Category Archives: Immunoinformatics

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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BioDataScience101: a fantastic initiative to learn bioinformatics and data science

Last Wednesday, I was fortunate enough to be invited as a guest lecturer to the 3rd BioDataScience101 workshop, an initiative spearheaded by Paolo Marcatili, Professor of Bioinformatics at the Technical University of Denmark (DTU). This session, on amino acid sequence analysis applied to both proteomics and antibody drug discovery, was designed and organised by OPIG’s very own Tobias Olsen.

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Speaking about Sequence and Structure at a Summit

A couple of weeks ago I was lucky enough to be asked to speak at the 5th Computational Drug Discovery & Development for Biologics Summit. This was my first virtual conference – it was a shame I didn’t get to visit Boston, and presenting to my empty room was slightly bizarre, but it was great to hear what people have been working on, and there’s definitely something to be said for attending a conference in fluffy socks…

A, antibody structure. An antibody is made up of four chains: two light (orange) and two heavy (blue). Each chain is made up of a series of domains—the variable domains of the light and heavy chains together are known as the Fv region (shown on the right; PDB entry 12E8). The Fv features six loops known as complementarity determining regions or CDRs (shown in dark blue); these are mainly responsible for antigen binding. B, example sequences for the VH and VL, highlighting the CDR regions and the genetic composition. It is estimated that the human antibody repertoire contains up to 1013 unique sequences, enabling the immune system to respond to almost any antigen. This is possible through the recombination of V, D and J gene segments, junctional diversification, and somatic hypermutation.
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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!

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Epitope mapping with structural data for SARS-CoV-2 RBD and 10 known binders

In the past few months we have seen a lot of papers reporting antibodies that they found to bind to SARS-CoV-2 (a database can be found here: http://opig.stats.ox.ac.uk/webapps/covabdab/). Some of them were from the analysis of a patient’s immune system. Some of them come with crystal structures to show where they bind. Some don’t have structures, but they have the sequences and some competition assay data to show approximately where on the spike protein they bind. The main focus is around an area called the Receptor Binding Domain (RBD) which is where the spike protein engages the human ACE2 receptor and causes the downstream problems. In this paper, the authors ran a complete mutagenesis on the RBD of the SARS-CoV-2 spike protein. 

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Curing Dogs With Cancer: The Power of the Antibody

This blog post finally combines the two great passions of my life: antibodies and dogs. Therapeutic antibody development is a huge area and is certainly not limited to humans. In the process of developing antibodies, we often use mouse or rat antibodies, obtained by injecting the animal with the antigen of choice and then collecting the resulting antibodies. The first monoclonal antibodies (mAbs) were produced in this way, by fusing spleen B cells from an immunised mouse or rabbit with immortalised myeloma cells to form antibody-expressing hybridoma cells. However, using antibodies to treat disease in animals lags behind humans.

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Re-educating myself about the light chain

I have an unconscious habit of personification, and I always see the antibody light chain as lazy for not contributing more residues to binding interfaces (obviously a generalisation – e.g. insertions in CDRL4 in anti-HIV bNAbs [1]). Perhaps this is why I have a personal preference for the more diverse [2] heavy chain with its specificity-determining [3] CDR3. Having written this down, I realised it’s actually pretty weird to consider an antibody chain as a person and I ought to re-educate myself about the role that light chains play.

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