Back in June this year, I went to Amsterdam to give a talk at “Antibody Engineering & Therapeutics Europe 2024”. I had a great time at the conference, and it presented many opportunities to gain some insights into research that is directly relevant to me, as well as research to broaden my horizons a little beyond the CDR loops. While I would love to go through all the fantastic talks, I’m opting to give some takeaways on only a subset:
Continue readingAuthor Archives: Bora Guloglu
Cosmology via Structural Biology and Half-Lives of Teaspoons: Bizarre Papers from Around the Internet
I don’t know if anyone out there shares this peculiar hobby of mine (God, I hope not!), but I often find myself scouring the depths of the internet for some truly bizarre academic papers. Though there is an endless supply of such content to keep one entertained (read: distract yourself during those afternoons you planned to be productive but ended up succumbing to the lunch food coma), I’ve managed to compile a short list of the most fascinating ones for your enjoyment!
- The case of the disappearing teaspoons: longitudinal cohort study of the displacement of teaspoons in an Australian research institute (Lim et al, 2005, BMJ, doi: https://doi.org/10.1136/bmj.331.7531.1498)
This fantastic and robust study examines the enigmatic phenomenon of disappearing teaspoons in a shared kitchen—an issue of acute importance to all of us who rely on these tiny utensils. The authors reveal the shocking truth about teaspoons’ shockingly short half-life in research institutes. The question remains: does this phenomenon extend to other cutlery as well?
Continue readingThree months in industry and returning to my PhD
Being in my third year of my DPhil, I decided that I should try to see what the world of industry looks like. Thankfully, I was lucky enough to be able to complete an industrial internship at Exscientia here in Oxford where I spent most of my time on scientific software engineering. I expected this to not be too different from what my work looks like here at OPIG, but quickly came to realise that this is not the case. What followed were three months of building a software package, getting to know all the new people around me, and getting used to all the new tools and infrastructure. Below are a few things that I am very happy to take back with me.
Read more: Three months in industry and returning to my PhDA PhD can often be very solitary work. You are the expert in your project, and also have the highest stake in your project. At times, the freedom of what to explore next this affords is fantastic, but can make things difficult when problems arise. In industry, projects are a lot more collaborative. Your work direction will be aligned heavily with company needs, and depending on company size there might be specialised teams to support you in specific aspects of the project.
Emphasis placed on code quality is also a stark difference. Internal software written for company use has to be readable and well-documented. The codebase must also be standardised to maintain consistency. This will make life for newcomers easy and ensures that if the author of some software leaves the company the next person can easily take on the task of maintaining their code. Here, academia is catching up. Scientific software engineering is becoming more focused on maintainability (one of the core values of the SABS programme), but sadly Github is still full of legacy code that was written in ways that make maintaining the code difficult after the author stops being involved with it.
Lastly, on a more personal note, it was also fantastic to be surrounded by people in a team who work with the same techniques as me. In my PhD, I am one of two people at OPIG regularly using molecular dynamics simulations but I also spend a lot of my time working in the Biochemistry Department with the Higgins Group which is an experimental structural biology group. This being the case, my internship has been a fantastic way of picking up some additional techniques from people who are already familiar with them. I would highly recommend giving yourself the opportunity to do this if possible, either via something like an industrial internship, or a research visit to a collaborating academic group.
The past three months have been invaluable. They have given me the opportunity to see what industry is like and given me experience with new skills that I can take back to my PhD. Best of all, I got to meet a fantastic team who were always ready to take time out of their days to help and who made the time I spent at Exscientia as fun as it was!
OpenMM Setup: Start Simulating Proteins in 5 Minutes
Molecular dynamics (MD) simulations are a good way to explore the dynamical behaviour of a protein you might be interested in. One common problem is that they often have a relatively steep learning curve when using most MD engines.
What if you just want to run a simple, one-off simulation with no fancy enhanced sampling methods? OpenMM Setup is a useful tool for exactly this. It is built on the open-source OpenMM engine and provides an easy to install (via conda) GUI that can have you running a simulation in less than 5 minutes. Of course, running a simulation requires careful setting of parameters and being familiar with best practices and while this is beyond the scope of this post, there are many guides out there that can easily be found. Now on to the good stuff: using OpenMM Setup!
When you first run OpenMM Setup, you’ll be greeted by a browser window asking you to choose a structure to use. This can be a crystal structure or a model. Remember, sometimes these will have problems that need fixing like missing density or charged, non-physiological termini that would lead to artefacts, so visual inspection of the input is key! You can then choose the force field and water model you want to use, and tell OpenMM to do some cleaning up of the structure. Here I am running the simulation on hen egg-white lysozyme:
Non-linear Dependence? Mutual Information to the Rescue!
We are all familiar with the idea of a correlation. In the broadest sense of the word, a correlation can refer to any kind of dependence between two variables. There are three widely used tests for correlation:
- Spearman’s r: Used to measure a linear relationship between two variables. Requires linear dependence and each marginal distribution to be normal.
- Pearson’s ρ: Used to measure rank correlations. Requires the dependence structure to be described by a monotonic relationship
- Kendall’s 𝛕: Used to measure ordinal association between variables.
While these three measures give us plenty of options to work with, they do not work in all cases. Take for example the following variables, Y1 and Y2. These might be two variables that vary in a concerted manner.
Perhaps we suspect that a state change in Y1 leads to a state change in Y2 or vice versa and we want to measure the association between these variables. Using the three measures of correlation, we get the following results:
Continue readingOPIGlets go flying
Just like any other bioinformatician, I spend a lot of time every day in front of my computer and I am under no false pretence that my posture is anywhere near ideal. To counteract this, I have taken up the flying trapeze for some exercise and since classes run at ten participants, we decided that some other OPIGlets should try their hands at the circus arts on a fine summer evening!
Antibody Binding is Mediated by a Compact Vocabulary of Paratope-Epitope Interactions
While my own research focuses mainly on what happens in an antibody before it binds its antigen, I recently came across a paper by Akbar et al [1] that examines antibody-antigen interactions using an elegant approach to identify a set of structural motifs that antibodies use to interact with their epitopes. Since I am interested in emergent properties that arise when a sequence is mapped onto an antibody structure, this paper was very exciting. I will also shamelessly admit that I’m a sucker for a pretty figure and this paper has many! Regardless, on to the findings!
It’s been here all along: Analysis of the antibody DE loop
In my work, I mainly look at antigen-bound antibodies and this means a lot of analysing interfaces. Specifically, I spend a lot of my time examining the contributions of complementarity-determining regions (CDRs) to antigen binding, but what about antibodies where the framework (FW) region also contributes to binding? Such structures do exist, and these interactions are rarely trivial. As such, a recent preprint I came across where the authors examined the DE loops of antibodies was a great motivator to broaden my horizons!
Continue readingLe Tour de Farce v8.0
Last Tuesday marked two exciting milestones for me in OPIG! Not only had I been looking forward to group socials since the beginning of lockdown, but I’d never met anyone other than Charlotte in person since starting in the group in April. As such, the annual cycling pub trip was an apt introduction to several OPIG members (who are now exempt from the game I play by myself during weekly Zoom group meetings: “Guess how tall this person is in real life!”) and a chance to interact with people other than my housemates!
Continue readingJournal Club: the Dynamics of Affinity Maturation
Last week at our group meeting I presented on a paper titled “T-cell Receptor Variable beta Domains Rigidify During Affinity Maturation” by Monica L. Fernández-Quintero, Clarissa A. Seidler and Klaus R. Liedl. The authors use metadynamics simulations of the same T-cell Receptor (TCR) at different stages of affinity maturation to study the conformational landscape of the complementarity-determining regions (CDRs), and how this might relate to an increase in affinity. Not only do they conclude that affinity maturation leads to rigidification of CDRs in solution, but they also present some evidence for the conformational selection model of biomolecular binding events in TCR-antigen interactions.
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