In this thesis, a novel strategy (MOBILE
(Modelling Binding Sites Including
Ligand Information
Explicitly)) was developed that models protein
binding-sites
simultaneously considering information about the binding mode
of bioactive ligands during the homology modelling process. As
a result,
protein binding-site models of higher accuracy and
relevance can be
generated. Starting with the (crystal)
structure of one or more template
proteins, in the first step
several preliminary homology models of the target
protein are
generated using the homology modelling program MODELLER.
Ligands
are then placed into these preliminary models using
different strategies
depending on the amount of experimental
information about the binding mode of
the ligands. (1.) If a
ligand is known to bind to the target protein and the
crystal
structure of the protein-ligand complex with the related
template
protein is available, it can be assumed that the
ligand binding modes are
similar in the target and template
protein. Accordingly, ligands are then
transferred among
these structures keeping their orientation as a restraint
for
the subsequent modelling process. (2.) If no complex crystal
structure
with the template is available, the ligand(s) can
be placed into the template
protein structure by docking, and
the resulting orientation can then be used
to restrain the
following protein modelling process. Alternatively, (3.) in
cases where knowledge about the binding mode cannot be inferred
by the
template protein, ligand docking is performed into an
ensemble of homology
models. The ligands are placed into a
crude binding-site representation via
docking into averaged
property fields derived from knowledge-based
potentials. Once
the ligands are placed, a new set of homology models is
generated. However, in this step, ligand information is
considered as
additional restraint in terms of the
knowledge-based DrugScore protein-ligand
atom pair
potentials. Consulting a large ensemble of produced models
exhibiting di erent side-chain rotamers for the binding-site
residues, a
composite picture is assembled considering the
individually best scored
rotamers with respect to the ligand.
After a local force-field optimisation,
the obtained
binding-site models can be used for structure-based drug
design
