Olgun Guvench1,2, Elizabeth K Whitmore1,2. 1. Department of Pharmaceutical Sciences and Administration, School of Pharmacy, Westbrook College of Health Professions, University of New England, 716 Stevens Avenue, Portland, Maine 04103, United States. 2. Graduate School of Biomedical Science and Engineering, University of Maine, 5775 Stodder Hall, Orono, Maine 04469, United States.
Abstract
The effects of sulfation and calcium cations (Ca2+) on the atomic-resolution conformational properties of chondroitin carbohydrate polymers in aqueous solutions are not well studied owing to experimental challenges. Here, we compare all-atom explicit-solvent molecular dynamics simulations results for pairs of O-type (nonsulfated) and A-type (GlcNAc 4-O-sulfated) chondroitin 20-mers in 140 mM NaCl with and without Ca2+ and find that both sulfation and Ca2+ favor more compact polymer conformations. We also show that subtle differences in force-field parametrization can have dramatic effects on Ca2+ binding to chondroitin carboxylate and sulfate functional groups and thereby determine Ca2+-mediated intra- and interstrand association. In addition to providing an atomic-resolution picture of the interaction of Ca2+ with sulfated and nonsulfated chondroitin polymers, the molecular dynamics data emphasize the importance of careful force-field parametrization to balance ion-water and ion-chondroitin interactions and suggest additional parametrization efforts to tune interactions involving sulfate.
The effects of sulfation and calcium cations (Ca2+) on the atomic-resolution conformational properties of chondroitin carbohydrate polymers in aqueous solutions are not well studied owing to experimental challenges. Here, we compare all-atom explicit-solvent molecular dynamics simulations results for pairs of O-type (nonsulfated) and A-type (GlcNAc 4-O-sulfated) chondroitin 20-mers in 140 mM NaCl with and without Ca2+ and find that both sulfation and Ca2+ favor more compact polymer conformations. We also show that subtle differences in force-field parametrization can have dramatic effects on Ca2+ binding to chondroitin carboxylate and sulfate functional groups and thereby determine Ca2+-mediated intra- and interstrand association. In addition to providing an atomic-resolution picture of the interaction of Ca2+ with sulfated and nonsulfated chondroitin polymers, the molecular dynamics data emphasize the importance of careful force-field parametrization to balance ion-water and ion-chondroitin interactions and suggest additional parametrization efforts to tune interactions involving sulfate.
The glycosaminoglycanchondroitin sulfate
(CS) occurs in the context
of its covalent attachment to extracellular protein–carbohydrate
conjugates termed proteoglycans (PGs). These biomolecules may be more
than 50% carbohydrate by mass, with CS contributing significantly
to the carbohydrate portion and serving to interact with growth factors,
cell surface receptors, and matrix proteins.[1,2] To
the extent that the function of biomolecules is tied to their three-dimensional
(3D) structures and conformations, a significant gap exists in the
understanding of CS PGs because of the difficulty in performing experimental
atomic-resolution structural biology on CS. Two major reasons for
this are that CS synthesis is not template-based, and CS is variably
sulfated.[2] Therefore, a biological sample
of CS will be polydisperse with regard to both polymer length and
sulfation. Toward addressing this difficulty, we and others have developed
and applied computer modeling methods to describe the conformational
properties of chondroitin and the tetrasaccharide that links it to
PG core proteins.[3−14]An additional complexity is the interactions of CS with cations.
In solution, divalent calcium cations (Ca2+) significantly
enhance interchain CS association while monovalent sodium cations
(Na+) do not,[15] which is consistent
with studies demonstrating that CS preferentially binds Ca2+ over Na+.[16,17] From proteoglycan calcium salt
X-ray diffraction data, chondroitin 4-sulfate, also called A-type
chondroitin (Figure ), demonstrates −OSO3– ... Ca2+ ... –OOC– coordination across the
β1–3 linkage,[18] an interaction
which has also been observed in molecular dynamics simulations of
A-type disaccharide in solution.[19] In the
same X-ray experiments, adjacent parallel CS chains were observed
to interact through −COO– ... Ca2+ ... –OOC– bridges. While this might suggest
preferential Ca2+ binding by carboxylate over sulfate,
it has been stated that CSsulfate binds Ca2+ more strongly
than CS carboxylate.[17] Also, the creation
of CScalcium complex by cation exchange showed that both of these
anionic functional groups were involved in the incorporation of Ca2+.[20] Therefore, while it is not
clear from these studies whether there is a strong preference for
Ca2+ binding by carboxylate versus sulfate in CS, it is
clear that both functional groups can contribute to binding. This
becomes especially evident when considering other glycosaminoglycans
(GAGs). For example, hyaluronan (HA), which is not sulfated and which
otherwise differs from chondroitin only at the C4 chirality of the
hexosamine (GlcNAc in HA vs GalNAc in CS), does bind Ca2+ through its carboxylate groups,[21] as
do the carboxylate groups in polyuronate.[22] And, in a series of GAGs of increasing degree of sulfation, going
from HA with no sulfation to CS to the highly sulfated heparin, Ca2+ binding increased with GAG anionic charge density (i.e.,
sulfation).[23] The ability of CS to bind
Ca2+ is biologically significant, as it plays a part in
biomineralization[24] and can serve as a
reservoir of Ca2+ for the calcification of epiphyseal cartilage.[23,25] That being said, it remains to be determined what individual contributions
Ca2+ binding to chondroitin carboxylate groups, Ca2+ binding to chondroitin sulfate groups, and intra- and inter-chain
bridging interactions of Ca2+ with chondroitin, as observed
in biophysical and simulation studies, make to such biological processes.
Figure 1
Structure
of chondroitin polymer [−4GlcAβ1–3GalNAcβ1−]. A-type chondroitin: R = −OSO3–; O-type chondroitin: R =
−OH.
Structure
of chondroitin polymer [−4GlcAβ1–3GalNAcβ1−]. A-type chondroitin: R = −OSO3–; O-type chondroitin: R =
−OH.Thus, while chondroitin is known
to bind Ca2+ and this
binding property has biological relevance, atomic-resolution details
of this binding under biological conditions are currently unclear.
While our previous work using all-atom explicit-solvent molecular
dynamics simulations of variably sulfated chondroitin disaccharides
has demonstrated the effects of direct binding of Ca2+ to
−COO– and −OSO3– functional groups,[19] there are no such
studies investigating Ca2+ in the context of proper chondroitinpolymers or of multiple polymers. The current work aims at addressing
this issue by considering pairs of chondroitin 20-mers in solutions
of NaCl or NaCl + CaCl2. The goal is to better understand
how Ca2+ can bind to chondroitin polymer and how Ca2+ may act to modulate chondroitin polymer conformation and
interpolymer association.In our analysis, we discuss not only
the results but also the possible
limitations to the approach and the model. For example, the need for
a large system size (∼200,000 particles) to address even the
limited problem of two chondroitin 20-mers (Figure , n = 10) in this study
limits the timescale of the simulations. Additionally, proper modeling
of ion-charge interactions in an aqueous environment using a molecular
mechanics force field is a challenging task. Despite these possible
limitations, the current approach offers a view of chondroitin interactions
with Ca2+ not currently available through experimental
means.
Materials and Methods
Choice of Ions and Ion Concentrations
In an attempt
to best represent the extracellular environment, we ran simulations
under two ion conditions: 140 mM NaCl, and 140 mM NaCl + 15 mM CaCl2. We note that the physiological Na+ concentration
of 140 mM is nearly 30× the concentration of the other monovalent
cation, K+, in the extracellular space.[26] From our previous work[19] and
the survey of existing literature above, it seems that Na+ does not have significant direct interactions with chondroitin.
Given the fact that K+ is also a monovalent ion and that
its extracellular concentration is ∼1/30th that of Na+, we made a simplifying assumption to exclude K+. With
regard to the divalent cations Ca2+ and Mg2+, while it has been demonstrated that CS binds divalent ions in general,[17] biological studies focus on Ca2+,
and existing available biophysical studies for use as reference for
our simulations similarly focus on Ca2+.The total
extracellular calcium is in the range 2.2–2.6 mM, and the free
amount is half that.[27,28] For context, our simulation systems
for chondroitin have ∼65,000 water molecules; 1 mM Ca2+ corresponds to a single Ca2+ cation mixed with this many
water molecules. With the understanding that Ca2+ can directly
bind to chondroitin, chondroitin can act as a sponge for Ca2+. However, it is impractical to maintain a 1 mM bath of Ca2+ through the addition/deletion of CaCl2 to the bulk solvent
during a simulation as binding/unbinding events change the solution
concentration of Ca2+. One estimate for the binding capacity
of CS is one cation per disaccharide unit,[29] while another study states that 1 μM CS disaccharide unit
binds 0.757 μM Ca2+.[30] To this end, we have added 16 Ca2+ cations per simulation
system (i.e., two polymers per simulation system * 10 disaccharides
per polymer * 0.757 Ca2+ per disaccharide = 15.14). This
is approximately 15 mM, hence the choice of 15 mM CaCl2 for simulation conditions.
Force Field
The most current version
of the CHARMM
C36 additive force field for carbohydrates,[31−34] available within “toppar_c36_jul20.tgz”
at http://mackerell.umaryland.edu/charmm_ff.shtml (accessed November
15, 2020), was used. This version of C36 includes the addition of
pair-specific nonbonded Lennard-Jones (LJ) parameters (“NBFIX”)
for macromolecule–ion interactions introduced into the prior
version, “toppar_c36_jul19.tgz.” NBFIX is a means of
introducing custom LJ parameters on a specific pairwise basis, that
is, not using the default combining rule to arrive at pairwise parameters
from single-atom (atom-wise) LJ parameters. As a control, we also
ran simulations involving calcium cation Ca2+ with “toppar_c36_jul17.tgz,”
which does not include these additions. Relevant to the present work
are the pairwise NBFIX values shown in Table , where OC2DP is the atom type for the three
equivalent terminal oxygen atoms on sulfate groups, OC2D2 is the atom
type for the two equivalent carboxylate oxygens, CAL is the atom type
for Ca2+, and SOD is the atom type for sodium cation Na+. Per the CHARMM force-field definition, the LJ energy between
two atoms i and j, VLJ,, separated at an interatomic distance
of r is computed aswhere ε is the force-field parameter
that determines the minimum value for
the function VLJ,,
which occurs when the inter-atomic distance r is equal to the force-field parameter rmin,.
Table 1
Force-Field
Parameter Values for Interactions
between Sulfate/Carboxylate Oxygen Atoms and Ca2+/Na+ in the c36_jul20 and c36_jul17 Versions of the CHARMM C36
Additive Force Field
i
j
c36_jul20
parameters
c36_jul17 parameters
atom
atom type
charge q
atom
atom type
charge q
εij (kcal/mol)
rmin,ij (Å)
literature
reference
εij (kcal/mol)
rmin,ij (Å)
literature
reference
sulfate terminal oxygen
OC2DP
–0.650
Ca2+
CAL
+2
0.12
3.256
(35)
0.12a
3.067a
(36)
carboxylate oxygen
OC2D2
–0.760
Ca2+
CAL
+2
0.12
3.232
(37)
0.12a
3.067a
(36)
sulfate terminal oxygen
OC2DP
–0.650
Na+
SOD
+1
0.07502
3.16
(38)
0.07502
3.16
(38)
carboxylate oxygen
OC2D2
–0.760
Na+
SOD
+1
0.07502
3.23
(38)
0.07502
3.23
(38)
No NBFIX entry for this pair. Value
shown is computed using default atom-wise LJ parameters ε and rmin, and CHARMM force field combining rules, and .
No NBFIX entry for this pair. Value
shown is computed using default atom-wise LJ parameters ε and rmin, and CHARMM force field combining rules, and .We note that all SOD LJ parameters
in Table are the
same for both c36_jul20 and c36_jul17,
whereas the rmin, CAL
parameters are shorter by 0.189 and 0.165 Å for sulfate and carboxylate
interactions, respectively, in the older version of the force field,
c36_jul17. As such, Ca2+ cations can more closely approach
sulfate terminal oxygens and carboxylate oxygens under the older c36_jul17
force-field model. This closer approach will lead to a more favorable
(more negative) Coulomb interaction energy, given the opposite signs
of the charge parameters on the Ca2+ cations and the oxygen
atoms. The charge parameters for all the atom types shown in Table that appear in the
systems considered here, as described below, are identical in c36_jul20
and c36_jul17. Water molecules were represented using the TIP3P model[39] included with the CHARMM force field, and Na+/Ca2+–water interactions are identical between
c36_jul20 and c36_jul17.
System Construction
Chondroitin
20-mers were built
with the sequence [−4GlcAβ1–3GalNAcβ1-]10 and using default force-field internal coordinates except
for glycosidic dihedrals, which were set based on favored conformations
from all-atom explicit-solvent simulations of chondroitin disaccharides.[19] Specifically, glycosidic dihedrals were ϕ
= −83.75° and ψ = −156.25° in all GlcAβ1–3GalNAc
linkages and ϕ = −63.75° and ψ = 118.75°
in all GalNAcβ1-4GlcA linkages, where ϕ is defined by the atoms O5-C1-O-C3/4 and ψ by the atoms C1-O-C3/4-C2/3,
and resulted in an extended polymer conformation with an end-to-end
distance of 99.2 Å, as measured from C1 of the reducing-end GalNAc
to C4 of the nonreducing-end GlcA. A-type chondroitin sulfate was
created from this O-type (nonsulfated) polymer by the conversion of
the axial C4 hydroxyl groups of all GalNAc residues to sulfate groups.
The polymer was placed with its center of geometry at the center of
a box with an edge length of 124.3 Å and was oriented such that
its largest to smallest principal axes were aligned with the x, y,
and z axes of the box, respectively. The polymer was duplicated, and
one copy was translated 30.4 Å in the +z direction and the other
30.4 Å in the −z direction so that the two polymers were
parallel in their longest dimension. The box was filled with water
molecules at the experimental liquid water density, and water molecules
overlapping with polymer atoms were deleted. Water molecules were
randomly replaced with Na+ and Cl– ions
to achieve 140 mM NaCl. Sixteen Ca2+ cations were added
to some of the systems by randomly replacing sixteen water molecules.
A total system net charge of zero was achieved by the random replacement
of water molecules by either Na+ or Cl–, as appropriate. The total number of atoms in the system was approximately
190,000. Throughout the text, systems are labeled with names according
to whether the polymer is A-type or O-type. The presence of sixteen
Ca2+ cations is indicated by the subscript “Cal,”
and the use of the older parameter set c36_jul17 instead of the most
recent parameter set c36_jul20 is indicated by a single apostrophe. Table summarizes the six
systems.
Table 2
System Names and Differences for the
Six Systems Studied
system name
chondroitin
type
C36 parameters
contains
Ca2+?
A
A
c36_jul20
no
ACal
A
c36_jul20
yes
A’Cal
A
c36_jul17
yes
O
O
c36_jul20
no
OCal
O
c36_jul20
yes
O’Cal
O
c36_jul17
yes
Molecular Dynamics Simulations
Each
of the six systems
was simulated in quadruplicate, with different random initial atomic
velocities to generate a unique trajectory for each simulation. Each
simulation had a production stage of 300 ns, during which trajectory
snapshots were taken every 0.1 ns, yielding 3000 snapshots per simulation
for subsequent analysis. Production simulations were in the constant
particle number, constant volume, constant temperature ensemble (NVT),
and used periodic boundary conditions,[40] the SHAKE algorithm[41] to constrain bonds
involving hydrogens and water geometries to equilibrium parameter
values, and leapfrog Verlet integration[42] to run Langevin dynamics[43] at 310 K with
a friction coefficient of 0.1 ps–1. Coulomb and
LJ interactions employed a 10 Å spherical cutoff. The particle
mesh Ewald (PME) method[44] with a grid spacing
of ∼1 Å was employed to account for Coulomb interactions
beyond the cutoff. An isotropic correction was applied to account
for LJ interactions beyond the cutoff[40] and a switching function[45] was used to
smooth LJ interactions in the interval 8–10 Å. These simulations
were run with the OpenMM[46] module in the
CHARMM v c41b2 software.[47] Prior to production,
each system was minimized for 1000 steps using the conjugate gradient
algorithm[48,49] and then heated to 310 K by velocity reassignment
every 1000 steps over a total of 20,000 steps with harmonic positional
restrains on non-hydrogen atoms of the polymers, all using the NAMD
software v 2.13.[50] Heating was followed
by a 100 ps equilibration run with OpenMM/CHARMM. Simulation conditions
for heating and equilibration were analogous to the production simulations.
To determine the optimal edge length of the periodic box for NVT simulations,
the NAMD software was used to perform constant particle number, constant
pressure, constant temperature ensemble (NPT) heating and equilibration,
with simulation conditions analogous to the production simulations.
The target temperature for the NPT simulations was 310 K, and the
target pressure was 1.01325 bar. NPT heating used the same protocol
as that described for NVT heating, including initial minimization,
and with the addition of a Langevin piston barostat.[51] NPT equilibration, using the same barostat, was for 1 ns.
The edge length for subsequent NVT simulation of the system was then
computed as the average of the edge length values sampled every 200
fs from the last 0.5 ns of this 1-ns NPT simulation.
Methyl Sulfate
Simulations
We used the same protocol
described above for chondroitin to perform methyl sulfate (CH3OSO3–) simulations. Methyl sulfate
was modeled using either the c36_jul20 (MeS) or the c36_jul17 (MeS’)
version of the CHARMM General Force Field (CGenFF).[52,53] The two CGenFF versions have the same sulfate terminal oxygen LJ
and charge parameters as the corresponding versions of the carbohydrate
force field used for the chondroitin simulations (Table ; in CGenFF, the sulfate terminal
oxygen atom type is OG2P1). The box edge length was 24.6 Å, and
the system contained ∼1500 atoms, including 1 Ca2+, 2 Na+, and 3 Cl– ions. Because of
the single instance of sulfate and the single Ca2+ in the
system, trajectory snapshots were taken every 0.01 ns to obtain sufficient
statistics for g(r) analysis, yielding
30,000 snapshots per simulation.
Data Analysis
Radial distribution functions g(r), minimum interpolymer distance, polymer–Ca2+ binding,
polymer end-to-end distance, and polymer radius
of gyration were computed from production simulation snapshots using
utility functions in and scripting with the CHARMM software. Periodic
boundary conditions were taken into account when computing g(r), minimum interpolymer distance, and
polymer–Ca2+ binding. Each g(r) was scaled by 1/, where is the average value of that g(r) in the interval 8–10 Å
to ensure
the value of g(r) = ∼1 for r = 10 Å. The VMD software[54] v 1.93 was used for visualization and the creation of molecular
graphics. Plots were created with Gnuplot v 5.4.
Results and Discussion
Sulfate–Calcium
Binding
A-type chondroitin contains
two functional groups per disaccharide that each carry a net −1
charge at physiological pH, a sulfate and a carboxylate (Figure ). Radial distribution
functions g(r) can show the relative
propensity of Ca2+ and Na+ to partition out
of bulk solution and associate with these functional groups. In the
case of sulfate, we consider the three terminal oxygen atoms, which
in the force-field representation have identical atom type and partial
charges and are more solvent exposed and negatively charged than the
oxygen atom that connects sulfur to GalNAc C4. As such, they are well
suited to associate with positive ions from the solution. g(r) for sulfate terminal oxygens and Ca2+ in both force-field representations contains three distinct
peaks between 2 and 8 Å, implying Ca2+ ordering in
three separate shells around sulfate. While peak locations are essentially
the same for both force fields, with a separation between peaks of
∼2.3 Å, there is a striking difference in the height of
the first peak. In the most current force field, c36_jul20, the first
peak is barely perceptible, implying that direct interaction (i.e.,
without bridging water molecules) is uncommon relative to water-bridged
association (Figure , top row; Figure ). In contrast, with the previous parameter set contained in c36_jul17,
there is a distinct first peak (Figure , bottom row). This contrasting behavior correlates
with a 0.189 Å increase in rmin, for this interaction from c36_jul17 to c36_jul20
(rmin, = 3.067 and
3.256 Å, respectively; see Table , first row for all charge and LJ parameters for this
interaction). Because rmin, is larger in c36_jul20 than in c36_jul17, the interaction
will be weaker in the former with all else being the same, and this
emerges as a greatly reduced first peak in the former’s g(r).
Figure 2
Sulfate terminal oxygen–Ca2+ radial distribution
functions for A-type chondroitin. ACal = A-type chondroitin
simulation with Ca2+ using the c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. In each panel, the four different-colored traces
are from four independent simulations. Each 300 ns simulation has
been analyzed in 100 ns blocks.
Figure 3
Water-bridged
association between sulfate terminal oxygen atoms
(red spheres) and Ca2+ (orange sphere) in A-type chondroitin.
The snapshot is from a simulation with the c36_jul20 force field (ACal).
Sulfate terminal oxygen–Ca2+ radial distribution
functions for A-type chondroitin. ACal = A-type chondroitin
simulation with Ca2+ using the c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. In each panel, the four different-colored traces
are from four independent simulations. Each 300 ns simulation has
been analyzed in 100 ns blocks.Water-bridged
association between sulfate terminal oxygen atoms
(red spheres) and Ca2+ (orange sphere) in A-type chondroitin.
The snapshot is from a simulation with the c36_jul20 force field (ACal).An alternative explanation for
the very small first peak in the
sulfate terminal oxygen–Ca2+g(r) for c36_jul20 is competition for the binding of Ca2+ with carboxylate oxygens; however, this is not the case
for two reasons. The first is that carboxylate binding with Ca2+ is more favorable in c36_jul17 than in c36_jul20 (Table , rmin, values for OC2D2–CAL; see also results below),
yet c36_jul17 has a much larger first peak in the sulfate terminal
oxygen–Ca2+g(r) (Figure , top vs
bottom rows). The second is that similar g(r) behavior is seen for methyl sulfate (CH3OSO3–) with Ca2+. As with chondroitin
A, the sulfate group in methyl sulfate is deprotonated and therefore
negatively charged at a physiological pH. Unlike chondroitin, methyl
sulfate does not contain a carboxylate functional group, and this
difference allows the separation of carboxylate binding effects from
sulfate binding. The c36_jul20 sulfate terminal oxygen–Ca2+g(r) traces for A-type
chondroitin and for methyl sulfate are practically identical (Figure , top row vs Figure , top). Therefore,
the very small first peak for this g(r) with c36_jul20 is indeed due to the parametrization, and specifically
the increase in rmin, compared to c36_jul17.
While this change weakens the interaction of the sulfate with Ca2+, the interaction of Ca2+ with water is unaltered.
Thus, the balance of forces in c36_jul20 is tilted toward keeping
Ca2+ solvated as it approaches sulfate, but the distinct
second and third peaks show that calcium–water clusters will
nonetheless organize around the negatively charged sulfate.
Figure 4
Sulfate terminal
oxygen–Ca2+ radial distribution
functions for methyl sulfate. MeS = methyl sulfate simulation with
Ca2+ using c36_jul20 force field. MeS’ = methyl
sulfate simulation with Ca2+ using c36_jul17 force field.
In each panel, the four different colored traces are from four independent
simulations.
Sulfate terminal
oxygen–Ca2+ radial distribution
functions for methyl sulfate. MeS = methyl sulfate simulation with
Ca2+ using c36_jul20 force field. MeS’ = methyl
sulfate simulation with Ca2+ using c36_jul17 force field.
In each panel, the four different colored traces are from four independent
simulations.Unlike the similarities in g(r) for sulfate terminal oxygen–Ca2+ interactions
in A-type chondroitin and methyl sulfate when using the c36_jul20
parametrization, there are significant differences in this g(r) for the two types of systems when
using c36_jul17. Specifically, the first and second peaks are much
larger for methyl sulfate (Figure , bottom) than for A-type chondroitin (Figure , bottom row). This is best
explained by the depletion of Ca2+ by chondroitin carboxylate
moieties. Unlike in methyl sulfate where Ca2+ can either
bind to sulfate or partition into solution, in A-type chondroitin,
Ca2+ can bind to sulfate, can partition into solution,
or can bind to carboxylate. As discussed in detail below, with c36_jul17,
Ca2+ binding to carboxylate is essentially irreversible
on the timescale of the present simulations, and therefore leaves
little opportunity for binding to sulfate.The kinetics of Ca2+ binding to sulfate on A-type chondroitin
is consistent with the picture inferred from the g(r) data. For both the c36_jul20 and c36_jul17 parametrizations,
only a small fraction of the 16 total Ca2+ ions in the
system are located within the first interaction shell (Figure , left column), defined as
being within 3 Å of sulfate terminal oxygen atoms as determined
from the g(r) (Figure ). Also, this number frequently
fluctuates to 0, meaning that there is frequent dissociation. If both
the first and second interaction shells (as defined by a sulfate terminal
oxygen–Ca2+ distance within 5.3 Å as determined
from the g(r); Figure ) are considered, the number
of bound Ca2+ is naturally larger. However, again, there
are frequent fluctuations to 0 (Figure , right column), indicating dissociation of all Ca2+ from the first and second interaction shells of all 20 sulfate
groups across the two A-type chondroitin 20-mers in each simulation.
Therefore, the overall picture is that regardless of parametrization,
Ca2+ binding to sulfate on A-type chondroitin is weak and
prone to frequent dissociation. Additionally, per residue analysis
of the binding data showed no dramatic differences in the likelihood
of Ca2+ binding to one particular sulfate as compared to
other sulfates in a 20-mer. As such, the observed binding of Ca2+ to sulfate moieties in A-type chondroitin is both weak and
nonspecific.
Figure 5
Kinetics of Ca2+ binding to sulfate terminal
oxygen
atoms on A-type chondroitin. ACal = A-type chondroitin
simulation with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. “Within 3 Å” indicates binding
is defined by a Ca2+–sulfate terminal oxygen distance
within 3 Å, and “within 5.3 Å” indicates binding
is defined by a Ca2+–sulfate terminal oxygen distance
within 5.3 Å. In each panel, the four different colored traces
are from four independent simulations.
Kinetics of Ca2+ binding to sulfate terminal
oxygen
atoms on A-type chondroitin. ACal = A-type chondroitin
simulation with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. “Within 3 Å” indicates binding
is defined by a Ca2+–sulfate terminal oxygen distance
within 3 Å, and “within 5.3 Å” indicates binding
is defined by a Ca2+–sulfate terminal oxygen distance
within 5.3 Å. In each panel, the four different colored traces
are from four independent simulations.
Carboxylate–Calcium Binding
As is the case for
sulfate terminal oxygens, carboxylate oxygen–Ca2+ interaction is weaker in the newer c36_jul20 than in c36_jul17 owing
to an increase in rmin, for the carboxylate oxygen–Ca2+ with no change
to ε or charge parameters (Table ). Despite this weakening,
this interaction in both A-type and O-type is overall very favorable.
As such, the g(r) data for this
interaction are unreliable because of poor equilibrium statistics
owing to the strong tendency of Ca2+ to associate with
carboxylate oxygen atoms combined with the limited number of Ca2+ cations in the system and the large system size.The
kinetics of Ca2+ binding to carboxylate on A-type and O-type
chondroitin shows an extreme force-field dependence, as well as dependence
on the presence/absence of sulfate functional groups (i.e., A-type
vs O-type). With regard to the force field, the NBFIX addition to
c36_jul20 (Table )
has a dramatic effect: without this update and using the default combining
rules for atom-wise LJ parameters for Ca2+ and carboxylateoxygen (Table , c36_jul17),
Ca2+ binding to carboxylate is irreversible across all
eight simulations (A’Cal and O’Cal quadruplicate simulations; Table and Figure ). By 300 ns, at least 75% of Ca2+ ions in every
single one of these eight simulations are bound to chondroitin. Additionally,
tracking the number of bound Ca2+ with time shows that
this value only increases with time (Figure ). This is in strong contrast to the newer
parametrization, where an equilibrium number of bound Ca2+ is reached early in the simulations, and this number fluctuates
between 0 and 6 for A-type chondroitin and 0 and 4 for O-type chondroitin
when considering the first interaction shell (Figure , first column, rows ACal and
OCal). These latter results indicate the influence of sulfate
on Ca2+ binding: chondroitin carboxylate moieties can bind
more Ca2+ when the polymer is sulfated. Not only does this
demonstrate the importance of charge density on the polymer for Ca2+ binding, which is consistent with experimental findings,[23] but it also shows that the increased charge
density can increase binding without direct charge–charge interactions
because neighboring sulfate, which very weakly directly binds Ca2+ itself (ACal in Figure and Figure ), substantially increases the average number of Ca2+ within the first interaction shell of carboxylate. Mean
(standard deviation) values from the first interaction shell data
shown in Figure (“within
3 Å”) are 2.26 (2.12) for ACal and 1.10 (0.98)
for OCal, which quantitatively demonstrate the influence
of sulfate functional groups on Ca2+ direct binding to
carboxylates.
Figure 6
Kinetics of Ca2+ binding to carboxylate oxygen
atoms
on A- and O-type chondroitin. ACal = A-type chondroitin
simulation with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. OCal = O-type chondroitin simulation
with Ca2+ using c36_jul20 force field. O’Cal = O-type chondroitin simulation with Ca2+ using c36_jul17
force field. “Within 3 Å” indicates binding is
defined by a Ca2+–sulfate terminal oxygen distance
within 3 Å, and “within 5.3 Å” indicates binding
is defined by a Ca2+–sulfate terminal oxygen distance
within 5.3 Å. In each panel, the four different-colored traces
are from four independent simulations.
Kinetics of Ca2+ binding to carboxylate oxygen
atoms
on A- and O-type chondroitin. ACal = A-type chondroitin
simulation with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. OCal = O-type chondroitin simulation
with Ca2+ using c36_jul20 force field. O’Cal = O-type chondroitin simulation with Ca2+ using c36_jul17
force field. “Within 3 Å” indicates binding is
defined by a Ca2+–sulfate terminal oxygen distance
within 3 Å, and “within 5.3 Å” indicates binding
is defined by a Ca2+–sulfate terminal oxygen distance
within 5.3 Å. In each panel, the four different-colored traces
are from four independent simulations.We note that all Ca2+-containing simulations started
with 16 Ca2+ ions in bulk solution, which corresponds to
∼15 mM and is well above the physiological concentration of
1–2 mM. As described in the Materials and
Methods section, the reasoning behind this was that despite
the large system size (∼200,000 atoms), 1–2 mM is equivalent
to having 1–2 Ca2+ ions in the entire bulk aqueous
solvent of this system, and chondroitin is expected to act as a sponge
for Ca2+. Thus, at a starting concentration of 1–2
mM, there would not be enough Ca2+ ions in bulk to properly
act as a reservoir source for the anticipated Ca2+ binding
to chondroitin; therefore, a starting concentration of ∼15
mM Ca2+ in the bulk solvent was used based on the literature
estimates of chondroitin binding. Using the older force-field representation,
c36_jul17, by t = 300 ns, chondroitin binding to
Ca2+ leaves as few as 1 or 2 Ca2+ ions unbound
out of the 16 total Ca2+ ions (Figure , A’Cal and O’Cal), which corresponds to 1–2 mM free Ca2+, which is in line with physiological concentrations. With the newer
force field representation, c36_jul20, at most five Ca2+ ions are bound (Figure , ACal), leaving 11 ions free, which corresponds
to ∼10 mM free Ca2+. While this is ∼10×
the physiological concentration, using a significantly lower concentration
of Ca2+ would risk very poor sampling owing to the small
number of Ca2+ ions in such a large system, with the additional
limit of 300 ns of simulation time, which took several weeks of real-world
continuous computing to achieve.
Sodium Binding
g(r) data for Na+ binding
to sulfate (Figure ) and carboxylate (Figure ) are unremarkable. In all cases, a distinct
first peak is followed by a less distinct second peak and a barely
distinguishable third peak, with each peak getting successively wider
and shorter. Equilibrium statistics are achieved within the first
100 ns block, as the g(r) profiles
are the same for this block as well as the second and third 100 ns
blocks. g(r) data are independent
of whether c36_jul20 or c36_jul17 was used. This serves as a useful
control because parameters involving Na+ are identical
across the two force-field versions (Table ). There is a subtle exception to these general
findings in the case of carboxylate oxygen–Na+g(r) with c36_jul17 (Figure , A’Cal and O’Cal), where there is more variability in the data. In particular,
the peak heights for this interaction diminish with time for A’Cal. A possible explanation for this is that the number of
available carboxylate oxygen sites for Na+ binding diminishes
with time because of increasing saturation with Ca2+ (Figure , A’Cal).
Figure 7
Sulfate terminal oxygen–Na+ radial distribution
functions in chondroitin. ACal = A-type chondroitin simulation
with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using c36_jul17
force field. In each panel, the four different colored traces are
from four independent simulations. Each 300 ns simulation has been
analyzed in 100 ns blocks.
Figure 8
Carboxylate
oxygen–Na+ radial distribution functions
for chondroitin. A = A-type chondroitin simulation (no Ca2+) using c36_jul20 force field. ACal = A-type chondroitin
simulation with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. O = O-type chondroitin simulation (no Ca2+) using c36_jul20 force field. OCal = O-type chondroitin
simulation with Ca2+ using c36_jul20 force field. O’Cal = O-type chondroitin simulation with Ca2+ using
c36_jul17 force field. In each panel, the four different colored traces
are from four independent simulations. Each 300 ns simulation has
been analyzed in 100 ns blocks.
Sulfate terminal oxygen–Na+ radial distribution
functions in chondroitin. ACal = A-type chondroitin simulation
with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using c36_jul17
force field. In each panel, the four different colored traces are
from four independent simulations. Each 300 ns simulation has been
analyzed in 100 ns blocks.Carboxylateoxygen–Na+ radial distribution functions
for chondroitin. A = A-type chondroitin simulation (no Ca2+) using c36_jul20 force field. ACal = A-type chondroitin
simulation with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. O = O-type chondroitin simulation (no Ca2+) using c36_jul20 force field. OCal = O-type chondroitin
simulation with Ca2+ using c36_jul20 force field. O’Cal = O-type chondroitin simulation with Ca2+ using
c36_jul17 force field. In each panel, the four different colored traces
are from four independent simulations. Each 300 ns simulation has
been analyzed in 100 ns blocks.
Association between Chondroitin Strands
The interpolymer
minimum distance gives an indication of whether or not there is association
between the two chondroitin polymer strands at any given time during
the simulations. The two polymers largely stay dissociated regardless
of the force field version or the presence of Ca2+, with
one notable exception: for O-type chondroitin with Ca2+ using the c36_jul17 force field (Figure , O’Cal), in the second
half of two of the quadruplicate simulations, there is continuing
association as indicated by a continual very low interpolymer minimum
distance. Further analysis of these two trajectories revealed that
they both contain a bound Ca2+ that directly bridges between
a carboxylate moiety on one polymer and a carboxylate moiety on the
second polymer throughout this time. That is, this Ca2+ cation is simultaneously within the first interaction shell of carboxylateoxygen on both the polymers in the system (Figure ). On the one hand, this is not especially
surprising, given the very strong binding interaction between these
atom types in c36_jul17. On the other hand, such behavior is not seen
for A-type chondroitin using this force field version (Figure , A’Cal).
We note that it would be helpful to extend the simulation lengths
and also to add simulations with more and fewer numbers of Ca2+ cations to better quantitate the effect of Ca2+ on chondroitin polymer association. However, this is not currently
feasible, given the computationally demanding nature of the simulations
arising from the large system sizes (∼190,000 atoms). With
this limitation in mind, additional analysis of the behavior of the
individual polymers (described below) provides some insights into
this observation.
Figure 9
Interpolymer minimum distances. A = A-type chondroitin
simulation
(no Ca2+) using c36_jul20 force field. ACal =
A-type chondroitin simulation with Ca2+ using c36_jul20
force field. A’Cal = A-type chondroitin simulation
with Ca2+ using c36_jul17 force field. O = O-type chondroitin
simulation (no Ca2+) using c36_jul20 force field. OCal = O-type chondroitin simulation with Ca2+ using
c36_jul20 force field. O’Cal = O-type chondroitin
simulation with Ca2+ using c36_jul17 force field. In each
panel, the four different colored traces are from four independent
simulations.
Figure 10
Intermolecular association between O-type
chondroitin polymer strands
bridged by Ca2+. The two chondroitin polymer strands are
colored green and purple, respectively, and bound Ca2+ cations
are shown as orange spheres. The conformation is from a simulation
with the c36_jul17 force field (i.e., O’Cal).
Interpolymer minimum distances. A = A-type chondroitin
simulation
(no Ca2+) using c36_jul20 force field. ACal =
A-type chondroitin simulation with Ca2+ using c36_jul20
force field. A’Cal = A-type chondroitin simulation
with Ca2+ using c36_jul17 force field. O = O-type chondroitin
simulation (no Ca2+) using c36_jul20 force field. OCal = O-type chondroitin simulation with Ca2+ using
c36_jul20 force field. O’Cal = O-type chondroitin
simulation with Ca2+ using c36_jul17 force field. In each
panel, the four different colored traces are from four independent
simulations.Intermolecular association between O-type
chondroitin polymer strands
bridged by Ca2+. The two chondroitin polymer strands are
colored green and purple, respectively, and bound Ca2+ cations
are shown as orange spheres. The conformation is from a simulation
with the c36_jul17 force field (i.e., O’Cal).
Polymer Compaction
End-to-end distance
and the radius
of gyration provide simple measures of the compactness of the linear
chondroitin polymers. Both sulfation and the addition of Ca2+ favor more compact conformations (Figure ). The effect of Ca2+ is especially
dramatic in the case of c36_jul17, where A-type (i.e., sulfated) chondroitin
strongly favors more compact conformations than chondroitin in the
other five types of simulations (Figure , A’Cal). Driving this
behavior is the tight binding of Ca2+ observed in the c36_jul17
parametrization. As discussed above, in the case of O-type chondroitin,
this association drove interstrand association (Figure , O’Cal). In the case of
A-type chondroitin, Ca2+ binding drives intramolecular
association instead such that instead of forming a bridging interaction
between the two polymers in the system, bound Ca2+ forms
a bridging interaction between functional groups in the same polymer,
which manifests as bends and kinks, and therefore a reduced end-to-end
distance and radius of gyration (Figure ). While this effect is less dramatic with
the NBFIX additions present in c36_jul20, it is nonetheless present
such that the addition of Ca2+ favors more compact conformations
(Figure , A vs ACal and O vs OCal) and sulfated chondroitin samples
more compact conformations in the presence of Ca2+ than
does nonsulfated chondroitin (Figure , ACal vs OCal). These effects
can be attributed to a combination of compact conformations stabilized
by both the binding of Ca2+ and by intramolecular hydrogen
bonding involving sulfate (Figure ).
Figure 11
Polymer radius of gyration vs end-to-end distance for
the 200–300
ns interval. A = A-type chondroitin simulation (no Ca2+) using c36_jul20 force field. ACal = A-type chondroitin
simulation with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. O = O-type chondroitin simulation (no Ca2+) using c36_jul20 force field. OCal = O-type chondroitin
simulation with Ca2+ using c36_jul20 force field. O’Cal = O-type chondroitin simulation with Ca2+ using
c36_jul17 force field.
Figure 12
Intramolecular association
bridged by Ca2+ in A-type
chondroitin. The chondroitin polymer strand is colored as a gradient
based on the sequence position, and bound Ca2+ cations
are shown as orange spheres. The conformation is from a simulation
with the c36_jul17 force field (i.e., A’Cal).
Figure 13
Compact A-type chondroitin conformation stabilized by
Ca2+ binding and by intramolecular hydrogen bonding involving
sulfate.
The chondroitin polymer strand is colored as a gradient based on the
sequence position, and bound Ca2+ cations are shown as
orange spheres. The conformation is from a simulation with the c36_jul20
force field (i.e., ACal).
Polymer radius of gyration vs end-to-end distance for
the 200–300
ns interval. A = A-type chondroitin simulation (no Ca2+) using c36_jul20 force field. ACal = A-type chondroitin
simulation with Ca2+ using c36_jul20 force field. A’Cal = A-type chondroitin simulation with Ca2+ using
c36_jul17 force field. O = O-type chondroitin simulation (no Ca2+) using c36_jul20 force field. OCal = O-type chondroitin
simulation with Ca2+ using c36_jul20 force field. O’Cal = O-type chondroitin simulation with Ca2+ using
c36_jul17 force field.Intramolecular association
bridged by Ca2+ in A-type
chondroitin. The chondroitin polymer strand is colored as a gradient
based on the sequence position, and bound Ca2+ cations
are shown as orange spheres. The conformation is from a simulation
with the c36_jul17 force field (i.e., A’Cal).Compact A-type chondroitin conformation stabilized by
Ca2+ binding and by intramolecular hydrogen bonding involving
sulfate.
The chondroitin polymer strand is colored as a gradient based on the
sequence position, and bound Ca2+ cations are shown as
orange spheres. The conformation is from a simulation with the c36_jul20
force field (i.e., ACal).As far as sulfation favoring compact conformations is concerned,
this is not necessarily an intuitive result in the context of the
simulations without calcium. In these simulations
having 140 mM NaCl only, the ensemble of A-type chondroitin conformations
is more compact than that of O-type (Figure , top row). A-type chondroitin has twice
the negative charge density as O-type, and the association of Na+ with sulfate and carboxylate is not especially strong based
on the radial distribution function data. Thus, one might reasonably
expect A-type to prefer more extended conformations relative to O-type
because of intramolecular charge–charge repulsion and the drive
to maximally solvate carboxylate and sulfate functional groups. However,
this is not the case. Rather, the presence of sulfate groups enables
intramolecular hydrogen bonds involving sulfate, similar to that depicted
in Figure , which
is an effect independent of Ca2+.
Conclusions
Based on the present simulations of A-type and O-type chondroitin,
both sulfation and Ca2+ favor more compact chondroitin
20-mer conformations. While existing experimental data demonstrate
the possibility for Ca2+ to form bridging interactions
between strands of chondroitin sulfate,[15,18] we find that
such association between 20-mers of A-type chondroitin is sensitive
to the details of force-field parametrization (Table ): an increase in the rmin force-field parameter from 3.067 Å[36] (c36_jul17) to 3.232 Å[37] (c36_jul20) for the interactions between carboxylate oxygens and
Ca2+ dramatically decreases Ca2+ binding to
chondroitin. This in turn prevents Ca2+-mediated intra-
and interchain bridging interactions between carboxylate groups.Force-field parametrization is a balance between generalizability/simplicity
and accuracy/complexity. For example, the need for carefully balancing
nonbonded interactions involving Ca2+ with carboxylate
has been well documented.[37,55−60] With regard to phosphate and sulfate, in both c36_jul17 and c36_jul20,
the same atom type is used for the terminal oxygen atoms on both of
these types of functional groups. This means that the only parameter
available for distinguishing nonbonded interactions between another
atom and either a sulfate or phosphate terminal oxygen is the partial
charge for that oxygen. The present results suggest a closer study
of whether additional complexity needs to be introduced into the force
field in the form of a new atom type for such sulfateoxygen atoms
in order to achieve modeling accuracy on the same level as that for
the corresponding phosphate atoms;[35] indeed,
the application of NBFIX parameters has been shown to have a marked
effect on bacterial membrane properties in simulations where Ca2+ associates with phosphateoxygen atoms in membrane molecules.[61] If a new separate atom type is ultimately deemed
necessary, it will additionally need to be determined whether combining
rules using atom-wise LJ parameters are sufficient to balance water–sulfate
vs ion–sulfate interactions, or whether NBFIX parameters will
be required to properly capture the latter after parametrizing atom-wise
parameters targeting the former.From the data presented here,
the c36_jul20 parametrization currently
favors Ca2+ retaining its first solvation shell as opposed
to directly interacting with sulfate. This is reminiscent of the finding
that in simulations of calbindin protein, Ca2+ exhibited
such behavior relative to carboxylate when using the GROMOS96 and
CHARMM22 force fields versus exhibiting ready loss of this shell and
tight direct binding to carboxylate when using the OPLS-AA force field,[55] which demonstrates the strong force-field dependence
of Ca2+ solvation.We note that in addition to uncertainties
arising from the sensitivity
of the results to force-field parametrization, a further limitation
to the present approach for understanding the atomic-resolution behavior
of chondroitin polymers with Ca2+ in solution is the practical
limitation on the system size and simulation timescale imposed by
computing software and hardware for molecular dynamics. In contrast
to the 20-mers studied here, biological CS chains may exceed ten times
this length.[2] The direct simulation of
such large CSpolymers would therefore require a simulation system
with 103 times as many particles as the ones in this study,
which puts the required particle count on the order of 300 million.
Barring breakthrough advances in software and/or hardware, the routine
performance of such simulations is out of the question for the foreseeable
future. This leaves the multiscale modeling approach[3] as the best option for attempting to understand the conformational
properties of CS and CS PGs, with all-atom explicit-solvent simulations,
like those presently described and using carefully parametrized force
fields, informing the development, validation, and interpretation
of less-detailed but more computationally efficient modeling methods.[4,14]
Authors: Kyungreem Han; Richard M Venable; Anne-Marie Bryant; Christopher J Legacy; Rong Shen; Hui Li; Benoît Roux; Arne Gericke; Richard W Pastor Journal: J Phys Chem B Date: 2018-01-22 Impact factor: 2.991
Authors: Olgun Guvench; Shannon N Greene; Ganesh Kamath; John W Brady; Richard M Venable; Richard W Pastor; Alexander D Mackerell Journal: J Comput Chem Date: 2008-11-30 Impact factor: 3.376