PhD student Reabetswe Zwane talks about her computational chemistry research and what it could mean for drug substances down the line.
Reabetswe Zwane is a third-year PhD student with SSPC, the Science Foundation Ireland research centre for pharmaceuticals, based at Dublin City University. Her PhD is in computational chemistry, which sees her employ high-level computation techniques to understand various chemical and physical properties of pharmaceutical drug substances.
Here, Zwane shares why she loves working in this field and how her work days typically play out.
‘The picture of the isolated mad scientist is not productive nor true’
– REABETSWE ZWANE
What experiences led you to the role you have now?
In my fourth year at the University of Cape Town, we had to do a six-week research project and I chose to do one in computational chemistry.
Although I was met with the initial challenge of using computers to do science, I found computational chemistry to satiate my love for chemistry, maths and physics all at once, which encouraged me to continue with my fourth-year supervisor for a master’s project and now a PhD.
Can you tell us about the research you’re currently working on?
In my research, I am focused on understanding the mechanical behaviour of pharmaceutical products. Most drugs on the market today are dosed in solid form, as tablets for example, as this is cheap and easy to administer to patients. Surprisingly, it is not always guaranteed that a drug substance can be turned into a tablet or compressed into tablet form.
In my research, I use computational methods and techniques to understand the properties that make drug substances ‘tablet-able’ and easily soluble in the body. The ultimate hope is that we will get to a place where we are able to determine such properties even before a drug is made in the lab.
What first stirred your interest in computational chemistry?
My interests have generally been towards understanding and developing materials we see around us. The first time I encountered something like materials development was about 12 years ago on a National Geographic programme.
In the programme, they showed how nanotechnology was able to be used to make a pair of waterproof pants which, on a molecular level, was coated with millions of very tiny silicone thread-like structures that made water just bounce off the pants.
This was and still is very cool to me, to be able to investigate materials at the smallest of scales and be able to gather extensive knowledge about the behaviour of the materials at a scale the eye can see.
If there is such a thing, can you describe a typical day for you?
My days look a bit different since I have been working from home. My mornings involve writing my to-do list for the day and then catching up on emails before I get into an online daily meeting with my research group members. In this meeting, we outline what tasks we managed to complete since the last time we met, our planned tasks for the day ahead and what is currently blocking us.
After that, I usually just check on my calculations, which were submitted to the Irish supercomputer called Kay. I then take my lunch, which means leaving my desk and hopefully catching the sun on a walk.
For the rest of my day, I usually just read papers or write computer codes and scripts that allow me to submit many calculations at once to the supercomputer, or extract and visualise data from big files generated by the supercomputer.
Depending on the time of the year, sometimes my days can involve attending a conference or symposium or demonstrating in the lab for undergraduates. I try to keep the evenings free.
What skills and tools do you use on a daily basis?
As a computational scientist, the main tool I use is the computer and computer software. For scripting computer code to help me with day-to-day data manipulation, I use Python and Bash, which are well-known scripting languages.
In terms of skills, I use organisational skills and time management to prioritise urgent and important tasks, and to sort, store and back up large amounts of data from a supercomputer. Another important skill is troubleshooting, which is essential to debug any errors from a computer software. With that, programming language literacy (being able to read code) is another skill one picks up on the way.
The soft skills I use include communication, which is essential for presenting my research orally and in written form, as well as interacting with my lab mates, supervisors and collaborators.
What applications do you foresee for your research?
As mentioned before, the ultimate goal is to be able to predict properties of drugs even before they are synthesised in the lab. Crystal structure prediction is a computational technique that tries to predict the crystal structure of a drug from just its chemical diagram or drawing.
Crystal structure prediction is one area wherein we can apply the computer protocols we have come up with to determine properties of postulated drugs from our crystal structure prediction calculations. However, crystal structure prediction is a growing field with its own limitations.
Are there any common misconceptions about computational chemistry research?
The one common misconception is that computational chemistry is a niche field and only accessible to people with coding skills, but computer software and computational models are to computational chemists what lab equipment is to a wet-lab chemist.
Arguably, you do not necessarily need to know the internal working electronics of a pH meter to measure the pH and interpret the number from the meter. You also need to know the amount of impurities you are willing to accept in your experiments. That is true for computer software too.
The other side of the coin is that computational chemistry is commonly accused of being a superficial field since computational chemists can be guilty of some kind of ‘black-box ticking’ when using computer software, similar to accepting the terms and conditions without reading them. Like with experiments, a computational chemist is expected to know the limitations of their models and also what their data tells them or what it does not tell them.
In essence, to do good computational chemistry, a computational chemist is expected to understand their ‘boxes’.
When you first started work as a researcher, what were you most surprised to learn was important in the role?
That the picture of the isolated mad scientist is not productive nor true. You need people! You need people as sounding boards to evaluate and challenge your ideas, you need people to collaborate on projects with and you need people for relational purposes.
What do you enjoy most about your career in research?
Travelling to different places for conferences and symposiums and meeting people with different accents and cultures is one perk of research. You get to interact with some of the great minds of in our communities.
Another thing I enjoy is that I get to spend my time understanding some of the coolest and complex things in the world, and also contribute to solving some of the challenges facing our communities today.