Virginia Apostolopoulou is ESR10, works in the Department of Physics at the University of Surrey, UK. Her PhD subject is “Modelling crystal formation in complex systems”.
Please tell us about yourself:
I graduated from University of Crete, Greece, in 2014 with a bachelor degree in Applied Mathematics. I continued my studies at the University of Crete, and in 2017 I got my master degree in Applied and Computational Mathematics.
I am passionate about many areas of applied mathematics, but I was always more interested in the close relationship between mathematics and practical problems related to physics and biology. During my studies, I tried to stay relevant, always trying to learn more about physics, through the university or in my spare time. Mathematics is a valuable tool when it comes to study and understanding physics, but I am looking forward to learning how to approach these problems from a physical perspective.
Why are you interested in science?
I do not think that the reason I am interested in science is any different than any other person that works as a scientist (and actually enjoys it). Science has always been a safe space for people who enjoy discoveries, challenges and finding answers. Whether it is mathematics, physics, biology etc, there is definitely a thrill in looking into subjects that nobody else has looked into before.
Please tell us about your PhD project:
Everyone’s project in this network revolves around the crystallisation of membrane proteins. My individual project has to do with modelling the process of crystallisation of membrane proteins.
Computer simulations are a way to link theory and experiment. Theory is often celebrated in the physical sciences, but it is questioned by the life sciences, mostly because, in biology we usually have very complicated systems and theory tends to be a bit obscure. However, thanks to the emergence of big data, theory has become a forefront in life sciences. Computational models can complement experimental data to provide a better understanding of the physical and biological processes. A new computational model inspires new experiments, provides new insights and it can suggest what variable are most important to investigate in an experiment.
In order to extend our understanding of the crystallisation mechanism further, l focus on advancing and evolving experimental and computational methods. As part of the project, I will focus on understanding how the phase diagram of membrane proteins controls crystallisation, by developing theoretical models to relate crystallisation behaviour to position in the phase diagram. The parameter space of membrane protein is high dimensional and nucleation is probabilistic, so an objective will be to study techniques for optimisation of random processes in high-dimensional parameter spaces.
The outcome of my project is to create models to better understand the process of membrane protein crystallisation, and to make experimentally testable predictions of how best to rapidly produce highly ordered crystal of membrane proteins. This will contribute to RAMP’s aim of developing rational strategies for membrane-protein crystallisation.
What do you or did you enjoy most until now in your position within RAMP network? Why ?
I really enjoying travelling, and through my position within the RAMP network I got to travel to many new places. The fact that we often get to stay for an extended period of time in each place, thanks to the secondments, is a big advantage for me, because this way you get to know the people and the culture as well. I was pleasantly surprised when I met the fellow ESRs. I think we got a great connection and understanding from the very beginning, and I could not ask for a better group of people to work with.