Category Archives: Protein Engineering

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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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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The State of Computational Protein Design

Last month, I had the privilege to attend the Keystone Symposium on Computational Design and Modeling of Biomolecules in beautiful Banff, Canada. This conference gave an incredible insight into the current state of the protein design field, as we are on the precipice of advances catalyzed by deep learning.

Here are my key takeaways from the conference:

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Experience at a Keystone Symposium

From 19th-22nd February I was fortunate enough to participate in the joint Keystone Symposium on Next-Generation Antibody Therapeutics and Multispecific Immune Cell Engagers, held in Banff, Canada. Now in their 51st year, the Keystone Symposia are a comprehensive programme of scientific conferences spanning the full range of topics relating to human health, from studies on fundamental bodily processes through to drug discovery.

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3 Key Questions to Think About When Designing Proteins Computationally

We have reached the era of design, not just ‘hunting’. Particularly exciting to me is the de novo design of proteins, which have a wide and ever increasing range of applications from therapeutics to consumer products, biomanufacturing to biomaterials. Protein design has been a) enabled by decades of research that contributed to our understanding of protein sequence, structure & function and b) accelerated by computational advances – capturing the information we have learned from proteins and representing it for computers and machine learning algorithms.

In this blog post, I will discuss three key methodological considerations for computational protein design:

  1. Sequence- vs structure-based design
  2. ML- vs physics-based design
  3. Target-agnostic vs target-aware design
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A quantitative way to measure targeted protein degradation

Whenever we order consumables in the Chemistry department, the whole lab gets an email notification once they arrive. So I can understand why I got some puzzled reactions from my colleagues when one such email arrived saying that my ‘artichoke’ was ready to collect from stores. Had I been sneakily doing my grocery shopping on a university research budget?

Artichoke is, in fact, the name of a plasmid designed by the Ebert lab (https://www.addgene.org/73320/), which I have been using in some of my research on targeted protein degradation. The premise is simple enough: genes for two different fluorescent proteins, one of which is fused to a protein-of-interest.

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What is a plantibody?

Plants can be genetically engineered to express non-native proteins, for example, crops can be engineered to produce insect toxins in order to improve disease-resistance. However, I was not aware of their ability to express antibodies until, inspired by my expanding collection of house plants, I googled ‘plant immune systems’. 

Plants don’t naturally produce antibodies – they do not possess an adaptive immune system or any circulating immune defence cells. Despite this, plants can be made to express and assemble full length antibody heavy chains and light chains. This was first published back in 1989, when Hiatt et al. [1] successfully introduced mouse immunoglobulin genes to tobacco plants and produced functional antibodies with reasonable efficiency. The excellent term ‘plantibody‘ was coined soon after, to refer to antibodies and fragments of antibodies produced by plants transformed with antibody-coding genes. 

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Antibody Engineering and Therapeutics Conference

I was invited to speak at the Antibody Engineering and Therapeutics Conference (presenting mine and Matt’s recently published epitope profiling paper), in San Diego (December 12th – 16th). Unfortunately, the pandemic had other ideas so I decided not to travel but luckily the conference was hybrid. 

The conference included 1 day of pre-conference workshops and 4 days of presentations from academic and industry, with livestreaming of the initial keynotes (including one from Charlotte). Remaining talks were recorded and made available after the conference. I’ve highlighted a few of my favourite talks and conference themes, with links to papers where available.

Naturally, a lot of the presented research related to covid-19. I was speaking in the ‘Antibody Repertoires and Covid-19’ session, where there were interesting presentations from Professor Eline Luning Prak from the University of Pennsylvania and Elaine Chen from Vanderbilt University analysing antibody responses in covid-recovered individuals, and comparing vaccine responses in covid-recovered vs covid-naiive individuals. Other talks around SARS-CoV-2 vaccines included Dr Laura Walker from Adimab/Adagio Therapeutics comparing BCR repertoire responses to different types of vaccinations, and the effect of using different booster types.

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Highlights from the European Antibody Congress 2021

Last month, I was fortunate enough to be able to attend (in person!) and present at the Festival of Biologics European Antibody Congress (9-11 November, 2021) in Basel, Switzerland. The Festival of Biologics is an annual conference, which brings together researchers from industry and academia. It was an excellent opportunity to learn about exciting research and meet people working in the antibody development field.

Here are some of my highlights from the European Antibody Congress, with a focus on antibody design and engineering:

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Targeted protein degradation phenotypic studies using HaloTag CRISPR/Cas9 endogenous target tagging and HaloPROTAC

Biologists currently have several options in their arsenal when it comes to gene silencing. if you want to completely vanquish the gene in question, you can use CRISPR to knock the gene out completely. This is a great way to completely eliminate the gene, and hence compare cell phenotypes with and without the gene, but it’s less good if the gene is essential and the cells won’t grow without it in the first place. 

Otherwise you can use RNA interference, where small pieces of RNA that complement the mRNA for that gene are introduced to the cell, with the overall effect of blocking transcription of that gene’s mRNA, hence silencing it. However, this method suffers from side effects and varying levels of gene knockdown efficiency. Moreover, it does not vanquish existing protein, it just stops more from being produced.

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