Modelling molecules

06 February 2015

Interview with

Michele Vendruscolo, University of Cambridge

Enzymes hold the key to biochemistry. Without them, life-critical chemical reactions couldn't happen fast enough to keep anyone alive. And now we know much more about how they work, we'd like to engineer these catalysts to do other important jobs. But to do that we need to know how they grab hold of their chemical substrates, and what changes in shape they temporarily need to adopt to bring about a reaction. Cambridge Chemist Michele Vendruscolo has been using nuclear magnetic resonance images of the enzyme lysozyme to model the process...

Michele - The problem is to understand how the molecule grabs another molecule and then releases it. This is a problem of molecular movement. So, we need techniques that are able to characterize the movements but a molecular level, typically nanometres. The particular technique that have used is called nuclear magnetic resonance spectroscopy, and is based on the properties of the interaction of electro-magnetic radiation with atomic nuclei. In simple terms, this is a technique that enables one to detect how molecules move. And this is the ideal technique for describing the set of movements that are needed to capture and release molecules.

Chris - Are the proteins, the enzymes, not continuously moving around all the time. So, why do you not get a sort of blurry image when you try to see those movements? How do you get them down to a resolution where you can watch them almost like clockwork to see those movements?

Michele - You actually get a blurred picture. And so the point is how to disentangle from this average information all the individual components of it. In case that we have studied, there is a fundamental stage which is called ground state, and then there is another interesting state which is called intermediate state and the intermediate state has a much lower probability of being present but is essential because it's the state that the molecule that is acted upon by enzymes as to go through in order to be released.

Chris - So how do you do it? Do you somehow freeze time with the enzyme in one form and look at it, and then freeze time in the other form and look at it? Or do you look at all the forms and then work out what shape it must be in order to produce the mixture of images you see?

Michele - It is model building in the end. So, because we have an average information about the population of different structures, but we know there are different structures. So, we use theoretical modelling and computer simulations to build realistic models of these structures and then we require that the signal that we see is coming out as an average from the models that we generate.

Chris - And when you do this, what has this revealed about the behaviour of this enzyme system that we didn't have an insight into before?

Michele - Well, despite the fact that it's fairly obvious that the molecule, that the enzyme has to capture and release its substrate. We simply didn't know their atomic structures. We knew that they ought to be there but we didn't have a model for that. So, what we contributed is, in the particular case of an enzyme - it's called lysozyme - we know now the atomic structure of this intermediate state for release. And this is helpful because in the long term this may lead to a better ability to design enzymes.

Chris - Because we're obviously in a position now where we can begin to manipulate proteins. Now if you understand how they work, then we can make proteins actually do certain chemical reactions that we want them to do that they currently don't exist in nature with the capacity to achieve.

Michele - Yes. This is actually a very small component of a much broader area of research, which as you said, we are starting to become capable of manipulating molecules and this is an astonishing ability because the scale at which these processes take place are typically a billion times smaller than our everyday life experience. So, the ability of working over these landscapes I think is continuous source of amazement.

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