C is for Cysteines (plus a fun quiz)

At group meeting a few weeks ago I presented this paper, “Landscape of Non-canonical Cysteines in Human VH Repertoire Revealed by Immunogenetic Analysis“, from Prabakaran and Chowdhury. The paper is an investigation of the frequency, location and patterns of cysteines contained in human antibody sequences. Cysteines are important amino acids found in proteins, including antibodies, which can form disulphide bonds with other cysteines due to the presence of their reactive sulfhydryl group in the side chain.

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Le 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! 

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Understanding Conformational Entropy in Small Molecules

While entropy is a major driving force in many chemical changes and is a key component of the free energy of a molecule, it can be challenging to calculate with standard quantum thermochemical methods. With proper consideration in flexible molecules, we can break down the total entropy into different components, including vibrational, translational, rotational and conformational entropy. The calculation of conformational entropy is the most time-consuming as we have to sample all thermally-accessible conformers. Here, we attempt to understand the components that contribute to the conformational entropy of a molecule, and develop a physically-motivated statistical model to rapidly predict the conformational entropies of small molecules.

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Learning from Biased Datasets

Both the beauty and the downfall of learning-based methods is that the data used for training will largely determine the quality of any model or system.

While there have been numerous algorithmic advances in recent years, the most successful applications of machine learning have been in areas where either (i) you can generate your own data in a fully understood environment (e.g. AlphaGo/AlphaZero), or (ii) data is so abundant that you’re essentially training on “everything” (e.g. GPT2/3, CNNs trained on ImageNet).

This covers only a narrow range of applications, with most data not falling into one of these two categories. Unfortunately, when this is true (and even sometimes when you are in one of those rare cases) your data is almost certainly biased – you just may or may not know it.

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Prerecording Conference Talks and Posters using OBS Studio

Seemingly every conference due to take place this year has either been cancelled or will be run virtually due to the COVID-19 pandemic. Many organisers have decided that running entirely live virtual programmes causes more trouble than it’s worth (e.g. due to unforseeable IT and internet issues disrupting the schedule), and so are asking their presenters to prerecord their talks, which are then broadcast “live” on the day.

I recently “presented” two virtual prerecorded talks at the ISMB conference using Open Broadcast Software Studio (OBS Studio), a free open-source software package most commonly used by live-streamers on Twitch and Youtube. It is super simple to use and achieves a professional output, with video overlaying a presentation slide deck/poster PDF. This blog is a “how-to” on getting started with OBS for conference talks/poster presentations.

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Pigs in the Parks: OPIG Social 28JUL2020

Tuesday afternoon normally heralds Group Meeting, the precious hour of the week where we gather on Zoom to hear about recently published papers, dissect each other’s research and, most importantly, bicker about appropriate usage of the servers. Knowing that Fergus B was on holiday this week and that a Group Meeting devoid of SLURM-inspired ranting would have felt strangely empty, it was instead decided that now was the time for the first in-person group social since the lockdown began in March.

Struggling to adapt to not being able to turn off Mic and Webcam – how on earth did we manage like this all the time before?!
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Climate Change @ ISMB

Another special session I was listening to at ISMB 2020 was the Green stream. Several talks dealt with climate change and its relation to bioinformatics and computational biology. Two of them I found particularly interesting, one calculating the carbon footprint of ISMB itself and the other calculating the footprint of specific bioinformatics tools.

I believe most people have realised how important the issue of human-made climate change is and I assume that everyone has heard about some aspects of our life that are causing particularly many emissions compared to certain alternatives. For example, train rides vs. short-haul flights, eating the food’s food (veggies) vs. mass production of meat or renewable energies vs. coal plants, just to name some that are rather easy to change. Admittedly, I have also underestimated the urgency of the issue and I found this plot quite convincing:

(Screenshot from Alex Bateman’s talk)

What can we as computational researchers do about it?

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Citizen Science in Video Games

What I really liked about visiting ISMB last year was their diversity of talks and subgroup meetings in all areas related to biology and computers. Last year I joined two talks about improving bioinformatics education which were really interesting because I hadn’t thought about that before. This year I joined a special session on citizen science.

Citizen science is public participation in scientific research and can be done by almost everyone. I had heard about Foldit or Rosetta@Home but (unfortunately) never participated. Those two projects deal with protein folding (how does a protein reach its final functional 3D structure?) which is an important scientific problem but is computationally very expensive to study. While one of the projects is a screensaver which uses free resources of personal computers, the other is a game where players can get highscores for folding protein fragments manually. Helping science in a playful way is cool by itself but the project that was presented in one of the talks brought this to the next level. A citizen science minigame was integrated into an action game for PCs and consoles.

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Drug Promiscuity vs Selectivity

In drug discovery, compound promiscuity and selectivity refers to the ability of drug compounds to bind to several different- (promiscuous) or only one main target (selective). An important distinction here is that promiscuity is defined as specific interactions with multiple biological targets (polypharmacology) rather than a number of non-specific targets. At first glance, you might expect drugs to be designed to be as selective as possible, only hitting one biological target necessary to treat the disease and therefore reduce the chance of any side effects. This paradigm of single-target specificity has been challenged over the past two decades. Even between scientists in the drug discovery field, compound promiscuity is still a controversial topic. The field has increasingly paid attention to the topic of polypharmacology and studies have shown many pharmaceutically relevant compounds, including approved drugs to derive their biological activity from polypharmacology [1-3].

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