only when Tyr 10 is deprotonated. The interplay between

physico-chemical properties of the Ab ligand and the Zn coordination is discussed.

1. Introduction

Alzheimer’s disease (AD) is the most common neuro-

degenerative cause of dementia, for which no pharmacological

treatment is available at present. Morphological hallmarks

of AD are extracellular amyloid plaques1 and intracellular

neurofibrillar tangles. The plaques are protein aggregates

mainly constituted of a peptide called amyloid b (Ab),2,3 of

40 and 42 residues, but high concentrations (up to mM) of Zn,

Fe and Cu ions are also found.4–6 This latter observation is

part of a large body of evidence indicating that transition

metal ions, their dyshomeostasis in the brain and abnormalities

in their metabolism are directly involved in the neuro-

degenerative process (see ref. 7 and references therein).

In vitro studies revealed that Zn and Cu ions promote the

aggregation of Ab (see ref. 8 and references therein), and that

contaminating trace amounts of metals (i.e. concentrations

lower than mM) were necessary for fibril formation.9–11 These

latter observations must be correlated with the conjecture that

soluble oligomeric forms of Ab, rather than more aggregated

forms like protofibrils and fibrils, are the most toxic species.12–15

This is particularly important in devising strategies to detect

the pathological disorder and its causes in early stages, before

neurodegeneration becomes devastating. The investigation

of a possible role of low-levels metal ions in promoting

(or eventually protecting from) the formation of soluble

oligomers is, therefore, of utmost importance. Among the

various metal ions, Zn is the most abundant in AD plaques

(up to 1 mM).4 Zn is released into brain synapses, during

signal transmission, atB200–300 mM16 and the distribution of

Zn in normal brain resembles the areas of the brain most

prone to amyloid deposition.17 Zn ions can promote in vitro

aggregation and formation of protease-resistant aggregates,18

even though Zn may be neuroprotective attenuating Abtoxicity in cortical cultures.19 To explain the different role of

Cu and Zn in Ab oligomerization, the competition between Zn

and Cu in Ab binding has been invoked: Zn in cells can reach

concentrations higher than Cu and, despite its generally lower

affinity for Ab, Zn can displace Cu, thus inhibiting Ab redox

chemistry otherwise activated by Cu binding.7,8

The binding sites for Zn are located in the first 16 aminoacids

of Ab and studies involving the peptide of 40 residues

(Ab(1–40)) agree on the fact that most of the residues involved

in Zn binding are shared also by Cu.20,21 The truncated

peptide Ab(1–16) shows low tendency to aggregate under

physiological concentrations (up to mM), when it is neutralized

at N- and C-termini and at pH only slightly lower than

physiological (6.5).22–25 It is, therefore, a good model for

studying both the metallated and non-metallated soluble Abpeptide. For this reason, intensive spectroscopic studies on

Ab(1–16) have been undertaken.21–24,26 Among these studies,

the proposed NMR structure of the monomeric Zn-Ab(1–16)complex is particularly elucidative.24 In fact, if the involvement

of three histidine side-chains (His 6, 13 and 14) in the Zn

binding is observed in most cases, the fourth Zn ligand is still

controversial. In the literature Asp 1,8,20 Arg 5,27 Glu 11,24

Ser 820 and Tyr 10.26 have been proposed. Asp 1 has been

considered as the most attractive candidate for Zn binding

also for its possible involvement of the N-terminus in

binding.8,20

In order to clarify the Zn coordination in the monomeric

Ab, we analyse in this work the results of first-principle

molecular dynamics simulations28,29 (in the frame of the

Car–Parrinello scheme, CP-MD hereafter) for several models

National research council, Institute for Chemistry of Organo-MetallicCompounds, via Madonna del Piano 10, I-50019 Sesto fiorentino(Firenze), Italy. E-mail: [email protected] Electronic supplementary information (ESI) available: Trajectories;parameters used for empirical models of Zn-Ab(1–16) complexes. SeeDOI: 10.1039/b822771c

6468 | Phys. Chem. Chem. Phys., 2009, 11, 6468–6481 This journal is �c the Owner Societies 2009

PAPER www.rsc.org/pccp | Physical Chemistry Chemical Physics

of Zn2+ ions interacting with the 1–16 region of the Abpeptide. The information about the nature of the configurations

provided by these simulations allows to monitor the stability

of local minima against thermal fluctuations that represent

room conditions. This information is combined with empirical

models for the solvation environment.

In the present study, the classical and quantum chemical

portions of the problem are separated: (i) The set-up of initial

configurations for first-principle molecular dynamics simulations

in the vacuum includes only a rough model for interactions

between Zn2+ and its ligand polypeptide, with the aim of

including excluded-volume effects in the initial models. (ii)

First-principle molecular dynamics simulations do not include

a model for the solvent, except for the effect of the thermal

bath, with the aim of monitoring the resistance of the initial

models to thermal fluctuations. (iii) The estimate of solvation

free energy for empirical models generated as in (i) is, again,

totally empirical and neglects solute polarization. More

detailed techniques like combined quantum mechanics and

molecular mechanics (QM/MM)methods30 and the development

of third-generation force-fields31 are more suited for a

complete study of Ab affinity for metal ions and for proposing

less-biased structures of related complexes. The work reported

in the following aims to provide a preliminary estimate of the

different role of excluded-volume, metal ion coordination and

solvent long-range effects before a full admixture of these

effects be made in a more complete modeling investigation.

2. Methods

If a possible structure with His 6, His 13, His 14 and Glu 11

bonded to Zn is available (PDB code 1ZE924), structural

models with Asp 1, Arg 5, Ser 8 and Tyr 10 side-chains

bonded to Zn2+ in place of Glu 11 and in addition to the

three His residues, are missing. In order to build these missing

models, we used a method based on the construction of

‘‘reasonable’’ biased random walks (RWs, hereafter): random

temperature hybrid Monte Carlo trajectories32,33 are performed

on empirical models of the peptide chain attached with a given

topology to the metal ion. The method is summarized in the

following. The hybrid Monte Carlo scheme is particularly

suited for such system with Zn introducing a knot in the

peptide. Moreover, the usage of a hybrid MC scheme prevents

the occurrence of unstable trajectories as it often happens

in the case of high-temperature MD (both empirical and

QM/MM) simulations. High temperatures are necessary to

improve the ligand exchange around the Zn ion.

2.1 Random walks generalities and building of starting

CP-MD configurations

We adopted an empirical force-field, in this case the PARM94

Amber force-field34 with modifications for correcting a-helixpropensity35 and parameters to bond Zn to His side-chains.36

These latter parameters are also reported in the ESI.w Since theempirical model here applied is constrained in such a way as to

build a set of reasonable (not overlapped) initial configurations

for CP-MD simulations, more recent developments in force-fields

for Zn environments37,38 are not expected to provide significant

differences. Once a force-field has been chosen and an initial

configuration is generated, a random temperature is assigned

and velocities are generated according to a Maxwell–Boltzmann

distribution corresponding to the given temperature. A classical

time-reversible molecular dynamics (MD) move is performed

and the final configuration is accepted or rejected according to

hybrid Monte Carlo scheme, i.e. the standard Metropolis test

based on the total energy change and to the initially assigned

temperature.39 Then a new random temperature is extracted

and the process repeated. The time-step and the number of steps

for the MD run are calibrated to have a compromise between

acceptance ratio and extent of configuration displacement.

The sequence of the 1–16 region of Ab was used:

H2N-Asp-Ala-Glu-Phe-Arg-His-Asp-Ser-Gly-Tyr-Glu-Val-

His-His-Gln-Lys-NH2

The peptide was neutralized in the N- and C-termini with

amino groups, in order to make possible the approach of

Zn by the N-terminus of Asp 1 and to better mimic the

experimental conditions used for determining the NMR

structure. His 6 and 14 are bonding Zn with Nd1 (i.e. they are

protonated in Ne2), while His 13 is bonding Zn with Ne2 (i.e. it

is protonated in Nd1), like in all of the 20 structures proposed on

the basis of NMR data24 (PDB entry 1ZE9). In order to bias

configurations with selected Zn ligand atoms in the fourth

coordination position, we distributed an additional charge of

�1 |e| to the point charges of amino terminal group of Asp 1, to

the two guanidinic groups of Arg 5 and to the hydroxyl groups

of Ser 8 and Tyr 10. The point charges of carboxylate groups in

Asp 1, Glu 3, Asp 7 and Glu 11 were not modified.

We performed a RW of 40000 000 MD runs of 10 time-steps

each, with an acceptance rate of about 80%. The cut-off for non-

bonding interactions was 5 A in order to adequately sample

swelled configurations, being the water solvent neglectedin the

force-field. The maximal random temperature was 10000 K. The

integration algorithm for MD moves was a time-reversible

multiple-time step velocity Verlet.39 A total amount of 40 000

configurations was collected for further analysis.

From this set of configurations, we extracted configurations

with selected atoms (N, Od of Asp 1, NZ of Arg 5, Og of Ser 8,OZ of Tyr 10, Oe of Glu 11) within a distance of 3 A from Zn.

Models will be identified with capital letters identifying the

Zn-bonded residue:

ASP1N – N (Asp 1) close to Zn

ASP1 – Od (Asp 1) close to Zn

ARG5 – NZ (Arg 5) close to Zn

SER8 – Og1 (Ser 8) close to Zn

TYR10 – OZ (Tyr 10) close to Zn

GLU11 – Oe (Glu 11) close to Zn

After this selection, the bias in the force-field was removed,

six configurations (one configuration for each of the models

ASP1, ASP1N, ARG5, SER8, TYR10 and GLU11) were

merged into an orthorhombic supercell of explicit TIP3P40

water molecules and the energy of the system was minimized

with respect to all atoms’ positions. These operations were

performed with GROMACS.41 Tentative constant temperature

MD simulations at T = 300 K of 1–2 ns, performed after two

thermalization steps of 100 ps at, respectively, T = 100 and

200 K showed that in all cases the fourth ligand escapes from

the Zn coordination sphere during thermalization. This indicates

that electrostatic interactions are not sufficient to keep the

This journal is �c the Owner Societies 2009 Phys. Chem. Chem. Phys., 2009, 11, 6468–6481 | 6469

fourth ligand at close distance from Zn. This occurs also

when the atom is a carboxylate oxygen. The configurations

minimized in the explicit water model, were used for the

following CP-MD simulations.

2.2 CP-MD simulations

First-principle molecular dynamics simulations are extremely

demanding in terms of computer time and resources, mainly

because of the short time step necessary to keep the electron

density close to the ground state during the extended dynamics

and to the many variables needed to represent electron density

via Kohn–Sham states in the density functional theory (DFT)

approach. A series of equilibration steps are required for

slowly driving the system, initially in a local energetic minimum,

towards configurations sampled at room temperature. After

these equilibration steps, simulation times of about 1–2 ps can

be acquired on available high performance computer clusters.

These simulations are not long enough to allow a reliable

statistical analysis. Nevertheless, the information about the

nature of the configurations that are sampled within these

short time windows is very rich, because it allows to monitor

the stability of local minima against thermal fluctuations that

represent room conditions and the possible presence of

low-barrier hydrogen-bond networks that can provide

mechanisms for proton transfers. This measure is performed,

in this work, without adding empirical contributions to forces

that can be introduced in a QM/MM scheme. Since the

QM/MM MD approach is still very demanding,30 a further

step, in the direction of conformational sampling and model

extension, could be done after an ad hoc development of the

force-field for the Zn environment.31

In performing CP-MD simulations of the various models, in

order to reduce the necessary computational resources, some

of the atoms initially far from the Zn atom were removed and

terminations modified accordingly. For ARG5, SER8, TYR10

and GLU11 the first four residues:

H2N-Asp-Ala-Glu-Phe

and the last two residues:

Gln-Lys-NH2

were replaced with amino groups. For ASP1 and ASP1N

models, only the last two residues were replaced by an amino

group. The number of atoms and electrons were, respectively,

219 and 666 for ASP1 and ASP1N models, and 167 and 504

for the other models.

The parallel version of the Quantum-ESPRESSO package42

which incorporates Vanderbilt ultra-soft pseudopotentials43

and the PBE exchange–correlation functional44 was used in

all CP-MD simulations. Electronic wave functions were

expanded in plane waves up to an energy cutoff of 25 Ry,

while a 250 Ry cutoff was used for the expansion of the

augmented charge density in the proximity of the atoms, as

required in the ultra-soft pseudopotential scheme. The choice

of ultra-soft pseudopotential is dictated by the fact that heavy

atoms, like the ones present in our systems, would have

required an impossibly high energy cutoff if standard norm

conserving pseudopotentials were employed.43 Calculations

performed with this DFT approximation well compares with

DFT results reported for the Zn2+-Imidazole complex.45 Even

if the DFT energy of coordination compounds does not well

compare with Hartree–Fock results, it is widely recognized

that DFT calculations better reproduce experimental thermo-

dynamic and structural features for compounds ranging from

organo-metallic catalysts to protein active sites (see ref. 30 and

references therein).

To minimize finite volume effects periodic boundary condi-

tions are, as usually, imposed to the system. Each initial model

for the Zn-peptide complex is inserted in a supercell with

sufficiently large linear dimensions to ensure a separation

between nearest-neighbor replicas of the system so as to have

negligible spurious self-interactions. Being all of the systems

charged, we have chosen a separation of 8 A.

All CP-MD calculations were performed under spin-

restricted conditions. Simulations have been carried out

according to the following general protocol consisting of the

four sequential steps listed below.

1. Minimization of electronic energy with fixed atomic

positions.

2. Minimization of total energy as a function of both atomic

and electronic degrees of freedom.

3. A few preliminary sequential CP-MD simulations of

0.3–0.6 ps each at fixed increasing atomic temperatures from

50 to 300 K. In every simulation the atomic temperature is

held fixed by a Nose–Hoover thermostat.46

4. Final CP-MD simulation at an atomic temperature of

300 K, using the same thermostat as in 3.

The thermalization procedure described in step 3 is necessary

to slowly reach room temperature and thus avoiding temperature

oscillations that may affect in an uncontrolled way the

approach of electrons to their ground state. The velocity-

Verlet algorithm39 for integrating the CP-equations of motion

was used with a time step of 0.12 fs. The time spent during

the different phases of the simulations are summarized in Table 1

for those systems that kept the initial Zn coordination after the

energy minimization step 2. All calculations were performed on

16 computational nodes on the JUMP IBM cluster of the John

von Neumann institute for computing (Julich, Germany) and on

the BCX Linux cluster of Cineca (Bologna, Italy).

In order to study the energy and the charge density in some

selected configurations, the energy is minimized with respect

to electron density via a self-consistent approach. The

Table 1 Summary of CP-MD simulation stages. Simulation times are in ps and temperatures are reported in K within brackets

Model Build-up Thermalization Simulation

ASP1N RW 0.60 (50) + 0.30 (150) —ASP1 RW 0.55 (50) + 0.32 (150) + 0.31 (200) + 0.24 (250) 1.70 (300)SER8 RW 0.73 (50) + 0.39 (150) + 0.21 (200) + 0.22 (250) 1.72 (300)TYR10 RW 0.51 (50) + 0.28 (150) + 0.14 (200) + 0.28 (250) 1.90 (300)GLU11 NMR 0.34 (50) + 0.33 (150) + 0.37 (200) + 0.29 (250) 1.81 (300)


Makov–Payne correction for the energy is applied.29 The

resulting charge density is analysed in terms of atomic basins47

by calculating via finite difference methods the density gradient

in the finer grid provided by the larger plane-waves cut-off

used in the calculation (250 Ry, i.e. each grid point has a side

of 0.10 A). The program described in ref. 48 has been used.

2.3 Solvation analysis

A mean-field empirical model for the solvent was used to

measure the contribution to potential energy of the complex in

water. For each configuration with atomic positions spanned

by the 3Na (Na number of atoms) component vector r, the free

energy of solvation is:

DGsolv(r) = DGnopol(r) + DGpol(r). (1)

The first term on the right-hand side, DGnopol, is the contribution

to the solvation free energy due to the formation of a cavity of

zero charge density with the shape of the solute and to the

creation of the solute–solvent interface. The introduction of a

charge density in the space occupied by the solute gives the

second contribution, DGpol. The charge density is given in

terms of the point charges qi of atom i in the modified Amber

force-field, where i runs over the Na atoms in the molecule.

These point charges are located in the positions ri of the given

molecular configuration r.

The term DGnopol is calculated as a linear combination of the

solvent accessible surface areas (SASAs) of each group in the

solute molecule:49

DGnopol ¼XNa

i

siSASAi ð2Þ

with the coefficients si positive and negative for hydrophobic

and hydrophilic groups, respectively.

The electrostatic contribution to the solvation free energy,

DGpol, is the electrostatic energy for charging the solute

molecule with an arbitrary shape and it is obtained by

numerical finite difference solution of the Poisson equation.50

A grid of cubic finite elements with side of 0.0875 nm was used.

Each configuration of the complex was placed in the center of

an orthorhombic cell providing at least 1 nm of boundary

dielectric in every direction of space. The electrostatic

potential was set to zero at the cell boundaries. The solvation

energy is obtained in terms of the interactions between the

atomic point charges and the polarization surface charge

density placed on the solute–water interface.51,52

The evaluation of SASA of each atom was performed using the

‘‘Numerical Surface Calculation’’ (NSC) code53 with a density of

122 points per unit sphere. The SASA of each group was

calculated using the van der Waals radii of the same Amber

PARM94 force-field used in the empirical calculations, with the

exception of Zn for which a zero van der Waals radius was

adopted. The probe radius was 1.4 A. The si coefficients of

eqn (2) were taken from literature49 and, for DGpol, the relative

dielectric permittivity was 1 inside the solute and 80 in the solvent.

Six different random walks were simulated. For each of

three selected systems (ASP1, TYR10, GLU11) two separate

RWs were simulated, one with four bonds connecting Zn to

the peptide ligand and one with only the three His residues

bonded to Zn, with the topology of the NMR structure. The

parameters used to keep Zn bonded to oxygen are reported

in the ESI.w The three RWs with Zn bonded only to His

residues span the same configurations for the three systems,

while the three RWs with four bonds span configurations

consistent, respectively, with each of the three different

four-fold coordinations assumed for Zn.

For 10 000 configurations acquired in each of these six RWs,

the solvation free energy was computed and analysed in the

following, for a total amount of 60 000 samples of the quantity.

3. Results

3.1 Building CP-MD starting structures

By performing the biased random walks on the Zn-Ab(1–16)molecule, with Zn bonded to the three His side-chains with

Table 2 Number of configurations with the distance between Zn andselected atoms within 3 A obtained in the random walk with Znbonded to three His side-chains with the topology of the NMRstructure. The total number of configurations analysed is 40 000

Atom Number of configurations Percentage

Asp 1

N 1 —Od1 13 533 34Od2 14 646 37

Glu 3

Oe1 1643 4Oe2 889 2

Arg 5

NZ1 1 —NZ2 1 —O 316 1

His 6

O 9647 24

Asp 7

Od1 5145 13Od2 4589 11O 737 2

Ser 8

Og1 11 497 29O 381 1

Tyr 10

OZ 10 959 27

Glu 11

Oe1 19 977 50Oe2 18 509 46

His 14

O 623 2


one of the possible topologies proposed according to NMR

data, the difficulty of obtaining by chance configurations with

a fourth ligand within a coordination distance (assumed here

of 3 A) is an indication of the constraints imposed by the

peptide topology to the fourth ligand, mostly as an excluded-

volume effect. In Table 2 the number of configurations with

selected atoms within 3 A from Zn is reported. For instance,

despite the identical force-field assumed for Glu 3 and Glu 11,

the Oe1 atom of the first residue enters the coordination sphere

in 4% of the collected configurations, while the same atom of

Glu 11 for 50% of the configurations. Moreover, the carbonyl

oxygen atom of His 6 has only slightly less chances to get close

to Zn than hydroxyl oxygen atoms of Ser 8 and Tyr 10:

carbonyl oxygen is a suitable ligand for Zn2+, as it is found

in many crystal structures.

Despite the bias introduced in the force-field to sample

configurations, those with N atoms bonded to Zn (N (Asp 1),

NZ (Arg 5)) are represented only once for each of the two

cases, respectively. On the other hand, the carboxylate atoms

of Asp 1 and Glu 11 are by far the atoms that have the largest

chance to get close to Zn.

Further information on the accessibility of Zn to different

ligands can be obtained by analysing the direction by which

Glu 11, Ser 8, Tyr 10 and Asp 1 side-chains can approach Zn.

We monitored the angles Cd (Glu 11)-Zn-Cg (Asp 1), Cd(Glu 11)-Zn-Cb (Ser 8) and Cd (Glu 11)-Zn-Cz (Tyr 10) whenthe distances between Zn and the atoms involved in the angles

above are smaller than 5 A. In Table 3 the statistics of these

parameters are summarized. Of the configurations with Cd(Glu 11) and Cg (Asp 1) within 5 A from Zn (i.e both atoms

approaching Zn), only one configuration displays an angle

smaller than 901, while when Cg (Asp 1) is replaced by Cz(Tyr 10), 2/3 of the configurations display an angle smaller

than 901. This observation shows that the approach of Asp 1

towards Zn occurs from the side opposite to that of Glu 11,

while Tyr 10 in most cases competes with Glu 11 from the

same side. Ser 8 competes with Glu 11 in less cases than Tyr 10

and the competition occurs from opposite sides in most cases

(64%). The larger Asp 1-Glu 11 distance in the peptide

sequence compared to that of Ser 8/Tyr 10-Glu 11 is not

sufficient to explain this result: since there are no bending

forces of type X-Zn-X (see ESIw) there are no forces or

constraints, except those acting between the atoms of the

polypeptide ligand, preventing an approach of Asp 1 from

the same side of Glu 11.

Selected configurations, with different putative Zn coordination

found in the RW, were merged in a bath of explicit water

molecules and were simulated via classical MD with only His

bonded to Zn explicitly (see the Methods section). In all of

these MD simulations, the fourth atom within the Zn

coordination sphere was observed moving away from Zn,

independently from the atom type and point charge in the

model. In most of the cases, like ASP1 and GLU11,

the charged groups initially close to Zn become extensively

surrounded by water molecules. In some cases, like ARG5, the

charged groups initially close to Zn tend to form salt-bridges

with oppositely charged groups in the peptide side-chains:

for instance, Arg 5 guanidinium group immediately form a

salt-bridge with Asp 7 carboxylate. The hydroxyl groups tend

to form hydrogen bonds with carbonyl oxygen atoms. The

carbonyl groups, when in the nearby of Zn, tend to point the

oxygen atom towards Zn.

Despite the crude approximation for the Zn coordination

assumed in the empirical MD model, a general conclusion is

that there is no evidence of any electrostatic interaction

favoring the proximity of negatively charged groups (carboxylate)

or highly polar groups (hydroxyl) to Zn. On the other hand,

the same groups appear propense to form interactions with

the solvent (carboxylate) or with backbone carbonyl groups

(hydroxyl).

3.2 CP-MD simulations

In this section the CP-MD simulations of those systems that

passed through the empirical treatment (except the empirical

MD) are discussed. The starting structures for CP-MD

simulations of Zn coordinated to Ab(1–16) as in the four

models ASP1, SER8, TYR10, GLU11, and analysed in the

following, are displayed in Fig. 1 (panels A, B, C and D,

respectively). The structures displayed are those geometry

optimized within the same DFT approach used in CP-MD

simulations (see the Methods section). As an example of the

extent of conformational changes occurring during CP-MD

trajectories at 300 K, the coordinates of ASP1 model are

provided in the ESIw as an archive file.

3.2.1 Asp 1 (ASP1 model). The starting structure for

CP-MD simulation of Zn coordinated by three His and one

of the oxygen atoms of the carboxyl group of Asp 1 is

displayed in Fig. 1A. This coordination is stable up to the

end of the CP-MD thermalization (see Fig. 3A).

The time evolution at T = 300 K of distances involving Zn

and atoms initially bonded to it are displayed in Fig. 2A.

For the initial 0.4 ps of the simulation the Zn ion is still

coordinated by Nd1 (His 6) (red line), Ne2 (His 13) (green),

Nd1 (His 14) (blue) and Od1 (Asp 1) (light blue). After this

time, the bond between His 13 and Zn is broken and slowly

Od2 (Asp 1) (magenta) enters into the coordination sphere

and Asp 1 carboxylate group becomes bidentate with a Zn

coordination still approximately tetrahedral. The breaking of

Zn–Ne2 (His 13) bond occurs because of the strengthening of

the bond between His 14 and Zn; the proton He2 of His 14 is

transiently extracted by Asp 7 and the His 14 side-chain

becomes an imidazolate anion during time within 0.4 and

0.8 ps. The narrow oscillation in time of the distance Nd1(His 14)-Zn (blue) is the hallmark of this transformation. The

deprotonation of NH groups in imidazolyl side-chains of His

by carboxylic groups often occurs in CP-MD simulations in

the vacuum54 when His side-chains are bonded to metal ions.

Table 3 Number of configurations with the distances Zn–Cd (Glu 11)and Zn-X smaller than 5 A (first column) and with the furthercondition of the angle Cd (Glu 11)–Zn-X lower than 901. The totalnumber of configurations analysed is 40 000

AtomNumber ofconfigurations

Number of configurations(percentage of second column)

Cg (Asp 1) 10 758 1 (0)Cz (Tyr 10) 6918 4674 (68%)Cb (Ser 8) 1497 536 (36%)


This event produces a transient imidazolide anion that, to be

stabilized, could bind a second Zn ion, as shown by most of

crystal structures of small Zn-imidazole complexes (see Dis-

cussion below), thus favouring Zn-mediated aggregation.

An analysis of the close contacts between Asp 7 and several

side-chains of other residues performed in the configurations

collected in the RW, shows that the approach of Od (Asp 7) to

Nd1 or Ne2 atoms of His side-chains is 4 times larger for

His 6 and 14 compared to His 13. His 13 is more protected by

the peptide from the approach of Asp 7, thus reducing

the probability of strengthening the bond with Zn because

of a transient imidazolide nature of His side-chain. This

observation supports a statistical weakening of His 13-Zn

bond compared to His 6 and His 14.

The stability of the bonds between Asp 1 carboxylate

oxygens and Zn, also considering the significant change of

Zn coordination upon His 14 transient deprotonation, indi-

cates that the interaction between Zn and carboxylate oxygen

atoms is strong.

3.2.2 Ser 8 (SER8 model). The starting structure for

CP-MD simulation of Zn coordinated by three His and the

Og oxygen atom of the Ser 8 is displayed in Fig. 1B. In most of

the structures obtained with the RW, Ser 8 points to Zn from

Fig. 1 Starting structures for CP-MD simulations of Zn2+ bonded to Ab via His 6, 13, 14 and, respectively, Asp1 (model ASP1, panel A), Ser 8

(model SER8, panel B), Tyr 10 (model TYR10, panel C) and Glu 11 (model GLU11, panel D). Color scheme is: C atoms are grey, H white, O red,

N blue, Zn green. This and the following molecular structures are represented using the program VMD.62


the same side of the three His side-chains and the initial

structure is largely distorted compared to a regular tetrahedral

Zn coordination. Indeed, during thermalization the hydroxyl

oxygen of Ser 8 is replaced with the carbonyl oxygen of His 6

in the bond with Zn (Fig. 2B and Fig. 3B). The CO

group actually comes from the side opposite to the three His

side-chains and, therefore, forms a more regular tetrahedral

coordination. In the same time of Ser 8 extrusion from the

coordination sphere, the side-chain of Ser 8 forms an hydrogen

bond first with Tyr 10 and later with the carbonyl oxygen of

Asp 7, with all these side-chains pointing away from the

Zn ion. A representative structure (the configuration with

minimal energy along the T = 300 K trajectory) is displayed

in Fig. 3B. Tyr 10 caps the 3N1O coordination of Zn to

possible solvent access. The distance between Zn and O (His 6)

is 2.15 A, consistent with similar weak bonds detected for Cu

complexes in polypeptides.55

3.2.3 Tyr 10 (TYR10 model). The starting structure for

CP-MD simulation of Zn coordinated by three His and the

OZ oxygen atom of Tyr 10 is displayed in Fig. 1C. This

coordination is stable up to the end of the CP-MD thermalization.

The time evolution at T = 300 K of distances involving Zn

and atoms initially bonded to it are displayed in Fig. 2C.

For the initial 0.3 ps of the simulation the Zn ion is still

coordinated by Nd1 (His 6) (red line), Ne2 (His 13) (green),

Nd1 (His 14) (blue) and OZ (Tyr 10) (magenta). After 0.3 ps

the bond between Tyr 10 and Zn breaks and the OZ oxygen of

Tyr 10 is replaced in the Zn coordination sphere by the

carbonyl oxygen of His 6 (light blue line in the same figure).

This behavior is similar to that occurring for the initially

Zn-bonded Ser 8 residue (see above) and indeed the first part

of the trajectory for the two systems (SER8 and TYR10)

displays a very similar behavior: when Tyr 10 OZ atom is at

distances from Zn of about 5 A (at about t = 0.7 ps in

Fig. 2C), the whole structure of the peptide ligand is similar to

the structure displayed in Fig. 3B; after a short time, this

transient structure changes, Tyr 10 moves farther away from

the Zn site, with the other part of the ligand not significantly

altered in structure. It is important to notice that OZ of Tyr 10

is able to bond Zn (in the first 0.3 ps of the T = 300 K

trajectory) because of the hydrogen bond of HZ (Tyr 10) with

O (His 6). As far as this latter hydrogen bond is broken, Tyr 10

starts moving away from Zn (data not shown).

A representative structure (that with minimal energy along

the T = 300 K trajectory, in this case at the very beginning) is

displayed in Fig. 3C.

3.2.4 Tyr 10 deprotonated (TYR10� model). The phenolic

OH group of Tyr 10 is the most acidic group within the neutral

side-chains of the Ab(1–16) sequence. The pKa of Tyr

side-chain (B10) can be decreased both by the proximity of

Fig. 2 CP-MD simulations at T=300 K of Zn2+ initially bonded to Ab as in Fig. 1. Panels are labeled as in Fig. 1: model ASP1 (panel A), model

SER8 (panel B), model TYR10 (panel C) and model GLU11 (panel D). Time evolution of several distances between Zn and several ligands: Nd1(His 6) (red line); Ne2 (His 13) (green line); Nd1 (His 14) (blue line); Od1 (Asp 1) (magenta line, panel A); Od2 (Asp 1) (light blue line, panel A); Og1(Ser 8) (magenta line, panel B); O (His 6) (light blue line, panels B and C); OZ (Tyr 10) (magenta line, panel C); Oe1 (Glu 11) (light blue line,

panel D); Oe2 (Glu 11) (magenta line, panel D).


Zn ion and by the network of hydrogen bonds formed by the

bending of Tyr 10 side-chain towards His-bonded Zn. A

similar shift of pKa for Ser side-chain is unlikely (ethanol is

less acidic than water itself). Since the N-terminus is protected

by acetilation, only the ammonium group of Lys 16

(pKa 4 9.3, that of ammonium) can in theory compete with

the phenolic group of Tyr 10 in terms of acidity. Nevertheless,

Lys 16, as well as Arg 5, has a positively charged side-chain

that has less chances to approach the metal ion in the

case where this latter is coordinated by three neutral ligands

(the His side-chains). As for the peptide backbone, the

deprotonation of amide groups in the presence of metal ions

is reported in a few cases for Gly residues and where favorable

chelate effects are present.56 Even if in the model TYR10 we

were not able to identify a mechanism for Tyr 10 deprotonation,

we removed the HO proton from Tyr 10 in the structure of

Fig. 3C in order to check if the strain acting on Tyr 10

(producing the Tyr 10 movement summarized above) can

compete with the OZ (Tyr�10)–Zn bond.

The OZ–Zn bond is stable for the whole duration of a 3 ps

CP-MD simulation at T= 300 K (data not shown). As for the

Zn coordination, the three His side-chains are bonded to Zn

Fig. 3 Representative structures for CP-MD simulations of Zn2+ bonded to Ab viaHis 6, 13, 14 and, respectively, Asp 1 (model ASP1, panel A),

Ser 8 (model SER8, panel B), Tyr 10 (model TYR10, panel C) and Glu 11 (model GLU11, panel D). Color scheme is as in Fig. 1.


for the whole simulation, except Nd1 (His 6) that for 0.2 ps

reaches distances larger than 2.5 A from Zn (a behaviour

similar to Ne2 (His 13) in GLU11 model, see below). On

average, the polypeptide ligand adopts a conformation with

Arg 5, Asp 7 and Ser 8 projected towards the solvent on a

direction opposite to the Zn site and forming an extended

network of hydrogen bonds. The Tyr 10 side-chain is largely

exposed towards the solvent, thus favouring an eventual

protonation of OZ by water competing with the Zn binding.

3.2.5 Glu 11 (GLU11 model). The starting structure for

CP-MD simulation of Zn coordinated by three His and the Oeatoms of Glu 11 is displayed in Fig. 1D. Glu 11 carboxylate

becomes monodentate during CP-MD thermalization and this

coordination is kept for the whole CP-MD trajectory at T =

300 K. The time evolution at T= 300 K of distances involving

Zn and atoms initially bonded to it are displayed in Fig. 2D.

The Zn ion is coordinated by Nd1 (His 6) (red line), Ne2 (His

13) (green), Nd1 (His 14) (blue) and Oe1 (Glu 11) (light blue).

The amplitude of distance oscillation is smaller for Zn–Oe1distance than for the N–Zn distances, thus showing a stronger

O–Zn interaction compared to N–Zn. All the three His ligand

atoms reach occasionally distances larger than 2.5 A, i.e.

distances larger than those reached in other cases (see for

instance Fig. 2C). This occurs because of the hydrogen bonds

formed by Oe2 (Glu 11) (not involved in direct Zn binding)

with H amide backbone atoms of His 13 and 14. These

hydrogen bond interactions force the mutual orientation of

Oe1 (Glu 11), Nd1 (His 14) and Ne2 (His 13) to be distorted

compared to an ideal tetrahedral Zn coordination and con-

tribute to make the N–Zn bonds weaker than in the other less

constrained situations.

A representative structure (that with minimal energy along

the T= 300 K trajectory) is displayed in Fig. 3D. Even though

there are significant differences between this representative

structure and the NMR structure displayed in Fig. 5 of

ref. 24, some features are common. For instance the salt

bridge between Arg 5 and Asp 7 in both structures drives

the side-chains of the segment from Ser 8 to Tyr 10 to point

towards a direction opposite to Zn. This occurs because Arg 5

is forced to point oppositely to His 6 side-chain. Indeed, this

fact makes very difficult also to mimic the Arg 5–Zn inter-

action via random walks (see above). The arrays of electro-

static interactions involving side-chains of Arg 5, Asp 7 and

Ser 8 (this latter partially interacting with Asp 7 carboxylate

via the hydroxyl group) move the entire region far from Zn.

This force also affects Tyr 10, that has less chances to stay

close to Zn. Noticeably, the array of electrostatic interactions

and hydrogen bonds involving Arg 5, Asp 7 and Ser 8 is also

present in the NMR structure and, in this latter case, includes

Asp 1-Lys 15 side-chains. But, to keep the model GLU11

reasonably small, Asp 1 and Lys 15 were not included.

3.2.6 Asp 1 bonded to Zn via N-terminus (ASP1N model).

The further model with Zn2+ coordinated by two His side-

chains and by the carboxylate oxygen of Asp 1 together with

the terminal N amino group was simulated. The N-terminus of

the Ab(1–16) ligand can be neutral at physiological pH

because of the presence of a metal ion. The simultaneous

metal binding of oxygen (in this case Od2) and N of Asp is

favored by the formation of a six-member ring.57 The CP-MD

thermalization at T = 50 and 150 K of the ASP1N starting

structure changed completely the initial coordination: the N

atom of Asp 1 exits the coordination immediately, together

with His 13; the carboxylate group of Asp 1 tends to become

bidentate; on the other side of the Zn coordination sphere,

Og1 of Ser 8 transiently enters into the coordination sphere

and Zn becomes tetrahedrally coordinated. When the second

oxygen of Asp 1 carboxylate starts entering into the coordina-

tion sphere, Og1 of Ser 8 exits and the structure becomes

similar to that obtained with the ASP1 model: Zn becomes

coordinated by Nd1 of His 6 and 14, and by Od1 and Od2 of

Asp 1. This structure appears the most likely when His 13 is

expelled from the Zn coordination sphere.

This result indicates that the binding of Zn by amino groups

is even weaker than that by hydroxyl groups. This situation is

expected to be different when Zn2+ is replaced by Cu+2

because in this latter case the preferred square planar coordi-

nation of Cu(II) imposes more stringent geometrical con-

straints and the binding motif implying the N-terminal

amino group can become a significant advantage over other

possible coordination geometries.

3.2.7 Analysis of energy and charge density. The electron

density of selected Zn coordination geometries found in the

CP-MD simulations above was analysed as explained in the

Methods Section. The difference of absolute charge (in |e|)

calculated subtracting the value obtained with Zn2+ from the

value obtained without Zn2+ in all the Zn ligand atomic

basins, was plotted. This quantity measures the extent of

electron donation to the Zn ion from each of the ligand atoms.

In Fig. 4, the difference is displayed for some representative

configurations. The GLU11 model (structure displayed in

Fig. 3D), the TYR10 model (Fig. 3C) and the SER8 model

(Fig. 3B) are shown in panels A, B and C, respectively, of

Fig. 4. Each residue starts with the backbone NH group and

ends with the backbone CO group. The numbers in the figures

are the charge differences summed over all the atoms of each

labeled residue. As expected, the bond between carboxylate

group and Zn (Glu 11 in panel A) has a covalent character

similar to that of the bond with imidazolyl side-chains of His.

A large ionic character would be displayed by a small differ-

ence between the unbound carboxylate atoms and those

bonded to Zn. Instead, in GLU11 model the charge transfer

from ligand residue to Zn2+ is similar for Glu 11 and for the

three His residues (panel A). The presence of peaks in the plots

indicate an effect of the metal ion on the charge density of the

ligand. Interestingly, residues relatively far from the metal ions

(for instance, Arg 5 and Gly 9 in GLU11 model) are polarized

by the metal ion, especially in the backbone. In model GLU11

(panel A), the Zn ion attracts a net charge of 0.75 |e| (the

integrated electron density of the Zn basin is 10.75), and the

ligand residues identified by observing the CP-MD simulation

donate 0.6 |e| as a whole. Therefore, a charge of 0.15 |e| comes

from the other residues in the chain as the sum of many small

contributions (Arg 5 contributes, for instance, for 0.016 |e|).

In the TYR10 model (panel B), the extent of donation from

His 14 is smaller than in GLU11 (about one third), due to the


slight displacement of Zn from the imidazole plane of His 14

(data not shown). The donation from Tyr 10 (0.10 |e|) is not as

large as that of Glu 11 in GLU11 case (0.13, panel A). The

difference in energy between configuration in Fig. 3C and that

in Fig. 3D is about 250 kJ mol�1. This large energy decrease in

replacing OZ (Tyr 10) with Oe (Glu 11) as Zn ligand can be

justified with the observed increase in charge donation.

In SER8 model (panel C), where the carbonyl oxygen of His 6

is bonded to Zn (see Fig. 3B and 2B), the electron donation

to Zn comes from the three His side-chains, with His 6

donating almost the same as in GLU11, where His 6 binds

Zn with Nd1 only (Fig. 2D). Differently from the TYR10 case,

His 13 and 14 give larger contributions to the electron density

on Zn. As observed above, the configuration represented in

Fig. 4C (SER8) is similar to the final configurations that are

obtained from the density represented in Fig. 4B (TYR10, see

discussion of the TYR10 model above). Accordingly, the

energy of the configuration displayed in Fig. 3B is only a

few kJ mol�1 smaller than that of Fig. 3C. Since the situation

represented in Fig. 4C looks stable like that in GLU11

(compare Fig. 2B and D), we argue that there is not a direct

correlation between the spread on the peptide ligand of charge

donation to Zn and the stability of Zn coordination: once an

almost tetrahedral coordination of Zn2+ is reached the system

begins relaxing interactions between atoms in the ligand. The

configuration of Fig. 3B and the related charge density

represent a relatively stable state with an energy larger than

the most stable state GLU11.

3.2.8 Partial conclusions. By analyzing the time evolution at

T = 300 K of configurations modeling different type of initial

Zn coordination types, we draw the following conclusions.

� Asp 1 carboxylate binds Zn from a side opposite to that of

Glu 11 carboxylate, Tyr 10 hydroxyl and His 6 carbonyl

groups (see section 1 and compare panel A in Fig. 3 with

panels B–D of the same figure). The coordination of Asp 1

(ASP1 model) inverts the pyramidal coordination of the three

His side-chains to Zn that occurs in the other cases (SER8,

TYR10, TYR10� and GLU11).

� In the Asp 1 (ASP1 and ASP1N) cases, one histidine

(His 13) is displaced from Zn. In case ASP1 this happens during

the transient deprotonation of His 14 by Asp 7. This event

represents a possible transient state in water solution at

pH B 7 (like in NMR experiments), with the proton of

the carboxyl group rapidly transferred back to His 14.

Nevertheless, Asp 1 is strongly bonded to Zn and it can easily

stabilize the lack of one of the His side-chains, with Asp 1

carboxylate becoming bidentate. The same effect is not

possible if a monodentate ligand with similar electrostatic

nature, like Tyr 10�, binds Zn. The destabilization of one

His ligand up to the expulsion from the Zn coordination

sphere, seems a hallmark of the Asp 1 binding. Since in

Ab(1–16) the binding of three His to Zn in water solution is

an established fact,23,24 this result suggests that the additional

binding of Asp 1 to Zn is not compatible with a stable binding

of three His. This is particularly important because two of the

bonded His are very close in the sequence (see Discussion

below) and are, therefore, mechanically destabilized in Zn

bonding: the presence of a negatively charged oxygen atom

close to Zn and able to compete with one of His 13-His 14

ligand atoms is sufficient to expel one of them.

� The binding of Zn by carboxyl groups (ASP1, GLU11 and

ASP1N final configurations) is stable. On the contrary,

hydroxyl groups (especially in the Tyr 10 case) binds Zn only

transiently, when hydroxyl oxygen atoms are involved in

hydrogen bond. As far as this hydrogen bond breaks, hydroxyl

groups are displaced from Zn coordination by nearby peptide

carbonyl groups, as in both the SER8 and TYR10 cases. The

binding becomes stable if a proton is displaced by the phenolic

oxygen (pKa B 10), but the Zn-bonded oxygen appears largely

exposed to the water solvent. While Zn–N (His) binding

is stable (except for His 13 in the very peculiar case of

deprotonation of His 14), Zn binding by hydroxyl groups of

Tyr 10 is possible only when hydroxyl group is involved in

hydrogen bonds or deprotonated. Despite the hydrogen bond

involving the protonated hydroxyl group of Tyr 10 with the

carbonyl group of His 6, there are no indications on a

mechanism for the loss of HO (Tyr 10) to form a phenolate

group. The observed propensity of Tyr 10 side-chain to move

away from Zn does not allow this event to occur.

Fig. 4 Difference in valence charge integrated over atomic basins

when Zn is present and absent. Models are: GLU11 (panel A), TYR10

(B) and SER8 (C).


� Zn prefers a nearly tetrahedral coordination and no

evidence of an octahedral coordination arises from CP-MD

simulations. When Zn is bonded to carboxyl groups, these

latter are monodentate except if one of the three His

side-chains is expelled from the coordination (cases ASP1

and ASP1N, final configurations). The major distortion from

the tetrahedral coordination occurs in case GLU11, because of

strong interactions of the carboxyl oxygen of Glu 11, not

involved in Zn binding, with the backbone of His 13 and His 14.

This distortion weakens the N–Zn bonds of His side-chains

and demonstrates that weak interactions between ligand

atoms can significantly distort Zn coordination.

�When one His is released from Zn coordination, this is His

13, while the bridge His 6-Zn-His 14 appears more stable than

any other. This fact can be due to the initial Zn binding by Ne2of His 13, assumed here according to the NMR structure, but

also to the competition between Asp 1 and His 13 that share

the same portion of the Zn coordination sphere. On the other

hand, Glu 11 competes only with carbonyl and hydroxyl

oxygen atoms, that are weaker competitors in Zn binding.

Asp 7 interacts more frequently with His 14 than with His 13,

thus making the His 14–Zn bond stronger, on average, than

His 13–Zn bond.

3.3 Solvation analysis

In this section empirical solvent mean-field contributions to

the different type of Zn binding are analysed. In particular the

different extent of solvation free energy is compared for three

types of Zn-Ab(1–16) 1:1 coordination: the monodentate

coordination of Zn2+ by one of the carboxylate oxygen atoms

in Asp 1 (Od1) and in Glu 11 (Oe1), and the coordination by

OZ (Tyr 10).

In Fig. 5 the distribution of DGsolv (see eqn (1)) is compared

when obtained by the three different random walks: when Zn

is bonded to Od1 (Asp 1) (panel A); when Zn is bonded to Oe1(Glu 11) (panel B) and when Zn is bonded to OZ (Tyr 10)

(panel C). The empty boxes represent the same distribution for

Zn bonded only to the three His side-chains (no fourth ligand

present in the force-field). The central peaks of each of these

distributions represent the contribution to DGsolv of the most

likely configurations consistent with each of the three-(empty

boxes) or four-fold (filled boxes) Zn coordinations.

It can be observed that while the maximum of the distribution

is displaced towards larger DGsolv values when Asp 1 (panel A)

and Glu 11 (panel C) are bonded to Zn, in the case of Tyr 10

(panel B) the distribution is almost unchanged. This effect is

due to the large contribution to the solvation free energy of

carboxylate groups, that, when these latter are bonded to Zn,

are hidden in the molecule by the ligand. Remarkably, by

comparing the shift in average values obtained in the three

different models, when the carboxylate groups are bonded to

Zn the loss of solvation free energy is about 200 kJ mol�1. This

value can play a significant role in partially balancing energy

differences due to different coordination modes for Zn.

4. Discussion

The results reported in the previous section are discussed in the

following within the frame of other structural information

available on similar systems.

To compare the results with known crystal structures

involving the binding of Zn ion by three His side-chains,

the Cambridge structural database (CSD) was searched for

complexes of composition similar to those modeled in this

work. Structures of Zn complexes having three imidazole

ligands were analyzed. The search carried out within the

CSD 5.30 (February 2009) release58 found 38 hits. Of these

structures, only 5 structures contain monomeric complexes,

while all the other structures contain imidazolide anion bridging

two different Zn ions. In all the 5 monomeric structures, the

hydrogen attached to one of the two imidazole N is replaced

with organic residues to prevent polymerization. Moreover, in

only three cases the coordination is 5 and in none of the

searched structures Zn has a coordination number larger

than 5.

A similar search was performed for Zn ligands containing

the phenolic oxygen bonded to Zn. According to the proto-

nation state of the phenolic group deduced from the charge of

the crystal cell, only 35 structures among the 1142 found

structures contain a protonated form of phenolic group. On

the other hand 362 of these structures contain the phenolic

group bridginig two different Zn ions.

To confirm the very low acidity of hydroxyl groups in the

proximity of Zn2+ ions (see the discussion about model

TYR10� above) the CSD was searched for hydroxyl–Zn

bonds. In the CSD, 750 structures contain at least one

X-CH2–O–Zn bond, 307 structures in this set contain

X-CH2–OH group bonded to a single Zn ion (according to

the net charge of the Zn ligand), and 114 structures contain

one oxygen bonding two different Zn ions. This latter data

show that the propensity of forming polymeric structures

involving Zn–O–Zn bridges is smaller than Zn–imidazolide–Zn,

as expected by the size of the bridging anion.

The search within the crystal structures of small compounds,

therefore, indicates the following features: the acidity of the

imidazole and of phenol groups are significant when these are

bonded to a Zn ion; the propensity for the formation of

Fig. 5 Distribution of DGsolv obtained via RWs with only three His

residues binding Zn as in NMR structure (empty boxes) and with an

additional fourth Zn ligand (filled boxes). The fourth ligand atom is:

Od1 (Asp 1) (panel A); OZ (Tyr 10) (panel B); Oe1 (Glu 11) (panel C).


polymeric species with different Zn ions connected by depro-

tonated imidazole or phenolic groups is high, but, as expected

by the ligand dimensions, the propensity is higher when

imidazolide is bridging in place of phenolate; the propensity

for Zn of having coordination larger than 4 when three

imidazole groups are bonded is low. The first two features

are observed in our model ASP1, where a transient formation

of an imidazolide anion is observed, providing a possible

intermediate species for the formation of oligomers with the

Zn-Imidazolide-Zn bridge. The stability observed for the

TYR10� model is also confirming the observed stability of

crystal structures implying deprotonated phenol groups.

Finally, Zn coordinations larger than four are never observed

in our CP-MD simulations.

A comprehensive analysis of Zn binding in protein structures

has been made by analyzing the Protein data bank (PDB).59

Interestingly, in the analysis of crystal structures Zn binding

sites with two flanking His side-chains are not reported and

even the HXH motif is possible when a third His residue is

more than 20 positions away (Class II of mononuclear Zn

proteins). The binding of carboxylate groups is more likely

when only two His side-chains are bonded to Zn (Class IV).

This analysis confirms the presence of the intramolecular stress

observed with the calculations of this work: in case GLU11 the

wide oscillation of one of the bonds between Zn andNe2 (His 13)

or Nd1 (His 14) (Fig. 2D); in case ASP1 the expulsion of

His 13 from the Zn coordination sphere. The coordination that

better allows the presence of the two flanking His side-chains

binding Zn occurs when a single negatively charged oxygen is in

the Zn coordination sphere (GLU11 when only one of the Oe isinvolved in hydrogen bonds and TYR10�).

The coordination of Zn2+ by proteins in the PDB can be

also investigated with dedicated tools like MSDSite60 freely

accessible on the web. If the Zn environment involving imidazole

and carboxylic groups has not significantly changed compared

to the analysis reported in reference above for crystal

structures,59 some information is added about the interactions

of Arg, Ser and Tyr side-chains with Zn. There are 39, 12 and 7

structures with Ser, Tyr and Arg, respectively, interacting

with Zn. Among these, 25, 6 and 5, respectively, are found

covalently bonded to Zn, i.e. with side-chain atoms at a

distance from Zn smaller than the sum of involved covalent

radii. This result, even if strongly biased by the data base of

crystal structures, shows that the binding of Zn to Tyr

side-chain is much less likely than for Ser, with this latter

side-chain protonated because of its low acidity. The low

frequency of the Arg binding to Zn is expected by the pKa

of guanidinium (B12.5), being this group less acidic than Tyr

side-chain and being the Arg side-chain more flexible. From

our models we obtained an almost negligible frequency of

contacts between NZ (Arg 5) and Zn in the biased RW (see

Table 2) where the positive charge of Arg was neutralized and

the positive charge of Zn was 0.5 because of charge transfer

towards the bonded His (see the tables in the ESIw). Moreover,

in most of the CP-MD simulations Arg 5 is projected towards

the solvent and often involved in salt-bridges with Asp 7.

The discussion of a possible equilibrium involving several

Ab species with different Zn coordination, has been recently

raised.61 The mutation H13R in the Ab sequence of rat can be

related to the low propensity of this sequence to bind Zn and,

consequently, to the low propensity to aggregate when Zn2+ is

added to the Ab solution. Despite the different molecular size

(Ab(1–28)) and the different molecular environment (SDS

micelles) used in the work reported in ref. 61, for the human

sequence the question whether Zn is bonded to N (Asp 1) or,

alternatively, to Oe (Glu 11) is not definitely answered, while

the binding of Zn to His 6 and 14 is confirmed. However, the

more hydrophobic environment of this NMR experiment,

compared to that reported in ref. 24, can provide a free energy

difference compensating for the energy difference between

Asp 1 and Glu 11 coordinations of Zn.

The spectrum of different results that are obtained for

the truncated complex Zn-Ab(1–16) and through in vitro

experiments, can be often interpreted in terms of formation

of oligomeric structures (see for instance ref. 8 and 21 and

references therein). We remark that our model aims at

explaining data on the monomeric complex Zn-Ab(1–16):the presence of the monomeric form is guaranteed, for

instance in NMR experiments, by the N- and C-termini

neutralization23 and by pH = 6.5.24,25 This pH is imposed

also to minimize the possible transient presence of

deprotonated His, Tyr and Arg side-chains bonded to metal

ions, that can act as possible perturbation of Zn coordination

as observed in our models. Imidazolate side-chains can act as

bridging group for two metal ions, as observed in Cu,

Zn-superoxidedismutase, in some experiments on Ab26 and

in the X-ray structures of small Zn complexes with three

imidazolyl groups. Other negatively charged groups, like

deprotonated Tyr side-chain, appear less competitive than

carboxylate or imidazolide in this respect.

This situation is expected to be different when Zn(II) is

replaced with Cu(II). Since Cu(II) tends to constrain the ligand

to square planar coordination, the binding of Cu by N and Odof Asp 1, together with two His side-chains, can be favored

compared to the binding by Glu 11. The competitive binding

of Asp 1 constraints Cu towards the N-terminal portion of the

chain, possibly favoring the formation of Ab oligomers more

accessible by the solvent in the C-terminal region. In the longer

Ab(1–42) peptide, the region 34–35 is accessed by the matrix

metalloprotease 2 (MMP2) family of enzymes.18 The different

conformational landscape allowed to the C-terminal region

upon Zn and Cu binding can suggest possible interpretation

for the slower degradation of Zn-Ab(1–42) aggregates

compared to Cu- and non metallated Ab(1–42).

5. Conclusions

We built several models for a single Zn2+ ion coordinated to

region 1–16 of the Ab peptide. For each of these models, we

performed first principle molecular dynamics simulations in

the vacuum of 1–2 ps at the temperature of 300 K. The

behavior of the initially built models was analysed in terms

of: electron density, time evolution of distances involved in Zn

coordination and mean-field empirical solvation free energy of

different types of Zn coordination.

Our models provide strong support to the coordination

mode proposed on the basis of NMR data for Zn-Ab(1–16)(with acetylated and amidated N- and C- termini, respectively)


at pH B 6.5, i.e. slightly more acidic than physiological

conditions. Solvation effects, favoring the hydration of

carboxylate groups, can compete with the large propensity

for the monodentate coordination of Zn by a carboxylate

oxygen of Glu 11 only if the carboxylate group around

Zn is replaced by the deprotonated side-chain of Tyr 10.

Nevertheless, we were not able to identify a possible

mechanism for Tyr 10 deprotonation and a direct extraction

of the HO (Tyr 10) by water, assisted by O–Zn binding,

should produce a larger set of protein crystal structures with

negatively charged Tyr bonded to Zn.

The 3N1O coordination of Zn involving three His side-

chains and the carboxylate group of Asp 1 destabilizes one of

the binding histidines, promoting the extrusion of His 13 from

the Zn coordination sphere through a temporary deprotona-

tion of His 14. This event produces a 2N2O coordination with

a bidentate carboxylate of Asp 1 and two His side-chains, both

bonded to Zn via Nd1. Nevertheless, this coordination has

larger energy than the 3N1O initial coordination. The scarce

resistance to thermal fluctuations of the 3N1O coordination of

Zn with monodentate Asp 1 involved, demonstrates that

thermally accessible mechanisms for its decomposition exist.

Similar mechanisms were not observed for the 3N1O coordi-

nation involving Glu 11.

The Zn binding by hydroxyl groups of Ser 8 and Tyr 10 (in

the protonated form) is even weaker than that of favorably

located carbonyl oxygen, with O of His 6 the most prone to

interact with Zn. In water solution, the extent of water

extrusion from the binding site (favoring intramolecular

hydrogen bonds within the Zn pocket) can stabilize hydroxyl

group as a fourth ligand. But as far as carboxylic groups

approach Zn, they displace hydroxyl and backbone carbonyl

groups. Only in the case of Tyr deprotonation, this latter

residue can compete with Glu and Asp.

From the models here reported, we draw the conclusion that

a driving force that can displace carboxylate, and particularly

that of Glu 11, from the Zn coordination sphere must involve

strong interactions between the extracted carboxylate group

and other groups, eventually in other molecules when the

concentration is high. The 2N2O coordination involving His

6, His 14 and bidentate Asp 1 can be an intermediate species

towards the formation of zinc-promoted oligomers.

Investigations of models for possible structures of zinc-

promoted oligomers are in progress.

Acknowledgements

We thank P. Giannozzi and C. Cavazzoni for the many

suggestions and constant help. All calculations were

performed on 16 computational nodes on the JUMP IBM

cluster of the John von Neumann institute for computing

(Julich, Germany) and on the Linux cluster BCX at Cineca

(Bologna, Italy). Financial support from Firb 2003 project

RBNE03PX83 is acknowledged.

References

1 D. J. Selkoe, Science, 2002, 298, 289–791.2 G. G. Glenner and C. W. Wong, Biochem. Biophys. Res. Commun.,1984, 120, 885–890.

3 C. L. Masters, G. Simms, N. A. Weinman, G. Multhaup,K. McDonald and B. L. Beyreuther, Proc. Natl. Acad. Sci.U. S. A., 1985, 82, 4245–4249.

4 M. A. Lovell, J. D. Robertson, W. J. Teesdale, J. L. Campbell andW. R. Markesbery, J. Neurol. Sci., 1998, 158, 47–52.

5 F. Li, N. Y. Calingasan, F. Yu, W. M. Mauck, M. Toidze,C. G. Almeida, R. H. Takahashi, G. A. Carlson, M. Flint Beal,M. T. Lin and G. K. Gouras, J. Neurochem., 2004, 89, 1308–1312.

6 L. M. Miller, Q. Wang, T. P. Telivala, R. J. Smith, A. Lanzirottiand J. Miklossy, J. Struct. Biol., 2008, 155, 30–37.

7 K. J. Barnham and A. I. Bush, Curr. Opin. Chem. Biol., 2008, 12,222–228.

8 P. Faller and C. Hureau, Dalton Trans., 2009.9 C. S. Atwood, R. C. Scarpa, X. Huang, R. D. Moir, W. D. Jones,D. P. Fairlie, R. E. Tanzi and A. I. Bush, J. Neurochem., 2000, 75,1219–1233.

10 P. Sengupta, K. Garai, B. Sahoo, Y. Shi, D. J. E. Callaway andS. Maiti, Biochemistry, 2003, 42, 10506–10513.

11 X. Huang, C. S. Atwood, R. D. Moir, M. A. Hartshorn,R. E. Tanzi and A. I. Bush, JBIC, J. Biol. Inorg. Chem., 2004, 9,954–960.

12 D. J. Selkoe, Physiol. Rev., 2001, 81, 741–766.13 J. Hardy and D. J. Selkoe, Science, 2002, 297, 353–356.14 W. Klein, W. Stine and D. Teplow, Neurobiol. Aging, 2004, 25,

569–580.15 C. Haass and D. J. Selkoe, Nat. Rev. Mol. Cell Biol., 2007, 8,

101–112.16 C. J. Frederickson, Int. Rev. Neurobiol., 1989, 31145–311238.17 A. I. Bush, Neurobiol. Aging, 2002, 23, 1031–1038.18 P. J. Crouch, D. J. Tew, T. Du, D. N. Nguyen, A. Caragounis,

G. Filiz, R. E. Blake, I. A. Trounce, C. P. W. Soon, K. Laughton,K. A. Perez, Q.-X. Li, R. A. Cherny, C. L. Masters, K. J. Barnhamand A. R. White, J. Neurochem., 2009, 108, 1198–1207.

19 M. P. Cuajungco and K. Y. Faget, Brain Res. Rev., 2003, 41,44–56.

20 J. Danielsson, R. Pierattelli, L. Banci and A. Graslund, FEBS J.,2007, 274, 46–59.

21 V. Minicozzi, F. Stellato, M. Comai, M. Dalla Serra, C. Potrich,W. Meyer-Klaucke and S. Morante, J. Biol. Chem., 2008, 283,10784–10792.

22 Y. Mekmouche, Y. Coppel, K. Hochgrafe, L. Guilloreau,C. Talmard, H. Mazarguil and P. Faller, ChemBioChem, 2005, 6,1663–1671.

23 C. D. Syme and J. H. Viles, Biochim. Biophys. Acta: Prot.Proteom., 2006, 1764, 246–256.

24 S. Zirah, S. A. Kozin, A. K. Mazur, A. Blond, M. Cheminant,I. Segalas-Milazzo, P. Debey and S. Rebuffat, J. Biol. Chem., 2006,281, 2151–2161.

25 C. Talmard, A. Bouzan and P. Faller, Biochemistry, 2007, 46,13658–13666.

26 C. C. Curtain, F. Ali, I. Volitakis, R. A. Cherny, R. S. Norton,K. Beyreuther, C. J. Barrow, C. L. Masters, A. I. Bush andK. J. Barnham, J. Biol. Chem., 2001, 276, 20466–20473.

27 S. Zirah, S. Rebuffat, S. A. Kozin, P. Debey, F. Fournier,D. Lesage and J.-C. Tabet, Int. J. Mass Spectrom., 2003, 228,999–1016.

28 R. Car and M. Parrinello, Phys. Rev. Lett., 1985, 55, 2471–2474.29 P. Giannozzi, F. De Angelis and R. Car, J. Chem. Phys., 2004, 120,

5903–5915.30 H. M. Senn and W. Thiel, Angew. Chem., Int. Ed., 2009, 48,

1198–1229.31 N. Gresh, A. Cisneros, T. A. Darden and J.-P. Piquemal, J. Chem.

Theory Comput., 2007, 3, 1960–1986.32 G. La Penna, J. Chem. Phys., 2003, 119, 8162–8174.33 G. La Penna, S. Morante, A. Perico and G. C. Rossi, J. Chem.

Phys., 2004, 121, 10725–10741.34 W. D. Cornell, P. Cieplak, C. I. Bayly, I. R. Gould, K. M. J. Merz,

D. M. Ferguson, D. C. Spellmeyer, T. Fox, J. W. Caldwell andP. A. Kollman, J. Am. Chem. Soc., 1995, 117, 5179–5197.

35 A. E. Garcia and K. Y. Sanbonmatsu, Proc. Natl. Acad. Sci.U. S. A., 2002, 99, 2782–2787.

36 L. Banci, P. Carloni, G. La Penna and P. L. Orioli, J. Am. Chem.Soc., 1992, 114, 6994–7001.

37 Y.-P. Pang, K. Xu, J. El Yazal and F. G. Prendergast, Protein Sci.,2000, 9, 1857–1865.


38 G. Cui, B. Wang and K. M. Merz, Biochemistry, 2005, 44,16513–16523.

39 D. Frenkel and B. Smit, Understanding Molecular Simulation,Academic Press, San Diego, USA, 1996.

40 W. L. Jorgensen, J. Chandrasekhar, J. D. Madura, R. W. Impeyand M. J. Klein, J. Chem. Phys., 1983, 79, 926–935.

41 D. van der Spoel, E. Lindahl, B. Hess, G. Groenhof, A. E. Markand H. J. C. Berendsen, J. Comput. Chem., 2005, 26, 1701–1718.

42 S. Baroni, A. Dal Corso, S. de Gironcoli, P. Giannozzi,C. Cavazzoni, G. Ballabio, S. Scandolo, G. Chiarotti, P. Focher,A. Pasquarello, K. Laasonen, A. Trave, R. Car, N. Marzari andA. Kokalj, http://www.quantum-espresso.org.

43 D. Vanderbilt, Phys. Rev. B: Condens. Matter Mater. Phys., 1990,41, 7892–7895.

44 J. P. Perdew, K. Burke and M. Ernzerhof, Phys. Rev. Lett., 1996,77, 3865–3868.

45 J.-P. Piquemal, A. Marquez, O. Parisel and C. Giessner-Prettre,J. Comput. Chem., 2005, 26, 1052–1062.

46 S. Nose, Mol. Phys., 1984, 52, 255–268.47 R. F. W. Bader, Atoms in Molecules—A Quantum Theory, Oxford

University Press, Oxford, UK, 1990.48 E. Sanville, S. D. Kenny, R. Smith and G. Henkelman, J. Comput.

Chem., 2007, 28, 899–908.49 T. Ooi, M. Oobatake, G. Nemethy and H. A. Scheraga, Proc. Natl.

Acad. Sci. U. S. A., 1987, 84, 3086–3090.50 A. Nicholls and B. Honig, J. Comput. Chem., 1991, 12,

435–445.

51 W. Rocchia, S. Sridharan, A. Nicholls, E. Alexov, A. Chiabreraand B. Honig, J. Comput. Chem., 2002, 23, 128–137.

52 S. Furlan, G. La Penna and A. Perico, Macromolecules, 2008, 41,2938–2948.

53 F. Eisenhaber, P. Lijnzaad, P. Argos, C. Sander and M. Scharf,J. Comput. Chem., 1995, 16, 273–284.

54 S. Furlan, G. La Penna, L. Banci and C. Mealli, J. Phys. Chem. B,2007, 111, 1157–1164.

55 S. Furlan, G. La Penna, F. Guerrieri, S. Morante and G. C. Rossi,JBIC, J. Biol. Inorg. Chem., 2007, 12, 571–583.

56 C. S. Burns, E. Aronoff-Spencer, C. M. Dunham, P. Lario,N. I. Avdievich, W. E. Antholine, M. M. Olmstead, A. Vrielink,G. J. Gerfen, J. Peisach, W. G. Scott and G. L. Millhauser,Biochemistry, 2002, 41, 3991–4001.

57 V. Pradines, A. J. Stroia and P. Faller, New J. Chem., 2008, 32,1189–1194.

58 F. H. Allen, Acta Crystallogr., Sect. B: Struct. Sci., 2002, 58, 380.59 S. Karlin and Z.-Y. Zhu, Proc. Natl. Acad. Sci. U. S. A., 1997, 94,

14231–14236.60 A. Golovin, D. Dimitropoulos, T. Oldfield, A. Rachedi and

K. Henrick, Proteins: Struct. Funct. & Bioinf., 2005, 58, 190–199,http://www.ebi.ac.uk/msd-srv/msdsite.

61 E. Gaggelli, A. Janicka-Klos, E. Jankowska, H. Kozlowski,C. Migliorini, E. Molteni, D. Valensin, G. Valensin andE. Wieczerzak, J. Phys. Chem. B, 2008, 112, 100–109.

62 W. Humphrey, A. Dalke and K. Schulten, J. Mol. Graphics, 1996,14(1), 33–38, http://www.ks.uiuc.edu/Research/vmd/.


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