Chemistry Reference
In-Depth Information
Today, as refi nement in relation to early simple procedures, intricate hybrid
MM/QC methods are applied [8]. The recent progress in methodology is excep-
tional and opens new horizons for further advances in carbohydrate modeling [9].
As to the shape, it is not only the inherent fl exibility around the glycosidic bond
that matters, as explained in the next part.
2.5
Additional Factors Infl uencing the Shape of Oligo- and Polysaccharides
The shape of the carbohydrates and oligosaccharides is also infl uenced by factors
resulting from the carbohydrate pendant groups/side chains. For example, there
are six fl exible groups (OH and CH
2
OH) present in glucose. Each such group has
three possible conformational states, resulting in 3
6
= 729 conformations for a
given
anomer. This number is dramatically increased when moving from 3
10
in a disaccharide (see Figure 2.2a for lactose
α
or
β
i
) to 3
n
in the case of oligosaccharides
(
n
describes the number of fl exible side chains). However, not all of the 3
χ
possible
orientations are populated in complex glycans (or even a disaccharide) due to pref-
erences resulting from both intramolecular forces and interactions with surround-
ing molecules (proteins, solvent and other molecules present in the biological
environment). Figure 2.4 illustrates the superimposed small subset of 100 low-
energy conformations of
n
β
-lactose obtained by running the Macromodel program.
The
values were restrained and only the conformational changes of side
chains were calculated. The fi gure gives an impression of the challenges inherent
to conformational analysis of glycans, aimed at fi nding the most probable shape of
the molecule. Modeling and predicting the conformational properties of glycans
are evidently a complex task, encompassing characterization of ring conformations
as well as conformations around the glycosidic bond and of the side chains.
In addition to the internal factors infl uencing carbohydrate shape already dis-
cussed, one should be aware of the additional infl uence coming from the environ-
ment. Taking into consideration the presence of water in living cells, it is clear
that a solvent effect has to be included in modeling studies in order to properly
describe glycan conformations. The most commonly encountered solvent effect is
due to water molecules, although solvents other than water may be used in the
course of NMR measurements, in order to pick up solvent- exchangeable hydroxyl
protons in an aprotic solvent [6]. In the simplest models the solvent is treated as
a bulk dielectric continuum, with solvation effects represented by electrostatic,
dispersion and cavity terms. Computationally more demanding are the discrete
models of solvents, especially those, where several hundreds of solvent molecules
form a solvation box using periodic boundary conditions. To give an impression
on the molecules processed in this procedure, a hydrated lactose molecule within
a water box of 30
Φ
,
Ψ
30 Å
3
is presented in Figure 2.5 as an example for the
discrete solvation model. Having provided the fundamentals of modeling includ-
ing the solvent, we can now present information on actual case studies.
×
3 0
×
