Category Archives: Antibodies

The wider applications of nanobodies

This week, it was my turn to give the short talk at our group meeting. I chose to present a recently published paper on thermostability prediction for nanobodies. The motivation for this work, at least in part, is the need for thermostability in the diverse applications of nanobodies. At OPIG, our research primarily revolves around the therapeutic uses of nanobodies, but their potential extends beyond this. I thought it would be interesting to highlight some of these broader applications here:

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Conference summary: Generative AI in Life Science

This year I attended the second edition of Generative AI in Life Science (GenLife – https://genlife.dk/) and it was an enriching experience that I thoroughly enjoyed. Held in Copenhagen, the event brought together researchers from different areas of AI applied to the life sciences and provided a fantastic platform for networking, learning and sharing ideas. The programme included a mix of long and short talks from experts in the field, but also had a significant presence of emerging PIs, making the conference a perfect place to discover emerging groups in the field. Here I have collected some highlights of the talks I have enjoyed the most at the conference.

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Conference Summary: MGMS Adaptive Immune Receptors Meeting 2024

On 5th April 2024, over 60 researchers braved the train strikes and gusty weather to gather at Lady Margaret Hall in Oxford and engage in a day full of scientific talks, posters and discussions on the topic of adaptive immune receptor (AIR) analysis!

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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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Let your library design blosum

During the lead optimisation stage of the drug discovery pipeline, we might wish to make mutations to an initially identified binding antibody to improve properties such as developability, immunogenicity, and affinity.

There are many ways we could go about suggesting these mutations including using Large Language Models e.g. ESM and AbLang, or Inverse Folding methods e.g. ProteinMPNN and AntiFold. However, some of our recent work (soon to be pre-printed) has shown that classical non-Machine Learning approaches, such as BLOSUM, could also be worth considering at this stage.

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What can you do with the OPIG Immunoinformatics Suite? v3.0

OPIG’s growing immunoinformatics team continues to develop and openly distribute a wide variety of databases and software packages for antibody/nanobody/T-cell receptor analysis. Below is a summary of all the latest updates (follows on from v1.0 and v2.0).

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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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