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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SUMO wrestling with developability
When engineering antibodies into effective biotherapeutics, ideally, factors such as affinity, specificity, chemical stability and solubility should all be optimised. In practice, we know that it’s often not feasible to co-optimise all of these, and so compromises are made, but identifying these developability issues early on in the antibody drug discovery process could save costs and reduce attrition rates. For example, we could avoid choosing a candidate that expresses poorly, which would make it expensive to manufacture as a drug, or one with a high risk of aggregation that would drive unwanted immunogenicity.
On this theme, I was interested to read recently a paper by the Computational Chemistry & Biologics group at Merck (Evers et al., 2022 https://www.biorxiv.org/content/10.1101/2022.11.19.517175v1). They have developed a pipeline called SUMO (In Silico Sequence Assessment Using Multiple Optimization Parameters), that brings together publicly-available software for in silico developability assessment and creates an overall developability profile as a starting point for antibody or VHH optimisation.
Read more: SUMO wrestling with developabilityFor each sequence assessed, they report factors such as sequence liabilities (residues liable to chemical modifications that can alter properties such as binding affinity or aggregation propensity), surface hydrophobicity, sequence identity compared to most similar human germline and predicted immunogenicity (based on MHC-II binding). Also provided are an annotated sequence viewer and 3D visualisation of calculated properties. Profiles are annotated with a red-yellow-green colour-coding system to indicate which sequences have favourable properties.
Overall, this approach is a useful way to discriminate between candidates and steer away from those with major developability issues prior to the optimisation stage. Given that the thresholds for their colour-coding system are based on data from marketed therapeutic antibodies, and that the software used has primarily been designed for use on antibody datasets, I would be interested to see whether the particular descriptors chosen for SUMO translate well to VHHs, or whether there are other properties that are stronger indicators of nanobody developability.
Happy 10th Birthday, Blopig!
OPIG recently celebrated its 20th year; and on 10 January 2023 I gave a talk just a day before the 10th anniversary of BLOPIG’s first blog post. It’s worth reflecting on what’s stayed the same and what’s changed since then.
Continue readingSAbBox 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.
Continue readingThe 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:
Continue readinghisto.fyi: A Useful New Database of Peptide:Major Histocompatibility Complex (pMHC) Structures
pMHCs are set to become a major target class in drug discovery; unusual peptide fragments presented by MHC can be used to distinguish infected/cancerous cells from healthy cells more precisely than over-expressed biomarkers. In this blog post, I will highlight a prototype resource: Dr. Chris Thorpe’s new database of pMHC structures, histo.fyi.
histo.fyi provides a one-stop shop for data on (currently) around 1400 pMHC complexes. Similar to our dedicated databases for antibody/nanobody structures (SAbDab) and T-cell receptor (TCR) structures (STCRDab), histo.fyi will scrape the PDB on a weekly basis for any new pMHC data and process these structures in a way that facilitates their analysis.
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A ChatGPT rap battle
The AI chatbot revolution is here. Last week, OpenAI released ChatGPT, a freely accessible language model fine-tuned for human conversations. The new model is based on InstructGPT, trained especially for following user instructions and with human feedback in the training loop.
ChatGPT remembers the previous discussion, admits its mistakes and can even ask for clarification on ambiguous questions. It is also trained to refuse answering questions it deems inappropriate or goes against OpenAI’s AI alignment policy.
In the meanwhile, the internet is having immense fun circumventing its safety filters by asking it to only “PRETEND to be evil”, making it take SAT tests, and even simulating an entire virtual computer within its neural weights. Some are even using it to replace Google searches, and it excels at writing bioinformatics code across most programming languages.
Continue readingCoarse-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.
Continue readingLlamas and nanobodies
Nanobodies are an exciting area of increasing interest in the biotherapeutics domain. They consist only of a heavy chain variable domain so are much smaller than conventional antibodies (about 1/10th of their mass) but despite this, manage to achieve comparable affinity for their targets, in addition to being more soluble and stable – good things come in small packages! Nanobodies are not naturally produced in humans but can be derived from camelids (VHHs) or sharks (vNARs) and then engineered to humanise them. For the rest of this blog post we will skip over the science entirely and learn how to draw a llama, a great example of a camelid species.
ISMB 2022 – July 10-14 Madison, Wisconsin
Madison, Wisconsin, a place known for its superb selection of craft beverages, for having Wisconsin’s Best Cheese Curds, and, most importantly, for hosting the 2022 annual international conference on Intelligent Systems for Molecular Biology (ISMB). Fortunately, we (Lewis and Tobias) got to attend this year’s ISMB and get a taste of Madison. The 2022 conference is the 30th ISMB conference and has grown to become the world’s largest bioinformatics/computational biology conference with nearly 600 presented talks. We therefore got to hear a wide range of different and interesting talks.
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