Study of Carbohydrate−Aromatic Interactions
A R T I C L E S
The first conformer set (MD set) was obtained by running three MC/
SD runs of 5 ns each, starting from three conformers corresponding to
the three idealized geometries of Figure 3 (Conf. A, Conf. B, Conf. C,
15 ns total simulation) and saving 5000 structures for each run, using
an electrostatic cutoff of 20 Å, a van der Waals cutoff of 8.0 Å, and a
hydrogen bond cutoff of 4 Å. The simulation was performed at 300 K,
with a dynamic time step of 1.5 fs; the Monte Carlo acceptance ratio
was less 4%, and each accepted MC step was followed by an SD step.
Structures were sampled every 1 ps and saved for later evaluation,
monitoring both energetic and geometrical parameters. As expected,
the MC/SD protocol allowed for fast interconversion of the starting
conformers, so that the populations obtained from the individual runs
appeared to be converged within 5% and the interproton distances
differed by no more than 0.1 Å.
model of 2c in Figure 9 shows that the apolar hydrogen atoms
on the R-face of the sugar are in proximity with the van der
Waals surface of the aromatic residue, and the molecular orbital
representation of the HOMO-6 orbital (Figure 9b) indicates a
stabilizing bonding interaction between the sugar CH vectors
and the aromatic ring. The electrostatic potential of the aromatic
ring (Figure 10) appears slightly more positive on the face which
is in contact with the sugar, suggesting that the sugar CHs are
acting as weak acids on the π-electron cloud of the phenyl ring.
Preliminary results obtained from NOESY spectra of 2c in
CD3OD solution30 appear to indicate a weakening of the NOE
contacts and possibly suggest a role for hydrophobic packing
in defining the molecule conformation. In light of the above
observations, the interaction between the aromatic ring and the
carbohydrate fragment in 2c-f could be best described as a
relatively extended contact between the two hydrophobic
surfaces involving significant electron overlap.
The second set (MM set) was obtained by Multiple Minimization
of the MD set (i.e., of the total 15 000 snapshots saved during the
molecular dynamics simulations) using the same force field and cutoff
applied in the MD set. The third set of conformations (Fitting set) was
obtained by fitting the NOE data, using a procedure that we have
recently described.21 Briefly, the MM set of conformations was clustered
in the three clusters A, B, and C of Figure 3 using the ø(C(O)-CR-
CHDC4-CHDH4) descriptor as detailed above. Interproton distances
and NOE intensities (%) were derived for each cluster using a full
matrix relaxation calculation extended to all the members of each
cluster. An initial value was assigned to the weight of each cluster,
and the conformer distribution was estimated by fitting the Noeprom-
based % overall NOE intensities to the experimental ones.
Aromatic amino acid residues are often present in the binding
sites of carbohydrate-binding proteins. The resulting carbohy-
drate-protein complexes are characterized by a placement of
the sugar in a roughly parallel orientation relative to the plane
of the aromatic ring, similar to the one observed in compounds
2c-f. These molecules, therefore, can serve as simple and
tunable models for study of the nature of carbohydrate-aromatic
interactions and the implications in the molecular recognition
of carbohydrates.
B. Ab initio Calculations. Full geometry optimizations, including
structural, orbital, and various electrostatic property analysis, were
carried out using the GAMESS software package.38 Structural computa-
tions were performed using hybrid density functional theory (HDFT).
The HDFT method employed Becke’s three-parameter functional in
combination with a nonlocal correlation provided by the Lee-Yang-
Parr expression with both local and nonlocal terms, B3LYP.39 The
DZV(2d,p) basis set40 was used. Full geometry optimizations were
performed and uniquely characterized by calculating and diagonalizing
the matrix of energy second derivatives (Hessian) to determine the
number of imaginary frequencies (0 ) minima; 1 ) transition state).
All energetics and Cartesian coordinates for the optimized geometries
are available in the Supporting Information.
Experimental Section
Computational Methods. A. Molecular Mechanics Calculations
and Generation of the Three Population Sets. All calculations were
performed using the MacroModel/Batchmin 8.534 package (Maestro-
version 6.0) and the AMBER* force field. Kolb’s parameters were used
for the hydroxyacid moiety.35 Bulk water solvation was simulated by
using MacroModel’s generalized Born GB/SA continuum solvent
model,36 which treats the solvent as an analytical continuum starting
near the van der Waals surface of the solute, and uses a dielectric
constant (ꢀ) of 78 for the bulk water and 1 for the molecule.
From the fully optimized structures, single-point energy calculations
were performed using the MP2 dynamic correlation treatment for further
analysis of energetics and properties. The optimal method was
determined using several levels of theory to establish self-consistency
in terms of basis sets as well as effects of dynamic correlation.
Additionally, these methods have been previously shown to be reliable
for the types of compounds considered here.41 Molecular orbital contour
plots and electrostatic potential plots, used as an aid in the discussion
of the results, were generated using the program 3D-PLTORB42 and
GAMESS, respectively, and depicted using QMView43 and MOLE-
KEL,44 respectively.
An initial conformational search was carried out using 10 000 steps
of the usage-directed MC/EM procedure following previously estab-
lished protocols.37 Extended nonbonded cutoff distances (a van der
Waals cutoff of 8.0 Å and an electrostatic cutoff of 20.0 Å) were used.
The output structures were clustered based on the improper dihedral
angle descriptor ø(C(O)-CR-CHDC4-CHDH4), which describes the
side-chain conformation. Three clusters were obtained, corresponding
to Conf. A, Conf. B, and Conf. C of Figure 3. Conformations with
values of the ø improper dihedral angle in the range 180° ( 60° were
clustered in the A family, those with ø in the range 60° ( 60° were
clustered in the B family, and those with ø in the range of -60° ( 60°
were clustered in the C family. In this way all the space was investigated
in all directions, without loosing information and no conformers were
outside of the defined staggered conformations (A, B, or C). The above
criteria were used also to define the A, B, and C populations of the
following sets.
NMR Methods. NMR spectra were recorded in a 5 mM D2O
solution using Bruker AVANCE 400, at 300 K. 1D, as well as 2D,
COSY, HSQC, and NOESY experiments were recorded using the
(38) Schmidt, M. W.; Baldridge, K. K.; Boatz, J. A.; Elbert, S. T.; Gordon,
M. S.; Jensen, J. H.; Koseki, S.; Matsunaga, N.; Nguyen, K. A.; Su, S.;
Windus, T. L.; Dupuis, M.; Montgomery, J. A. J. Comput. Chem. 1993,
14, 1347-1363 (www.msg.ameslab.gov/GAMESS/GAMESS.html).
(39) Becke, A. D. J. Chem. Phys. 1993, 98, 5648-5652.
The cluster leaders were used as starting structures for the dynamics
simulations.
(40) Dunning, T. H. J. Chem. Phys. 1970, 53, 2823-2833.
(34) Mohamadi, F.; Richards, N. G. J.; Guida, W. C.; Liskamp, R.; Lipton, M.;
Caufield, C.; Chang, G.; Hendrickson, T.; Still, W. C. J. Comput. Chem.
1990, 11, 440-467.
(41) (a) Milet, A.; Korona, T.; Moszynski, R.; Kochanski, E. J. Chem. Phys.
1999, 111, 7727-7735. (b) Perez-Jorda, J. M.; San-Fabian, E.; Perez-
Jimenez, A. J. J. Chem. Phys. 1999, 110, 1916-192. (c) Guerra, C. F.;
Bickelhaupt, F. M. J. Chem. Phys. 2003, 119, 4262-4273. (d) Zhang, Y.;
Pan, W.; Yang, W. J. Chem. Phys. 1997, 107, 7921-7925.
(35) Kolb, H. C.; Ernst, B. Chem.sEur. J. 1997, 3, 1571-1578.
(36) Still, W. C.; Tempzyk, A.; Hawley, R.; Hendrickson, T. J. Am. Chem. Soc.
1990, 112, 6127-6129.
(42) 3D-PLTORB; San Diego, 3D version, 1997.
(37) (a) Brocca, P.; Bernardi, A.; Raimondi, L.; Sonnino, S. Glycoconjugate J.
2000, 17, 283-299. (b) Bernardi, A.; Raimondi, L.; Zuccotto, F. J. Med.
Chem. 1997, 40, 1855-1862.
(43) Baldridge, K. K.; Greenberg, J. P. J. Mol. Graphics 1995, 13, 63-68.
(44) Flu¨kiger, P.; Lu¨thi, H. P.; Portmann, S.; Weber, J. MOLEKEL 4.0; Swiss
Center for Scientific Computing: Manno, Switzerland, 2000.
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