Category Archives: Social

Le Tour de Farce v6.0

Tuesday the 12th of June brought sun, cycling and beer to the land of OPIG. It was once again time for the annual Tour de Farce.

Le tour, now in its highly refined 6.0 version, covered a route which took us from the statistics department at Oxford (home to many OPIGlets) to our first port of call, The Head of the River pub. We then followed the river Isis (or Thames if you prefer) from the head of the river towards Osney mead.

Passing though Osney we soon arrived at our second waypoint. The Punter. One of the OPIGlets lived locally and so we were met by their trusty companion, who was better behaved than many of the others on Le Tour.

Departing the punter on two wheels (or in one case, on one) we followed the river upstream to The Perch.

Our arrival at The Perch was slightly hampered by a certain OPIGlet taking out anything in her path in her excitement. Mr Sulu.. Ramming speed.

Those that survived soon left the perch, as we were once again headed upstream, this time to The Trout.

Having braved about half the journey it was now time for another restorative beverage and to take on supplies. Sustenance was provided by Jacob’s Inn. Jacob’s Inn has the advantage of goats, chickens and pigs in the back garden. Having spent most of the afternoon in each other’s company, the company of pigs was preferable for some.

As we finished dinner, the sun was beginning to set and so we abandoned the original plan of finishing off at The Fishes. Instead we returned southwards where we closed off the evening with a drink at The Royal Oak, mere yards from where we started the day.

The route of the 2018 v6.0 Tour de Farce.

OPIGTREAT

On the 19^th of March OPIG set off on our group retreat – henceforth referred to as the OPIGTREAT.

We kicked off a little late as apparently Saulo and check in times are not a good combination (though he is an expert at reversing on an icy road).

Jin and Flo gave the first talk on web programming specifically Flask and D3. If I understood correctly flask is a web development framework for python that runs everything on the server side. Whereas D3 is data/driven/document, which appears to be a way of making very pretty things.

Garrett then gave us an impressive overview on the area of docking, thinking about whether docking had improved in the last 10 years. He discussed how docking can be used to both predict the binding mode (the orientation and conformation) as well as the binding affinity. The state of the art appears to be if we are docking a small molecule into approximately the correct binding site a native like pose can be identified but binding affinity prediction in all cases remains challenging.

Mark then attempted the impossible, he tried to give a talk explaining how to give a good talk. In this case in the context of public engagement and taking our work out to schools. I am now versed in the 4 Ms Manageable, Measurable, Made first and Most Important. I am also weirdly aware that my head shouldn’t move when I am teaching.

Ellliot then took us through how we should judge a PDB structure, a really useful skill for everyone in the group. He described measures such as resolution, B factors Rfree, Clash score, Ramachandran outliers, sidechain outliers and RSRZ outliers. Interesting facts that I collected the average resolution of an X-ray structure in the PDB is ~2A and the average Rfree is 0.25. I also learnt of the existence of PDBredo a service that re-refines datasets in the PDB.

Saulo and the Fergi were up next and they treated us all to a short talk and then a Jupyter notebook practical on machine learning. They discussed supervised, unsupervised and reinforcement learning. Giving examples of each and how and when they should/could be used. Claire and I then learnt a great deal about Jupyter notebooks, the most important thing being to press shift enter. Useful facts “out of the bag” is a method for measuring the error of random forests, score using all data points apart from those used to make that tree.

The evening finished with a film about the evil iniquities of smoking (very high brow stuff!?!).

The second day began with Bernhard (a visitor from the far of land of Barcelona these days) talking to us about his latest research project. As this is his story – no details in the blog.

Claire then gave an update of the talk she gave at the last OPIGTREAT – how to make “stuff” pretty. Obviously a popular topic as we all wish to display our data and findings in a way that is easily interpretable as well as visually appealing. Claire took us through some of the tools to use like ggplot and Pymol – showed us where to find the lists of useful commands and then showed us the types of images you could make if you really put some thought into it.

Anne was up next, she discussed the challenges and opportunities of integrating heterogeneous data sources and she came up with a lot of data sources to think about, running from protein structures, protein interactions, small molecule structures, drug safety, drug targets, functional annotation and pathways. One thing to remember probably don’t tell your boss when she should or shouldn’t be taking notes……

It was then the turn of team networks Javi, James and Lyuba who walked us through the basics of networks and expanded on their uses across multiple data types in biology. They mentioned areas from simple motifs to protein structure, MD simulations, ontologies, disease prediction, drug target identification…. We then had a practical to check we had understood the power of networks! The networks under consideration were dolphins, Myoglobin structure, Facebook data and the mystery voter network (where we discovered that Fergus the first in no way tried to rig the vote for what film to watch).

That afternoon I visited the bird sanctuary just down the road, others went to a gin distillery or on a walk. Top quote of the afternoon was from James “I want the birds to eat from my pants”. I believe he is from one of those countries that has the misguided belief that pants means trousers. Actually I could have a different top quote from Alex about somebody being a cheap ride in his dreams but I think I should pass over that one.

That evening we were treated to a fragment based drug discovery extravaganza headed up Hannah, Susan and Joe. They took us through the use of fragments for drug discovery and then we attempted a practical. I seem to remember that Claire and I once again excelled at shift enter on the Jupyter notebook.

That evening we had a pub quiz, which apparently ended in a draw between all the teams playing. I feel that Claire and Flo as quizmasters might have made a minor miscalculation. I was happy though as I ended up with the minions bowl and cup. I also managed to persuade several grown men to jump and smash chocolate eggs on their heads on the ceiling.

Next morning Alex and Matt were up first. In their talk they demonstrated not only their knowledge on the area of the future immunotherapy repertoire but also their ability to finish each other’s sentences. They gave a really excellent overview of current immunotherapies and where the field is moving and what might be the future. Facts to store in the head, first ever approved AB therapeutic Muromonab (1986). Currently most successful Humira (Adalimumab) from Abbvie worth 18.4b dollars in 2017, this is a fully human AB for autoimmune diseases and binds to the mediator of inflammation (TNF-alpha).

Next up Catherine and Lucian who discussed distributed computing in PySpark, they started by explaining why distributed computing is going to become so important. Basic info by 2025, 100 million to 2 billion human genomes will have been sequenced that is 2 – 40 exabytes of data. They discussed distributed computing vs centralised and Pyspark compared to Hadoop. There was a practical but Mark had to solo perform for the audience leading to one of the top photos of the whole OPIGTREAT.

As a punishment for being in charge I gave the final talk where I discussed future research direction and how you decide what those might be.

So with thanks to all of the group that concludes the OPIGTREAT report.

ISMB wrap-up (it was coming, we insist…!)

So ISMB 2015 seems a bit far away from now (just under 2 months!), but Dublin was an adventure, filled with lots of Guinness, Guinness, and … Guinness. Oh and of course, science (credits to Eleanor for the science of Guinness video)! We definitely had lots of that, and you can see some of our pictures from the week too (credits to Sam; https://goo.gl/photos/2qm9CPbfHtoC3VfH9)

Here are some key pieces of work that got to each of us here at OPIG.

Claire:

Jianlin Cheng, from the University of Missouri, presented his research into model quality assessment methods – ways of choosing the model that is closest to the native structure from a set of decoys. Their method (MULTICOM) is a consensus method, which calcualtes an average rank from 14 different quality assessment methods. By combining this average rank with clustering and model combination to select five top models for a target, their method produces good results – in CASP11, the group were ranked third when considering the top-ranked models and second when considering the top five.

Alistair:

Accounting for the cell cycle in single cell RNA-seq

The current ubiquitous of RNA-seq throughout academia speaks volumes to the strength of the methodology. It provides a transcript-wide measure of a cell’s expression at the point of cell lysis; from which one can investigate gene fusion, SNPs and changes in expression, to name only a few possibilities. Traditionally, these measurement are made using a cell culture and as such the expression levels, and derived results, are based on averages taken over a number of cells. Recent advances have allowed the resolution to increase to the point where measurements can now instead be made on single isolated cells. With this increase in capability, it should now be possible to measure and identify subpopulations within a given culture. However, the inherent variability of expression, such as that caused by the cell cycle, often overshadows any change that could be attributed to these subpopulations. If one could characterise this variability, then this could be removed from the data and perhaps these subpopulations would then be elucidated.

Oliver Stegle gave a great presentation on doing exactly this for the cell cycle. They modeled the different phases as a set of latent variables such that they are inferred directly from the data (rather than merely observed). Via this model, they estimated that upwards of 30% of the inherent variability could be accounted for, and hence subtracted from the data. Applying such a technique to culture of T cells, they were able to identify the the different stages of differentiation of naive T cells into T helper 2 cells. Crucially, these would of been obscured had the cell cycle not been identified. Given this success with just accounting for the cell cycle, Stegle suggested that their technique can be expanded upon to elucidate other sources of gene expression heterogeneity while making it easier to identify these cellular subpopulations.

Jaro:

Dr. Julia Shifman from Hebrew University of Jerusalem studies protein-protein interactions. In her 3DSiG presentation she focused on the presence of “cold-spots” in protein sequence where in sillico mutations to several different amino acids improve the binding affinity. Such cold-spots are often observed at the periphery of the complex, where no interaction is observed.

Paper link

Malte:

Alex Cornish from Imperial College London presented his work on the structural difference between cell-type specific interaction networks. To generate these, he weighted protein-protein interaction network edges by cell-type specific gene expression data from the FANTOM5 project. Using these cell-type specific networks, he finds that it is possible to associate specific networks with specific diseases based on the distances between disease-associated genes in the networks. Furthermore, these disease – cell type associations can be used to assess the similarity between diseases.

Jin:

Barry Grant presented an overview of the research activity in his group — namely nucleotide switch proteins (e.g. GTPases, such as Ras and Kinesin). In the case of Kinesin, the group used simple statistical methods such as principal components analysis to draw inferences between conformation and functional states. The group then used correlated motions to construct a community network that describes how certain groups of residues behave in certain conformational states.

Sam:

Discovery of CREBBP Bromodomain Inhibitors by High-Throughput Docking and Hit Optimization Guided by Molecular Dynamics

Min Xu, Andrea Unzue, Jing Dong, Dimitrios Spiliotopoulos, Cristina Nevado, and Amedeo Caflisch Paper link

In this paper MD simulations were used to confirm the binding modes found by in silico docking and to guide the chemical synthesis of hit optimisation. In one example three binding modes were observed during MD, which helped to identify favourable electrostatic interactions that improved selectivity. For another compound a favourable polar interaction in the binding site was observed during MD, which helped to increase its potency from micro- to nanomolar. Thus, given a robust in-silico screening and docking approach, it seems that MD simulations can be a useful addition to confirm binding modes and inspire derivatives that might have been overseen in static structures.

Eleanor:

Bumps and traffic lights along the translation of secretory proteins
Shelley Mahlab, Michal LinialIn her talk, Michal described how a theoretical measure of translation speed, tAI, shows the differences between the translation speeds of proteins targeted to different locations. Proteins with a signal peptide (either secreted or transmembrane) have significantly slower codons than proteins without, over approximately the first 30 codons, perhaps allowing more time for binding to the signal recognition particle. Transmembrane proteins had a lower predicted speed overall, which may be important for their insertion and correct folding.