1. INTRODUCTION:
Chemical speciation of metals is important to
understand their distribution, mobility, bioavailability, toxicity and for
setting environmental quality standards.1 A number of studies has
been reported on ternary stability constants of α-amino acids in different
media.2 Investigations of acido-basic equilibria of amino and
carboxylic acids and their interaction with metal ions in media of varying
ionic strength, temperature and dielectric constant throw light on the
mechanism of enzyme-catalyzed reactions. Bioavailability of a particular metal
depends on its complex chemical reactions of dissolution, binding and
complexation with the constituents of the environmental aquatic phase.3
L-Histidine
(His) is an essential amino acid and the imidazole side chain of histidine is a
common coordinating ligand in metalloproteins and is a part of catalytic sites
in certain enzymes.
It is essential for the
growth and repair of tissues and for the production of both red and white blood
cells.
His has been used in the treatment of rheumatoid
arthritis, allergies, ulcers and anemia. L-Glutamic
acid (Glu) plays a vital role in various biochemical processes at the molecular
level. It acts as a neurotransmitter4 and a precursor of γ-
aminobutyric acid.5
Cobalt is essential for the production of
the red blood cells. Vitamin B12 acts as catalyst in a variety of
enzyme system functions and as coenzyme in several biochemical processes.6
Nickel is present in specific environments of nucleic acids or nucleic
acid-binding proteins. It is found in urease, which accounts for 6% of the
soluble cellular proteins7 and catalyses the hydrolysis of urea to
yield ammonia and carbamate. Copper containing enzymes and proteins constitute an
important class of biologically active compounds. Copper is distributed widely
in the body in liver, muscle and bones and its biological functions include
electron transfer, dioxygen transport, oxygenation, oxidation, reduction and
disproportionation.8
Dimethylsulfoxide (DMSO) is a dipolar
aprotic solvent that
dissolves both polar and non-polar compounds and is miscible in a wide range of
organic solvents as well as water. It is also used as a cryoprotectant, added
to cell media in order to prevent the cells from dying as they are being
frozen.9
Protonation and binary complex equilibria of Glu and
His with the above metals have been reported earlier.10-12 Hence,
chemical speciation of their ternary complexes is reported in the presence of
DMSO in this communication.
2. EXPERIMENTAL SECTION:
0.1 mol L-1 aqueous solutions of Co(II),
Ni(II) and Cu(II) chlorides (G.R. Grade E-Merck, Germany) were prepared by
dissolving them in triple distilled water. 0.05 mol L-1 aqueous
solutions of L-histidine and L-glutamic acid
(E-Merck, Germany) were also prepared. To increase the solubility of the
ligands and to supress hydrolysis of metal salts, 0.05 mol L-1
hydrochloric acid (Qualigens, India) was maintained in the solutions. DMSO
(Qualigens, India) was used as received. The strength of alkali was determined
using the Gran plot method.13,14 Errors in the concentrations of
ligand, metal ions and alkali were subjected to ANOVA.15 The pH
metric titrations were carried out in media containing varying concentrations
of DMSO maintaining an ionic strength of 0.16 mol L-1 with sodium
chloride (Merck, India) at 303.0 K. The pH was measured with an ELICO
(Model LI-120) pH meter of 0.01 readability in conjunction with a glass and
calomel electrode. The pH meter was calibrated with 0.05 mol L-1 potassium
hydrogen phthalate in acidic region and 0.01 mol L-1 borax solution
in basic region. The glass electrode was equilibrated in a well stirred
DMSO-water mixtures containing inert electrolyte. Titration of strong acid with
alkali was carried out at regular intervals to check whether complete
equilibration was achieved. The calomel electrode was refilled with DMSO-water
mixtures of equivalent composition as that of the titrand. In each of the
titrations, the titrand consisted of 1 mmol of hydrochloric acid in a total
volume of 50 cm3. Titrations were carried out in the presence of
different relative concentrations of the metal (M) to His (L) to Glu (X) (M: L:
X = 1:2.5:2.5, 1:2.5:5.0, 1:5.0:2.5) with 0.4 mol L-1 NaOH. The
effects of variations in asymmetry potential, liquid junction potential,
activity coefficient, sodium ion error and dissolved carbon dioxide on the
response of glass electrode were accounted for in the form of correction factor
(log F) which was computed from the experimental and simulated acid-base
titration data calculated by SCPHD program.16 The pH meter dial
readings were corrected using log F to account for the solvent effect on pH.
The best-fit chemical model for each system investigated was arrived at using a
non-linear least squares analysis program MINIQUAD7517 which
exploits the advantage of constrained least squares method in the initial
refinement and reliable convergence of undamped, unconstrained Marquardt
algorithm.
3. RESULTS AND DISCUSSION:
3.1. Exhaustive modeling:
A preliminary investigation of alkalimetric titrations
of mixtures containing different mole ratios of DMSO in the presence of
hydrochloric acid and inert electrolyte inferred that no condensed species were
formed. The protonation constants and stability constants of the binary metal
complexes of these ligands were fixed in refining ternary complexes and in
testing various chemical models using MINIQUAD75. The best fit models were
chosen based on the statistical parameters like χ2, R-factor,
skewness and kurtosis. Existence of various species was determined by
performing exhaustive modeling18 and the results of a typical system
are given in Table 1. The models were evaluated assuming the simultaneous
existence of different combinations of species. Models containing various
numbers and combinations of species were generated using an expert system CEES19
and they were refined using MINIQUAD75. As the number of species increased, the
models gave better statistics denoting better fit. This indicates that the
final model appropriately fits the experimental data.
3.2. Modeling of chemical speciation:
All the systems were
modeled based on the exhaustive modeling mentioned in Table 1 and the final
models are given in Table 2. The ternary complex species detected are MLXH, MLX2
and MLX2H for Ni(II) and Cu(II) and MLX2H and MLX2 for
Co(II). Low standard deviations (SD) in overall stability constants (log
β) indicate the precision of the parameters. The small values of Ucorr
(sum of the squares of deviations in the concentrations of the metal, the
ligands and the hydrogen ion at all experimental points corrected for degrees
of freedom) indicate that the models represent the experimental data. Small
values of mean, standard deviation and mean deviation for the systems
corroborate that the residuals are around a zero mean with little dispersion.
For an ideal normal distribution, the values of kurtosis and skewness should be
three and zero, respectively. The kurtosis values in the present study indicate
that most of the residuals are greater than three and their distribution shall
have sharp peak (leptokurtic) pattern in majority of the systems.
The values of skewness
recorded in Table 2 are in between -1.88 and 1.24. These data evince that the residuals form a
part of normal distribution. Hence, least squares method can be applied to the
present data. The sufficiency of the model is further evident from the low
crystallographic R-values.
3.3. Effect of dielectric constant on stability of
ternary complexes:
DMSO is a dipolar aprotic solvent
and it does not form any hydrogen bond with solute species. Hence, it removes
water from the coordination sphere of metal ions, making them more reactive
towards the ligands. As a result, the stability of the complexes is expected to
increase. At the same time, it is a coordinating solvent and it competes with
the ligands for coordinating the metals. This decreases the stability of the
complexes. Hence, the stability of the complexes is expected to either increase
or decrease. The variation of overall stability constants with co-solvent
content depends upon electrostatic and non-electrostatic factors. Born’s
classical treatment20 holds good in accounting for the electrostatic
contribution to the free energy change. According to this treatment, the energy
of electrostatic interaction is related to dielectric constant. Hence, the log
β values should vary linearly as a function of reciprocal of the
dielectric constant (1/D) of the medium. The non-linear variation observed in the present study (Figure 1) indicates that the
non-electrostatic forces are dominating the equilibrium process under the
present experimental conditions.
Figure 1: Variation of stability constant values of
ternary complexes with reciprocal of dielectric constant of DMSO (A) Co(II),
(B) Ni(II) and (C) Cu(II); (□) log βMLXH, (○)
log βMLX2, (∆) log
βMLX2H
3.4. Quantification of change in the
stability of species:
The change in the stability of the ternary complexes as
compared to their binary analogues was quantified21,22 as
disproportionation constant (log X) given by Equation 1,
Which corresponds to the equilibrium
ML2 + MX2 
2MLX
Under the equilibrium conditions one can expect the
formation of 50% ternary complexes and 25% each of the binary complexes
statistically and the value of log X shall be 0.6. A value greater than this,
accounts for the extra stability of MLX. Another approach to quantify23-26
the stability of ternary complexes was based on the difference in stability
(Δ log K) for the reactions, ML with X and M(aq) with L and X,
where L is the primary ligand (His) and X is the secondary ligand (Glu). It is
compared with that calculated purely on statistical grounds as given in Equation
2.
The electrostatic theory
of binary complex formation and statistical arguments suggest the availability
of additional coordination positions of the hydrated metal ion for the first
ligand than for the second. Hence, the usual order of stability 
applies.
This suggests that Δ log K should be negative, although several exceptions
have been found27.
The statistical values of
Δ log K for tridentate L and X are in the range of 3.61 to 7.13 for Co(II)
and -0.46 to 1.42 for Cu(II). Negative values of Δ log K can be understood
as the secondary ligand forms a more stable complex with hydrated metal ion
than with ML. Whenever the experimental values of Δ log K exceed the
statistical values, it can be inferred that the ternary complex is formed as a
result of interaction of ML with X or MX with L. The log X and Δ log K
values calculated from binary and ternary complexes are given in Table 3. The
equations for the calculation of Δ log K and log X are given in Chart 1.
These values could not be calculated for some systems due to the absence of
relevant binary species. In the present study, the log X values range from 1.58
to 9.02 and some values found to be higher than those expected on statistical
basis (0.6). These higher values account for the extra stability of the ternary
complexes. Δ log K values are in the range from -0.46 to 7.13 which
indicate that the ternary complexes formed by the Co(II) and Cu(II) are more
stable than their binary complexes. The reason for the extra stability of these
complexes may be due to interactions out side the coordination sphere such as
the formation of hydrogen bonds between the coordinated ligands, charge
neutralization, chelate effect and stacking interactions.28,29 The
extra stability of ternary complexes makes them more amenable for metal
transport. The less stable binary complexes make the metals bioavailable.
Table 4: Effect of errors in influential
parameters on stability constants of His-Ni(II)- Glu ternary complexes in 50%
v/v of DMSO- water mixture.
|
Ingredient
|
% Error
|
log βmlxh (SD)
|
|
1111
|
1120
|
1121
|
|
DMSO
|
|
|
0
|
24.40(16)
|
22.26(10)
|
32.35(14)
|
|
|
|
|
|
|
|
Alkali
|
-5
|
30.67(4)
|
Rejected
|
Rejected
|
|
-2
|
24.72(20)
|
Rejected
|
Rejected
|
|
2
|
23.66(76)
|
26.02(28)
|
32.47(32)
|
|
5
|
Rejected
|
28.21(23)
|
33.19(44)
|
|
|
|
|
|
|
|
Acid
|
-5
|
Rejected
|
28.04(16)
|
33.36(20)
|
|
-2
|
23.87(62)
|
23.56(17)
|
32.61(30)
|
|
2
|
24.37(18)
|
20.15(25)
|
Rejected
|
|
5
|
28.97(5)
|
Rejected
|
Rejected
|
|
|
|
|
|
|
|
Histidine
|
-5
|
22.26(*)
|
22.24(9)
|
Rejected
|
|
-2
|
24.49(11)
|
22.40(7)
|
32.36(9)
|
|
2
|
Rejected
|
21.71(11)
|
31.42(25)
|
|
5
|
Rejected
|
21.56(12)
|
31.64(21)
|
|
|
|
|
|
|
|
Glutamic acid
|
-5
|
20.65(*)
|
24.13(5)
|
31.24(12)
|
|
-2
|
Rejected
|
22.12(6)
|
31.12(13)
|
|
2
|
24.66(24)
|
22.10(20)
|
32.55(26)
|
|
5
|
24.54(24)
|
21.35(23)
|
32.29(27)
|
|
|
|
|
|
|
|
Metal
|
-5
|
24.23(16)
|
22.50(8)
|
32.52(9)
|
|
-2
|
24.32(18)
|
22.35(10)
|
32.41(14)
|
|
2
|
24.28(12)
|
22.06(7)
|
32.08(10)
|
|
5
|
23.09(43)
|
21.49(9)
|
Rejected
|
|
|
|
|
|
|
|
Volume
|
-5
|
24.25(14)
|
22.17(8)
|
32.17(10)
|
|
-2
|
Rejected
|
21.83(10)
|
31.24(30)
|
|
2
|
24.39(13)
|
22.26(8)
|
32.35(11)
|
|
5
|
24.45(26)
|
22.30(17)
|
32.42(26)
|
(*) indicates high standard deviation (SD) values.
3.5. Effect of influential parameters on stability
constants:
Any variation in the
parameters like concentrations of ingredients affects the magnitudes of
stability constants. Such parameters are called influential parameters. In
order to rely upon the best chemical model for critical evaluation and
application under varied experimental conditions with different accuracies of
data acquisition, an investigation was made by introducing pessimistic errors
in the concentrations of alkali, acid, ligands, metal and volume. The results
of typical samples given in Table 4 emphasise that the errors in the
concentrations of alkali and acid affect stability constants more than those of
the ligands and metal.
3.6. Distribution
diagrams:
The ternary complexes of His (L) and Glu (X) in
DMSO-water mixtures are MLXH, MLX2H and MLX2 for Ni(II)
and Cu(II) and MLX2H and MLX2 for Co(II). The active
forms of the ligands are LH32+, LH2+,
LH and L- and XH3+, XH2,
XH- and X2-. The binary complex species of His11
are MLH, ML2, ML2H, ML2H2 and ML2H4
for Co(II), ML2, ML2H, ML2H2 and ML2H4
for Ni(II) and MLH, ML2, ML2H and ML2H2
for Cu(II). The binary species of Glu12 are MX, MX2, MX2H
and MX2H2 for Co(II), MX, MX2 and MX2H2
for Ni(II) and MXH, MX2, MX2H and MX2H2 for
Cu(II). The formation of the ternary species is given in the following
equilibria.
|
M(II) + LH3
+ XH3  MLXH + 5H+ (1)
|
|
M(II) + LH2
+ XH3 MLXH + 4H+ (2)
|
|
MLXH + XH2 MLX2H
+ 2H+ (3)
|
|
MLX2H
MLX2
+ H+ (4)
|
For Ni(II) and Cu(II) the protonated ligands interact
with the metal ion to form MLXH through Equilibria 1 and 2. MLX2H
species is formed by the interaction of MLXH with XH2 (Equilibrium
3). Formation of MLX2 can be explained based on the deprotonation of
MLX2H (Equilibrium 4). 
Based on the protonation and deprotonation
equilibria of His and Glu, and based on coordination chemistry principles, the
possible structures of the ternary complexes are proposed as given in Figure 3.
Figure 2: Distribution diagrams of ternary complexes
of His and Glu in 60% v/v DMSO- water mixture. (A) Co(II), (B) Ni(II) and (C)
Cu(II) .
Figure 3: Plausible structures of ternary complexes
of Co(II), Ni(II) and Cu(II) ions with L-histidine (L) and L-glutamic acid (X).
4. CONCLUSIONS:
The following conclusions
have been drawn from the speciation studies of ternary complexes of Co(II),
Ni(II) and Cu(II) with His and Glu in DMSO-water mixtures.
1.
The
ternary metal complexes detected are MLXH, MLX2H and MLX2 for
Ni(II) and Cu(II) and MLX2H and MLX2 for Co(II).
2.
The
values of Δ log K and log X indicate that the ternary species have extra
stability compared to their binary species.
3.
The
non-linear increase in the stabilities of ternary complexes with solvent
composition is due to the dominance of non-electrostatic forces over
electrostatic forces.
4.
The
magnitudes of the stability constants for ternary complexes are affected by the
errors in the influential parameters like the concentrations of the
ingredients. The order of the influence is alkali > acid > ligands >
metal.
5.
The
study also gives an insight into the metal availability/metal transport in
biofluids. The ternary complexes are more amenable for “metal transport”
because of their extra stability.
5. ACKNOWLEDGEMENTS:
The authors (SR, BAK and KBK) thank the University
Grants Commission, New Delhi, India for financial support under Faculty
Development Programme.
6. REFERENCES:
1. Teigen S and Andersen R. Trace
metals in the marine environment: State of The Art and Research Needs. Programme
on marine pollution. Zagreb. Croatian Society of Chemical Engineers. 1992.
2. Rao PS, Srikanth B, Rao VS,
Kamala Sastry C and Rao GN. Protonation Equilibria of L-Aspartic, Citric and
Succinic Acids in Anionic Micellar Media. E-J. Chem. 6;
2009: 561-568.
3. Paquin PR, Santore RC, Wu KB, Kavvadas CD
and Di Toro DM. The biotic ligand model: a
model of the acute toxicity of metals to aquatic life. Environ. Sci.
Policy. 3; 2000: 175-182.
4. Ajito K, Han C and Torimitsu K. Detection of Glutamate in Optically Trapped Single
Nerve Terminals by Raman Spectroscopy. Anal. Chem. 76;
2004: 2506-2510.
5. Sauvinet V, Parrot S, Benturquia
N, Bravo Moraton E, Renaud B and Denoroy L. In vivo simultaneous monitoring of γ-aminobutyric acid,
glutamate, and L-aspartate using brain microdialysis and capillary electrophoresis
with laser-induced fluorescence detection. Electrophoresis,
24; 2003: 3187-3196.
6. Sennett C, Rosenberg LE and
Mellman IS. Transmembrane Transport of Cobalamin
in Prokaryotic and Eukaryotic Cells. Annu. Rev. Biochem.
50; 1981: 1053-1086.
7.
Mulrooney
SB and Hausinger RP. Nickel uptake and
utilization by microorganisms. FEMS Microbiol. Rev.
27; 2003: 239-261.
8. Holm RH, Kennepohl P and Solomon
EI. Structural
and Functional Aspects of Metal Sites in Biology. Chem. Rev. 96;
1996: 2239-2314.
9. Pegg DE. Principles of cryopreservation. Methods Mol. Biol.
368; 2007: 39-57.
10. Raju S, Ananda Kumar B, Pushpa
Raju G, Bharath Kumar Naik K and Rao GN. Protonation Equilibria Of L-Glutamic
Acid And L-Histidine in DMSO-Water Mixtures. Curr. Chem. Res., India. 2011
(in press).
11. Raju S, Bharath Kumar Naik K,
Ananda Kumar B and Rao GN. Effect of dielectric constant of medium on chemical
speciation of L- Histidine complexes of Co(II), Ni(II) and Cu(II). Bull.
Chem. Soc. Ethiop. 2011 (communicated).
12. Raju S, Bharath Kumar Naik K,
Ananda Kumar B and Rao GN. Speciation of binary complexes of L-glutamic acid
with Co(II), Ni(II) and Cu(II) in low dielectric media J. Indian Chem. Soc. 2011
(in press).
13. Gran G. Determination of the
equivalence point in potentiometric titrations. Analyst. 77; 1952:
661-671.
14. Gran G. Equivalence volumes in
potentiometric titrations. Anal. Chim. Acta. 206; 1988:
111-123.
15. Rao RS and Rao GN. Computer
applications in Chemistry. Himalaya publishing house, Mumbai, India,
2005: 302-309.
16. Rao GN. Complex equilibria of some
biologically important metal ions in aquo organic media. Ph. D. Thesis, Andhra
University, Visakhapatnam, India. 1989.
17. Gans P, Sabatini A and Vacca A. An improved computer
program for the computation of formation constants from potentiometric data.
Inorg. Chim. Acta. 18; 1976: 237-241.
18. Rao GN, Lavanya KV and Rao VM. Binary
complexes of Mg(II) and Ca(II) in water-surfactant mixtures. Chem. Spec.
Bioavail. 22; 2010: 285-296.
19. Briabanti A. Rao RS. Babu AR and
Rao GN. CEES.Expert system for complex equilibria. MODGEN. Model generator for
metal ligand equilibria in solution phase. Ann. Chim. (Italy). 85;
1995: 17-29.
20. Born M. Volumen und hydratationswarme der ionen. Z.
Phys. 1; 1920: 45-48.
21. Griesser R and Sigel H. Ternary
complexes in solution VIII: complex formation between the
copper(II)-2,2’–bipyridyl 1 : 1 complex and ligands containing oxygen and (or)
nitrogen donor atoms. Inorg. Chem. 9; 1970: 1238-1243.
22. Griesser R and Sigel H. Ternary
complexes in solution XI: Complex formation between the cobalt(II)-, nickel(II)-,
copper(II)- and zinc (II)-2,2’-bipyridyl 1:1 complexes and ethylenediamine,
glycinate or pyrocatecholate. Inorg. Chem. 10; 1971: 2229-2232.
23. Sigel H, Caraco R and Prijs B. Ternary complexes in solution
XVI: Influence of the size of the chelate rings on the stability of mixed
ligand copper(II) complexes containing aliphatic ligands. Inorg. Chem. 13;
1974: 462–465.
24. Sigel H, Huber PR, Greisser R
and Prijs B. Ternary complexes in solution XV. Mixed-ligand copper(II)
complexes with 2,2’-bipyridyl or 1,10-phenanthroline and pyrocatecholate or
derivatives thereof. Inorg. Chem. 12; 1973: 1198-1200.
25. Kida S. Investigation on mixed
complexes I. Spectrophotometric study of mixed complexes formed by cupric ion
and bidentate ligands. Bull. Chem. Soc. Jpn. 29; 1956: 805-811.
26. Martin RB and Prados R. Some
factors influencing mixed complex formation. J. Inorg. Nucl. Chem. 36; 1974:
1665-1670.
27. Sigel H. Ternary Cu2þ complexes:
Stability, structure and reactivity. Angew. Chem. Int. Ed. Engl. 14; 1975:
394-402.
28. Sakurai T. Yamauchi O and
Nakahara A. Mixed ligand copper(II) complexes of α-amino acids with
ligand-ligand interactions. Bull. Chem. Soc. Jpn. 49; 1976: 169-173.
29. Yamauchi O. Sakurai T and
Nakahara A. Stereoselectivity in mixed ligand copper(II) complexes with electrostatic
ligand-ligand interactions. Applications to optical resolution of α-amino
acids with a charged side chain. Bull. Chem. Soc. Jpn. 50; 1977: 1776-1779.
s
