Chemistry Reference
In-Depth Information
surface shapes are often assumed to likely share similar drug-like properties
suggesting that 3d LBVS shape comparison techniques can offer a protocol for
discovering novel drug leads. Due to important conformational changes (induced
by binding), it may be desirable to generate a diverse ensemble of conformers
[387-391].
Gaussian density functions are an efficient and elegant approach to represent and
compare molecules. These can be first aligned with Cartesian coordinate axes by
diagonalization of a second order steric multipole matrix, calculated from the
atom-centered Gaussian functions. Subsequently, minimizing the sum of atomistic
Gaussian overlaps can superpose pairs of molecules [392, 393].
Spherical harmonics (SH) functions can also be used for fast shape-based protein-
ligand docking and virtual screening. These methods use SH polynomial
expansions in order to represent the surface shape and other molecular surface
properties. Subsequently, the special rotational properties of SH functions are
used to perform fast Fourier-based correlations yielding efficiency in high-
throughput receptor-based virtual screening [394-396]
.
BINDING SITE-BASED
In terms of physicochemical properties such as shape, size, hydrophobicity and
polar interactions, all biological targets possess ligand binding pockets
complementary to their ligands. The similarity of these properties in binding
pockets for diverse proteins should lead to similarity of bound ligands.
This considered, it should be possible to apply, on a wide scale, computational
approaches designed to detect physicochemical similar properties of binding
pockets. This could also facilitate identification of potential off-targets as well as
the whole multiple-target ligand design process [397, 398].
INVERSE MOLECULAR DOCKING
Potent binding of a small molecule ligand is not guaranteed by the presence of a
protein-binding pocket. It is desirable to be able to directly predict protein-ligand
binding complexes as well as their binding affinities.
