During the summer of 2019, prior to my final year of Mathematics (BSc), I was fortunate enough to be awarded an undergraduate fellowship at Kings College London, in the Department of Physics to work on molecular dynamics simulation. Firstly, I would like to express gratitude to my supervisors, Dr Chris Lorenz and Rob Ziolek and all the members of the group. The fellowship has provided me not only with a pleasant summer, but the opportunity to broaden my understanding of biophysics, while at the same time apply mathematical techniques to real world applications. Having always had a keen interest in chemistry and biology, it has been fascinating to gain a deeper understanding of intermolecular behavior in the analysis of polymer self-assembly used in drug delivery. I could not be more thankful for the time and generosity of the department and hope that my period within the fellowship has added value to the research and that the findings prove valuable to the field.
The objective of the project was to develop an approach in order understand intermolecular interactions of a micelle (molecules which self-arrange into an aggregate when in aqueous solutions). Utilizing the programming language – Python, we developed for more efficient and therefore faster means of analyzing molecular interactions.
As a result of running simulations, I was introduced to a collection of software packages, one of which was GROningen MAchine for Chemical Simulations (GROMACS), a molecular dynamics package used in the simulations of biological and soft matter. Utilizing GROMACS I ran molecular dynamics simulations on Pluronic polymers. Pluronic is a triblock copolymer with the structure PEO-PPO-PEO, where PEO is poly (ethylene oxide) and PPO is poly (propylene oxide). Pluronic polymers are commonly investigated for use as a drug delivery vehicle. For example, Pluronic F127 has been approved for use in humans and is often used in drugs, F127 can commonly be found in medicines such as Ibuprofen and Aspirin. In our simulation system, 35 Pluronic polymers are surrounded by water molecules. Each simulation was run for 30 nanoseconds, prior to visualizing the assembly of molecules using a software called VMD.
Throughout the research I used computer simulations and my background in Mathematics to investigate the self-assembly of Pluronics. I made use of MDAnalysis python libraries to compute and analyze the trajectory of polymers.
Working with Rob, we used the Radial Distribution Function in order to discover the nearest neighbor distances between polymers, and then we used these distances to identify polymers which were aggregating together. Our simulations used periodic boundary conditions (PBCs), a set of boundary conditions which are often chosen for approximating a large (infinite) system by using a unit cell, also known as a box, which I found both surprising and intriguing. In applying these methods to this problem, I have broadened my understanding of certain mathematical topics covered throughout my undergraduate studies to a new level of real-world applications.
One of the greatest challenges I faced during this fellowship is learning the Linux operating system. Having had little exposure in using Linux, I found it abnormal to ‘communicate’ with the computer directly. Given there is no GUI (Graphical User Interface), it required typing commands into the terminal, and from here locating and executing files and software such as Python and GROMACS. At first, having to memorize an array of commands was challenging, despite this, with time I found familiarity and understood the importance of using Linux for the project and now have a preference for using Linux, as a result of its speed, stability and flexibility.
As well as Linux, I was able to build upon certain skills, including (but not limited to), Python and presentations. Given my degree, I have had a limited occasion to both create and give presentations, as well as the opportunity to learn how to articulate mathematical theories to an audience, who may not be from a mathematical background. Towards the end of the study, I had the opportunity to present my findings to a group of PhD students from a range of backgrounds, e.g. Chemistry, Biology and Computer Science and successfully answer all queries from the group relating to the methodology, such as the formulae used. I have also been able to carry out research within a team and independently, helping to build on my research technique.
A good proportion of my time was spent coding, if time was not limited, I would do further bug fixing to improve the efficiency of the program and test the code on multiple systems including micelles. I would also like to apply Machine Learning and Monte Carlo simulations in comparison to the molecular dynamic simulation in order to obtain further understanding of fundamental ideas regarding simulation.
I also enjoyed the social activities of the group, on Thursday lunches each person would discuss what they are researching, as well as their duties and opinion of the work. This was highly engaging, and I believe was a reason why the group bonded so well. I was also fortunate enough to have joined the department’s afternoon tea, where I met and conversed with researchers from different fields of Physics, such as Material science, Photonics and Astronomy, an excellent experience. It was also interesting to find others who had a bachelor’s degree in mathematics, like myself, and have now moved on to different subjects, applying the mathematical theories they have learnt.
Following this fellowship, I will be continuing my studies in applied mathematics and hopefully a PhD in a similar field using mathematics to analyze a given subject. This experience further provided me with an opportunity to meet and discuss areas of Biophysics and broadened my knowledge of physics from nanoparticles to astronomy. I was able to see the real-world application of mathematics in science and how it can be utilized to benefit society. I have greatly enjoyed working in such an area and with PhD research students and academic researchers. It has been enjoyable, thought provoking and insightful and I hope KURF can provide similar opportunities to others in my future.