Category Archives: Commentary

AlphaFold 2 is here: what’s behind the structure prediction miracle

Nature has now released that AlphaFold 2 paper, after eight long months of waiting. The main text reports more or less what we have known for nearly a year, with some added tidbits, although it is accompanied by a painstaking description of the architecture in the supplementary information. Perhaps more importantly, the authors have released the entirety of the code, including all details to run the pipeline, on Github. And there is no small print this time: you can run inference on any protein (I’ve checked!).

Have you not heard the news? Let me refresh your memory. In November 2020, a team of AI scientists from Google DeepMind  indisputably won the 14th Critical Assessment of Structural Prediction competition, a biennial blind test where computational biologists try to predict the structure of several proteins whose structure has been determined experimentally but not publicly released. Their results were so astounding, and the problem so central to biology, that it took the entire world by surprise and left an entire discipline, computational biology, wondering what had just happened.

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One of my other hats – Covid-19 Response Director for UK research and innovation

The group asked me if I would tell them a little bit about one of my other hats at our regular Tuesday meeting, and this blog is about that.

In October 2019 I was seconded part-time to UKRI as the Deputy Executive Chair of the Engineering and Physical Sciences Research council (EPSRC). What is UKRI (UK research and Innovation)? It’s a non-departmental public body that funds research and innovation. It is made up of the seven disciplinary research councils (acronyms to please Tom – AHRC, BBSRC, EPSRC, ESRC, NERC, STFC and MRC), Research England, and the UK’s innovation agency, Innovate UK.

As Deputy Executive Chair of EPSRC I was helping with UKRI strategy, learning how a spending review round works, visiting universities to talk about how they could work better with UKRI – pretty much everything I was expecting to be doing. But like everyone, my world changed in early 2020.

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How fast can a protein fold?

A protein’s folding time is the time required for it to reach its unique folded state starting from its unfolded ensemble. Globular, cytosolic proteins can only attain their intended biological function once they have folded. This means that protein folding times, which typically exceed the timescales of enzymatic reactions that proteins carry out by several orders of magnitude, are critical to determining when proteins become functional. Many scientists have worked tirelessly over the years to measure protein folding times, determine their theoretical bounds, and understand how they fit into biology. Here, I focus on one of the more interesting questions to fall out of this field over the years: how fast can a protein fold? Note that this is a very different question than asking “how fast do proteins fold?”

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Safety and sexism: the heroic stubbornness of Frances Oldham Kelsey

With covid-19 vaccine rollouts well underway the world over, the subject of clinical trials has been a focal point of discussion lately. Of course clinical trials are applicable to every drug, not just vaccines, and the class of molecules on which my own work focuses includes perhaps one of the most famous case studies of why clinical trials are necessary: thalidomide.

The teratogenic effects in unborn infants of this seemingly innocuous small molecule are well documented and infamous. But at the time of its initial use a treatment for morning sickness in the mid twentieth century, little was known about its mechanism of action. Only within the last 20 years has the molecular glue-type nature of thalidomide and its analogues (collectively known as immunomodulatory imide drugs, or IMIDs) become apparent. Armed with this knowledge, we know not only understand how thalidomide works in useful situations (such as curing cancer), but also how it exhibits its less desirable effects (recruiting SALL4 to the E3 ligase cereblon, leading to SALL4’s degradation and subsequent embryogenesis havoc).

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Do antibodies care about sex?

In a recent OPIG antibody meeting, the topic of immune system differences between men and women came up. I thought this was cool and something I hadn’t read about, so what a brilliant topic for a blog most. This post is a high-level overview – I’ve listed the papers I’ve used at the bottom of this post so please consult them for more details!

Differences between males and females can lead to pretty big disparities in disease prevalence and outcomes. For example, non-reproductive cancers occur predominantly in males, whilst the majority of autoimmune disease occurs in females. Many factors may be impacting this, including environmental, genetic and hormonal influences, and much more research is required to fully understand these processes. Here I focus on sex-based biology, rather than gender, though both can influence the immune response.

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6 things I’ve learnt in my first year as a PhD student

Despite spending only four weeks working in the department, this month roughy marks a year since I started my unlikely career as a statistician and was inaugurated into the hall of opiglets (if you account for my foray into the magic of quantum computing last summer). The past year has been filled with learning opportunities, some of which I ought to take note and others are probably worth forgetting. Nonetheless, here is a short list of things I’ve learned in my first year as a DPhil Student, which you may find helpful in what I hope are more precedented times.

Simple and stupid first

When it comes to deciding how to tackle your next scientific problem or which lesson to start your blog post with, often the simplest and sometimes most ‘stupid’ idea is the way to go. Keeping things simple gives you the time to better understand your question without getting lost in the details of a complex solution. Plus, the results will inform your later next steps.

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Slippery slopes and slippery flats

In this episode of my decade-long quest to correct popular British misconceptions, I wish to turn to one of my most geeky obsessions: trains. In particular, I would like to address a particularly British obsession, which many take as a signal of the lapse of British know-how from its mid-Empire industrial-revolution heights.

This is, of course, ‘leaves on the line‘. Why – demand the British public – must timetables run five to ten minutes slower when there are more leaves on the ground? Why do no other modern countries suffer from these ills? And why does the railway take no action over this commuting scourge?

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IWD 2021 and the Gender Pay Gap

Throughout the pandemic, the statistics on division of childcare and home-schooling responsibilities have been shocking: mothers are taking on 150% more homeschooling than fathers (1), while 71% of working mothers’ furlough applications were rejected (2).  A third of working mothers reported having lost  some or all work due to a lack of childcare during the pandemic, with this figure rising to 44% for  BAME mothers. On top of this, 90% of the UK’s 2 million single parents are women (3). These unequal divisions are threatening to undo decades of progress towards gender equality.

In April 2019, the pay gap between men and women in the UK was 17.3% (4), and at the current rate of gender pay gap reduction, the gap will not be closed until 2052 (5).  The causes of this gap continue to be unequal caring responsibilities,  more women in low-paid work and (illegal) discrimination. BAME women are also subject to the ethnicity pay gap.  While this varies regionally and by ethnicity, in London in 2018 the overall figure was 23% (6).

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Commercialising your research: Where to start?

If you look at some of the biggest technology companies in the world, from Google and Facebook to hardware companies like Dell or even biotech unicorns like Oxford’s own Oxford Nanopore, all of them started on university campuses. If you are a researcher interested in finding out how to make the first steps to commercialise your research here is a quick guide:

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The Coronavirus Antibody Database: 10 months on, 10x the data!

Back in May 2020, we released the Coronavirus Antibody Database (‘CoV-AbDab’) to capture molecular information on existing coronavirus-binding antibodies, and to track what we anticipated would be a boon of data on antibodies able to bind SARS-CoV-2. At the time, we had found around 300 relevant antibody sequences and a handful of solved crystal structures, most of which were characterised shortly after the SARS-CoV epidemic of 2003. We had no idea just how many SARS-CoV-2 binding antibody sequences would come to be released into the public domain…

10 months later (2nd March 2021), we now have tracked 2,673 coronavirus-binding antibodies, ~95% with full Fv sequence information and ~5% with solved structures. These datapoints originate from 100s of independent studies reported in either the academic literature or patent filings.

The entire contents CoV-AbDab database as of 2nd March 2021.
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