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I'm Dr. Graham Ladds in the Department of Pharmacology at the University of Cambridge.
I'm going to be talking today about how we've been using
computational modeling techniques to investigate
G-protein-coupled receptor signaling dynamics.
I'm sure the vast majority of people who will be listening
to this know quite a bit about G-protein-coupled receptors,
but we'll start with just a brief introduction to how they function,
and where computational modeling can come in and explain things.
GPCRs are typically seven-transmembrane receptors.
They typically bind agonists on the outside of the cell and
transmit the signal to an intracellular or second messenger,
cascaded with inside a cell.
The example I've shown here is a GPCR coupled to a single heterotrimeric G protein,
which is known as Gq, and it activates an IP3 cascade, bringing about a cellular response.
This would have been the idea that we understood about
GPCRs up until more recently in the last 10 years or so.
Now, we understand that they're much more complex with
a single receptor being able to bind multiple ligands.
As we can see here on this slide,
I've depicted a number of different agonists binding into a single receptor,
bringing about a range of different signaling cascades,
be that signaling through different intracellular the G proteins.
Each mammalian cell typically contains somewhere in
the region of 16 different G Alpha subunits,
and all of these can bring about different intercellular signaling cascades.
Furthermore, we now understand that GPCRs can also bind to proteins known as arrestins,
and this promotes either internalization or,
in fact, independent signaling from the different G-proteins.
Now, when we first started working on GPCRs,
we always thought that this mammalian based system was very complex.
Therefore, if we were going to apply any form of modeling techniques,
we actually need to get down to a more simple understandable system.
To do that, we chose to use a range of different cells and organisms.