Bioorganic Chemistry
29
atoms in the molecule), which results
in portions of the molecule traversing
energy barriers that could not normally
be traversed. The result of this is that
the conformations of the molecule are
explored. ‘‘Cooling’’ of the molecule in
thesimulationthenallowsthemoleculeto
settle into a local energy minimum. With
enough rounds of heating and cooling,
it is then possible to Fnd the global
energy minimum.
Molecular mechanics is an effective
tool for predicting conformational energy;
however, it cannot describe the electronic
nature of a molecule, such as the energy of
a transition state associated with the break-
ing of a bond, or overall reaction energies.
±or this and other applications where a
detailed understanding of the electronic
nature of a molecule is needed, quan-
tum mechanical methods are required.
The list of approaches is vast, including
semiempirical methods (e.g. AM1, PM3),
Hartree ±ock methods, and correlated
methods including Moeller–Plesset and
density functional methods. The common
element in all of these approaches is that
they estimate solutions to the Schr¨odinger
equation. As such, they are able to ad-
dress questions involving movement of
electrons (such as reaction energy), which
molecular mechanics is unable to. This
fundamental assessment of electron move-
ment and energy in a molecule comes
at a cost, which is the increased com-
putational resources demanded of these
methods.
A common aim in bioorganic chem-
istry is the design of small molecules to
target macromolecules. Modeling of the
structure of the small molecule can be
performed using the techniques described
above. Of further interest is modeling
the potential for interaction of the small
molecule with the target of interest. This
examination can be done ‘‘by hand’’ in
a
qualitative
fashion
using
interactive
molecular graphics (e.g. programs such
as MIDAS, Chimera, Rasmol). In addi-
tion, a range of docking programs exists
that allows for rapid generation of poten-
tial complexes and their assessment via
scoring functions. The algorithms used
by these programs are fast enough that
databases of
>
100,000 compounds can be
virtually screened for potential interaction
with a target macromolecule in a reason-
able amount of time (
∼≤
1 week). Dock-
ing programs include Dock, Autodock,
and ±lexX.
The methods described above for mod-
eling a molecule’s structure (molecular
mechanics, semiempirical, and
ab initio
methods) are in general
in vacuo
methods.
In other words, the result is a predicted
structure or energy based on the molecule
and its conformations while completely de-
solvated. ±or some molecules, in fact for
most molecules that are of interest to bioor-
ganic chemistry, this eliminates a very
important factor from the calculation – the
effect of solvent water. The presence of wa-
ter diminishes electrostatic interactions by
screening full and positive charges. In ad-
dition, it strengthens nonpolar–nonpolar
interactions through the hydrophobic ef-
fect. ±or a true and accurate simulation
of molecules in an aqueous environment,
solvation energy corrections have to be ap-
plied. There are multiple approaches to
doing this. One is to incorporate a shell
of explicit water molecules in the simu-
lation. This can be computationally very
demanding. More efFcient methods in-
clude so-called continuum methods, which
do not include individual water molecules
but model the solvent as a continuum.
These include the SM (Solvation Model)
methods of Cramer and Truhlar.
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