Tag Archives: Antibodies

The Antibody Dictionary

Similar to getting lost in a language when moving country, you might encounter a language barrier when moving research fields. This dictionary will guide you in the complex world of immunoinformatics, with a focus on antibodies. Whether your main research will be in this field, you want to apply your machine learning model on antibodies, or you just want to understand the research performed in OPIG, this dictionary will get you started.

The Antibody Dictionary:

Affinity maturation: The optimisation process of naive antibodies to memory antibodies such that the antibody is optimised for a specific antigen. 

Antibody: (immunoglobulin) a Y-shaped molecule important in the adaptive immune system. A canonical antibody consists of two identical heavy chains and two identical smaller light chains. 

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Exploring the Observed Antibody Space (OAS)

The Observed Antibody Space (OAS) [1,2] is an amazing resource for investigating observed antibodies or as a resource for training antibody specific models, however; its size (over 2.4 billion unpaired and 1.5 million paired antibody sequences as of June 2023) can make it painful to work with. Additionally, OAS is extremely information rich, having nearly 100 columns for each antibody heavy or light chain, further complicating how to handle the data. 

From spending a lot of time working with OAS, I wanted to share a few tricks and insights, which I hope will reduce the pain and increase the joy of working with OAS!

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SAbBox in 2023: ImmuneBuilder and more!

For several years now, we have distributed the SAbDab database and SAbPred tools as a virtual machine, SAbBox, via Oxford University Innovation. This virtual machine allows a user to utilise the tools and database locally, allowing for high-throughput analysis and keeping confidential data within a local network. Initially distributed under a commercial licence, the platform proved popular and, in 2020, we introduced a free academic licence to enable our academic colleagues to use our tools and database locally.

Following requests from users, in 2021 we released a new version of the platform packaged as a Singularity container. This included all of the features of SAbBox, allowing Linux users to take advantage of the near bare-metal performance of Singularity when running SAbPred tools. Over the past year, we have made lots of improvements to both SAbBox platforms, and have more work planned for the coming year. I’ll briefly outline these developments below.

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The exotic zoo of antibodies

When I think of antibodies, I usually think of the standard human Y-shaped IgG. It is easy to forget that the world of antibodies is extremely diverse, both in the constant domain, with many different isotypes (i.e. IgA, IgD, IgE, and IgM), and in the variable domain (i.e. with or without a light chain and CDR lengths). This is before we even start looking at engineered antibodies, like the ones illustrated in a previous blog post by Alissa

Of the many different antibodies, in this blog post, I want to highlight some of the exotic naturally occurring antibodies which might not have gotten much attention yet, but which each have interesting features.

The standard antibody (i.e. humans, mouse)

This is the standard antibody which we will compare with. A protein complex of two paired heavy and light chains forming the well-known Y shape. At the tips, a binding site that consists mainly of the three CDR’s on each chain. Nice and simple. 

Interesting facts:

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Festival of Biologics 2022 – November 2-4 Basel, Switzerland

In November I attended the Festival of Biologics (FoB) 2022 conference in Basel, Switzerland. Originally a set of different conferences (now called agendas) that has merged into a single conference, FoB focuses on anything related to biologics. One of the agendas is an antibody specific agenda, derived from the former European Antibody Congress. This year the antibodies agenda had more than 100 talks across multiple tracks, covering many different aspects of using antibodies as therapeutics, making it an exciting conference for an antibody enthusiast. However, while FoB does include talks on machine learning and bioinformatics, most are focused solely on experimental work. Another drawback is that the majority of the talks are by industry, with the few academic speakers almost all also representing a company. This meant that of the few talks about computational methods and tools for protein design, most felt more like a commercial rather than a research presentation. Nonetheless, FoB is still an interesting conference to attend when you are working on applied research for antibody therapeutics. It is an amazing opportunity to hear about which antibody specific problems companies are trying to overcome, which are deemed solved and which are the future problems to solve.

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Coarse-grained models of antibody solutions

Various coarse-grained (CG) models have become increasingly common in studies of antibody-antibody interactions in solution. These models appear poised to enter development pipelines in the near future to help predict and understand how antibody-antibody interactions influence the suitability of a given monoclonal antibody (mAb) for mass production and delivery as an antibody therapy. This blog post is a non-exhaustive summary of some of the highlights I found during a recent literature search.

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The SARS-CoV-2 protein spike glycosylation not only shields but primes binding by providing structural stability too

Yep, it is very well known that the sugar coating (aka glycosylation) of viruses makes them invisible to the immune system, a strategy so effective that like in the case of HIV, whose spike is almost entirely covered by glycans, makes it so difficult to target by the human immune system.

Unsurprisingly, coronaviruses such as SARS, MERS, and SARS-CoV-1(2) not only benefit from this evolutionary strategy but there is evidence now that sugars provide stability to their spikes to be effective binders by glueing the spike chains, hence making them infectious.

This is the major finding of this paper that introduces very interesting results from all-atom MD simulations of a fully glycosylated model of the  SARS-CoV-2 spike protein embedded in a realistic viral membrane. Researchers aimed to look into the stability of the protein spike (A, B, and C) chains in the “open” and “closed” conformation and how these changed upon key residue mutations to test how glycans sitting in the inter-chain space affect stability. It also aimed at quantifying glycans’ shielding effect from molecules ranging from 2 to 15 Angstroms, i.e., from small-sized to peptide- and antibody-sized molecules.  

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A to Z of Alternative Antibody Formats: Next-Generation Therapeutics

Do you know your diabodies from your zybodies?

Antibodies are a highly important class of therapeutics used to treat a range of diseases. Given their success as therapeutics, a wide variety of alternative antibody formats have been developed – these are driving the next generation of antibody therapeutics.

To note, this is not an exhaustive list but rather intended to demonstrate the range of existing antibody formats.

Inspired by this article in The Guardian: “Rachel Roddy’s A-Z of pasta

Figure 1. Alternative Antibody Formats
Many of these figures were adapted from Spiess et al., 2015. Additionally, some of these formats have multiple variations or further possible forms (e.g., trispecific antibodies) – in these cases, one example is given here.

A – Antibodies

Antibodies – a fitting place to start this post. Antibodies are proteins produced by our immune systems to detect and protect against foreign pathogens. The ability of antibodies to bind molecules strongly and specifically – properties essential to their role in our immune defence – also make them valuable candidates for therapeutics. Antibody therapies have been developed for the treatment of various diseases, including cancers and viruses, and form a market estimated at over $100 billion1.

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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!

Example of identified interaction motifs. Figure from Akbar et al, 2021
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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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