Drug Design – ACENET

Simulating Solutions: The Power of Computational Chemistry

Stijn De Baerdemacker says his research in theoretical chemistry is “fairly fundamental” and yet it doesn’t find itself very far away from real-world applications.

“Typically, when we think about chemistry, it’s about tubes and beakers and people in lab coats, and that’s still a big portion of what of what we do,” De Baerdemacker says. “However, it’s not only running the experiments, it’s also exploring what molecules you can make and how they can solve problems.”

In other words, he’s always looking to develop something new — a better material for a device, or a better drug for a disease, for example. And if you’re searching for the “holy grail” that will solve your problem, it’s very time-consuming, he says, because you have to assess all of the options.

“This is where computations come in, because on a computer, we are not bound by safety requirements,” he says. “We can just go in and try to simulate what will happen. That speeds up the discovery process by many orders of magnitude.”

De Baerdemacker applies various mathematical models that describe the structure of molecules to determine which ones would provide the most accurate results.

“We make sure the methods are grounded in proper theory,” he says. “Once we have the theory down, we run tests and we use ACENET’s resources to put everything into code. We test it on our own local systems and then try them on a bigger system like ACENET,” he says. They then send the code to the chemist, who runs computer simulations using various molecules. This enables the chemist to narrow the options to the most promising candidates before running experiments.

De Baerdemacker says that when he talks to people about high-performance computing and asks them who they think might be HPC’s biggest clients, they’re surprised to learn that chemists are among them. And, he adds, his colleagues in computational chemistry are definitely more frequent users, but even fundamental chemists make good use of services at ACENET.

“We also run a lot of simulations,” he says.

Using a concrete example, he says a lot of diseases are associated with how the proteins in our bodies work and the way they are folded in the cell is also are important for their functionality. Alzheimer’s is one example where a protein starts to curl up and then pierces through a cell membrane,” he says.

“We’re actively looking for a drug that will inhibit that behaviour, but in order to do that, we need to come up with candidates and do a lot of simulations,” he says. “When we’re doing those simulations, we use ACENET.”

But where he has used ACENET to the fullest extent is with machine learning, which he says chemists have been using for 20 years.

“When we’re working on computations, it’s not one variable, it’s millions,” he says. “On machine learning, we’ve discovered that the machine has figured out the kind of molecule we were looking at all by itself. It looked at the data and it found patterns. At this point, ACENET is really crucial.”

New Tools For Designing Safer Chemical Catalysts

Dr. Ghislain Deslongchamps leads a small group of researchers at the University of New Brunswick, adapting computational chemistry tools normally used in drug design for discovering new catalysts with a wide range of applications – and not just any kind of catalyst. A catalyst is a small molecule that accelerates a particular chemical reaction. One type of extremely valuable catalyst is one that promotes a chemical reaction to generate a molecule as a single stereoisomer. Stereoisomers are molecules that are identical except that they mirror each other’s structure. The analogy used by Deslongchamps is a pair of gloves. The two gloves are exactly the same except that the left glove is a mirror image of the right; each glove can only fit its respective hand. The same applies to drug molecules and how they interact with the body, so they typically need to be produced in the correct “handedness” in order to be safe and effective. For example, thalidomide was a drug sold in the late 1950’s to treat morning sickness in pregnant women. It was manufactured as a 50:50 mixture of its two stereoisomers; one had the desired medicinal properties whereas the other was later found to cause severe birth defects. Thus, the ability to manufacture drugs as single stereoisomers has become a critically important issue for the modern pharmaceutical industry. It’s more difficult to make a molecule as a single stereoisomer, however, Deslongchamps is developing computer-based tools and methods for doing just that – developing asymmetric organocatalysts (purely metal-free organic catalysts) that can produce a molecule of “single handedness”. His is the only research group in the world retraining computer-based drug design tools for the purpose of organocatalyst discovery. Because organocatalysts are metal-free, they may produce less toxic and more environmentally sound drugs, important components of green chemistry. While the catalysts he is designing are of great interest to the pharmaceutical industry, Deslongchamps’s computational tools can also be applied to many other areas where molecules with very specific chemical shapes, features and properties are required. The tools he’s creating — one called “reverse-docking” and the other called “virtual screening” – are inspired by those used in computer-assisted drug design. The computations carried out in his lab can be extremely time onerous and require very advanced computing resources. “We are extremely fortunate to be part of ACENET and having access to the Compute Canada resources to do the research that we do,” Deslongchamps says. “A lot of the work we do might otherwise take months of calculating as opposed to days. It’s almost impractical to do this research on a single computer.” Deslongchamps has a long-standing collaborative relationship with Chemical Computing Group Inc. (CCG), a leading drug software company based in Montreal. CCG is one of only a handful of such companies in the world and Dr. Deslongchamps is utilizing and adapting their software for designing and discovering new catalysts.

Designing New Molecules

Jason Masuda has something in common with the alchemists of old. But instead of trying to turn lead into gold, he’s building substances that have never been seen on Earth before. Masuda is a chemistry professor at Saint Mary’s University who is building new molecules from atoms. He says the idea is to use new combinations of atoms to make an actual physical compound with unique chemical properties. “In organic chemistry there are a number of functional groups – specific groups of atoms within molecules that have very characteristic properties, such as aldehydes, ketones, and alcohols – but what we’re doing is making functional groups that have not been made before. Organic chemists understand how the normal functional groups react. We make a new arrangement of atoms and then we study them and how they react with other molecules. That gives us insights into their reactivity. That’s what chemistry is about. Reactions.” The majority of Masuda’s work is done in the lab using glove boxes in an inert environment because many of the molecules he creates are reactive to water and air. “The compounds that we make are not transient things,” he says. “They are actually something you can physically store in a lab.” Once a new molecule has been created, Masuda studies it and catalogs its properties in a library of molecules. “We purify these molecules, we crystallize them and then we analyze them using a variety of techniques. One of the key methods is by using an Xray defractometer on single crystals. That lets us see the places of the atoms in three dimensions.” Masuda also uses ACENET to conduct electronic structure calculations using software called Gaussian09 – a program that places groups of atoms into a structure that is the most stable configuration.“We use that alongside our experimental work to predict the reactivity of these molecules,” he says. Masuda will often use Gaussian to see ahead of time if a molecule will be stable enough to exist in nature. “Gaussian09 is a great tool to save us from wasting time. Because we’re pushing the boundaries of what nature allows, quite often I will generate a molecule and get it to optimize on ACENET and then, if it looks promising, we’ll make it in the lab. There’s a saying that two hours in the library saves you two months in the lab. It’s the same with ACENET. Sometimes a couple of hours with Gaussian09 will save you weeks or months in the lab.” While Masuda creates molecules in the name of pure science, he says giving scientists such as cancer researchers a palette of molecules to work with will ultimately have many practical applications as well. “Basic science leads to new discoveries,” he says. “Often we have no idea what those discoveries will be ahead of time.”