As you know, all cells are enclosed within what we call a membrane, a cellular membrane,
that separates the interior of the cell from outside. But, at the same time, you need to
exchange the materials between the two sides of the membrane. You need to bring in nutrient
molecules and to expel waste molecules. And, in order to do that, specialized proteins
have been evolved which are called membrane transporters.
There are kinds of membrane transport proteins that we call channels. And, when you open
a channel, you just have an open pathway for substrate ions, sugar molecules, etc. etc.
to go through. Whereas, in the case of membrane transporters, which we refer to as active
pumps, they cannot be open to both sides of the membrane at the same time. They have to
work against this and pump in the opposite direction. And because of this fundamental
difference between active transporters and membrane channels, they have to undergo very
large conformational of changes -- you recruit the substrate, you have to close on one side,
before you open the other side. And that is the only way that you can have directional
transport. Experimentally, we cannot describe the entire
transition process. So, the structure of a molecule you can still get that from certain
experimental approaches. But how it moves is extremely challenging for experimental
approaches. We might be able to get the initial and the final states, for example from x-ray
crystallography, but how it goes from the initial state to the final state is completely
unknown because we cannot reach the spatial and temporal resolutions that are needed to
describe these motions. And the computational methods are the only way to describe this.
The Holy Grail of the structural biology of membrane transporters is to describe this
whole transition. Why? Because right now we are working with only initial and final structures
as targets; for example, for drug design. We can only design drugs for this form and
this form of the protein. Whereas, if you know all the intermediate forms adopted by
the protein during the function, then you have many, many, many more targets to attack.
And the chance of finding a selective drug that does not work with other proteins and
does not cause side-effects is much higher if you know all the intermediates involved
in the function of these transporters. What we did in this work was, for the first
time, to describe the motion, the kind of structural change and transition that connects
these two dots through this kind of broad computational simulation.
What we do is we start with the initial structure of the protein, and then we push the protein
along different pathways to go from the initial state to the final state. And then, along
each pathway, we can measure how hard it is for the protein and compare these pathways
to see what pathway might be the most relevant pathway.
So, in order to act as a pump, you need to, of course, have a source of energy, you need
to have some sort of fuel. The cell does not have access to very high energies. All cellular
processes just use a few kilocalories per mole of energy. And, in order to find how
it happens really in a cell, in nature, we have to identify pathways that require really
low amounts of energy.
The way these calculations function is that we calculate the interaction between individual
atoms in a molecule, and we have to do this for all pairs of atoms. And, if you can imagine
if your molecular system includes several hundred thousand atoms, you have a lot of
calculations to do. One of the main outcomes of our work was that
it is actually very difficult for the protein to directly, in a linear fashion, go to its
final state. It has to take many, many turns during its function. And, it turns out, by
allowing the protein to take a more complex transition, we can find much better pathways
that are most likely relevant to what happens in nature.
It is almost like a dance rather than a simple move within the protein structure. So you
have a set of coordinated motions. The order of these motions was not known before our
simulations. But we are showing here that the protein is most compliant if you do these
stages and moves in a certain order. And that fits and explains the overall mechanism of
the protein. So, in this paper, we looked at an ABC transporter.
A prominent member of this family is P-glycoprotein, which is a major protein involved in multi-drug
resistance in cancer cells. They essentially pump drugs outside the cell, and that is a
mechanism of developing resistance against anti-cancer drugs. If we can find out how
to block these proteins, we might be able to have a much better penetration of drugs
into cancer cells, for example.