Handbook of Solvents - George Wypych - ChemTech - Ventech!

720 Ranieri Urbani and Attilio Cesàro
bilities associated with the conformers and therefore produce a rearrangement of statistical
weights among conformers and, thus, a variation of the average properties of the system, as
for example illustrated by the changes of the chain dimension parameters (see below Figure
12.2.11). Calculated average data like dipole moment, μ, linkage rotation, Λ, and pro-
ton-carbon coupling constants across glycosidic linkage,
3 JC1-H4 and 3 J C4’-H1, for
β-D-maltose 14 and β-D-mannobiose 45 in different solvents are reported in Table 12.2.2.
These results show that the equilibrium composition of dimer conformers depends strongly
on the solvent and that the departure from the in vacuo conformation increases with increasing
solvent dielectric constant. For mannobiose the determining factor of the solvent effect
on the conformation is the intra-residue electrostatic interaction, which depends on ϕ and ψ
in the same manner as the dipole moment.
Table 12.2.2. Calculated average values of dipole moment, four-bonds proton-carbon
coupling constant and linkage rotation of β-D-maltose and β-D-mannobiose in
different solvents at 25°C
Solvent ε ϕ, deg ψ, deg μ, debye
3
JC1-H4, Hz
3
JC4�-H1, Hz Λ, deg
vacuum - -21 -28
solute: β-D-maltose
3.80 4.2 4.5 -31
1,4-dioxane 2.21 -22 -22 3.89 4.1 4.5 -30
pyridine 12.40 -24 -39 4.02 4.0 4.5 -27
ethanol 24.55 -24 -41 4.09 3.9 4.5 -27
methanol 32.70 -25 -46 4.17 3.9 4.5 -25
DMSO 46.68 -24 -41 4.10 3.9 4.5 -28
water 78.30 -28 -65 4.47 3.7 4.7 -19
solute: β-D-mannobiose
vacuum - 81 -18 6.00 2.29 4.14 77
1,4-dioxane 2.21 82 -19 5.92 2.23 4.15 76
pyridine 12.40 91 -22 6.01 1.95 4.22 69
methanol 32.70 97 -24 6.08 1.72 4.25 54
DMSO 46.68 94 23 6.05 1.84 4.23 67
water 78.30 100 -18 6.27 1.53 4.32 57
It should be pointed out that even the small variations in the dihedral angles due to the
presence of solvent molecules may produce a large change on a macromolecular scale, as
discussed above.
12.2.4.2 Molecular dynamic methods
One of the most powerful theoretical tools for modeling carbohydrate solution systems on a
microscopic scale and evaluating the degree of flexibility of these molecules is the molecular
dynamics technique (MD) which has become popular over the last two decades. The first
reported works of MD carbohydrate simulation appeared in 1986 54,55 and since then an in-