Hello, I'm Nathan Brown
from the Institute of Cancer Research
And I'm going to talk to you today
about structure-based drug design
and the computational methods
we apply in developing
medicinal chemistry strategies.
So structure-based drug design,
what is it we're trying to achieve?
We're using computational
methods to design, select,
synthetic chemistry targets
that will then contribute positively
to the medicinal chemistry project.
And how we achieve this
is to work around this design,
make test iterative cycle
where we identify new molecules to make,
we enumerate those molecules
in the computer.
We calculate predictions,
and synthesize and test them,
by far the most time-consuming
part of the cycle,
and then extensive data analysis
that allows us to distill down
the learning from
the synthesis and testing
to make even better decisions
in the next cycle.
So in this talk I'm going to cover
a few different types
of the main methods
that we apply in drug discovery
with computational methods.
First, we're going to cover
and scaffold hopping
which is a subset
of bioisosteric replacement.
We're then going to cover
It starts when we've got
a hit compound of interest,
how to identify other compounds
that are analogs of that
to validate that chemotype of that scaffold.
Then I'm going to move on
to virtual library design
where we can enumerate virtual libraries
and make predictions
about those libraries
that can then be tested
using structure-based methods.
We'll touch briefly
on homology modeling.
This is where we predict
the protein structure,
given the sequence of that protein
and also the protein structure of
a similar protein targets of interest.
Then we'll cover the elucidation
and what the pharmacophore is in context
and how we use pharmacophores
to search large libraries of compounds
by taking into account
the three dimensional structure
of the molecules under investigation.
we'll move into virtual ligand docking,
that's how we can simulate
the docking of ligands into proteins
and protein binding sites
to understand potential interactions
that can be exploited
in optimizing potency
in the drug program.