Our Group Research

Drug design of the future. Could the next generation of medicines be designed on the computer using the laws of quantum mechanics?

Technology has been advancing rapidly and now computers are everywhere. In our homes, on our commutes, in our hands, and increasingly used in our jobs too. Designing drugs is no different. Gone are the days of accidentally stumbling upon a wonder drug. For the past 50 years or so, computational chemistry has steadily gained the interest of research groups and pharmaceutical companies looking to speed up the process and reduce costs. With technology and computational simulations advancing, computational chemistry hopes to bring drug design into the technological 21st Century. (That link is to my first published paper…)

Although more knowledge goes into making today’s drugs, traditional drug discovery methods are still to some extent an exercise in trial-and-error. High-Throughput Screening has aided the arduous task of trawling through thousands of potential drug candidates, but those selected from the large libraries (100 compounds or so) are still required to be made and tested in the lab. Not only does this waste money, creating many compounds which will never see the light of a pharmacy shelf, but it is also a great expense in resources and the precious time of synthetic chemists. However, one of the great discoveries of the twentieth century — quantum mechanics — could hold the key to improving the efficiency of the drug design process.

Computationally aided drug design works to simulate and predict how well a drug will bind to the protein target in question. Using crystal structures, we can visualise a protein target, design a drug to bond with said target, and subsequently implement the desired reaction; be that inhibition, activation etc. Bonds, like gravity, can be described as a force; some of them can be strong (i.e. intramolecular force such as a covalent bond), or weak (i.e. intermolecular force). To achieve an accurate representation of protein-ligand binding, we focus on intermolecular forces. As well as dictating various properties of the drug (such as boiling and melting points), they also determine the drug’s ability to bind well to the target.

Where can we see such forces in everyday situations? Although intermolecular forces are weaker than gravity, we can still observe their effects as without these forces molecules wouldn’t stick together. To achieve this cohesion, a common intermolecular force is the hydrogen bond. An example of such bonds can be seen between the base pairs of our DNA; hydrogen bonds are strong enough to hold this vital structure together, but weak enough that they can allow for the unzipping of DNA during cell replication. Another type of intermolecular force is the van der Waals force; these are the weakest form of a bond but are in fact used by geckos to help them adhere to surfaces and scale. Our last example of an intermolecular force is an electrostatic force, which can be observed when you rub a balloon on your hair.

A recent paper by Cole et. al. demonstrates how we can use quantum mechanics to predict how well a drug will bind to the protein target. Quantum mechanics is something you may have heard banded around on Brian Cox documentaries, but how do we use it in drug discovery? Quantum mechanics is the most accurate description we currently have of how matter interacts, but it is very complicated. It creates the most accurate and detailed picture of interactions; detailing all the electrons. However, this requires a lot of computer power and time, neither of which we have. Let’s imagine we are drawing the Earth with everyone and everything on it. To simulate what’s happening on Earth we would have to repaint the image every few seconds to include what everyone is up to (for a protein it is every femtosecond, that’s one quadrillionth of a second; it’s really small); this would be a mammoth task. Instead let’s zoom out a bit, lose some detail, but make the painting much faster (e.g. just painting the continents and oceans now).

That’s what we’re doing in our drug design method: we lose the detailed electronic structure of the potential drugs but retain the accuracy. We speed up the process and fill in our image a lot faster whilst retaining information about the atoms and the intermolecular forces, through which they interact with one another. Our method is called QUBE (QUantum mechanical BEspoke).

Using quantum mechanics in this way enables us to predict how well drugs will bind with the target, by deducing the possible interactions the drug will make with the protein. As with any new method, the use of quantum mechanics in computationally aided drug design must be tested thoroughly. To do this, we are comparing experimental data of known drugs/compounds, with computed values we have gathered using our method, QUBE. The recent paper by Cole et. al. used this technique to predict how six small molecules would bind to the protein lysozyme, before comparing with experimental results. Their simulated findings using QUBE were in good agreement with experimental values, showing an accurate method of predicting drug interactions. If we continue to test and improve the QUBE method, we have the potential to quicken the drug discovery process dramatically.