As someone who works with T cell antigen receptor (TCR) and peptide-major histocompatibility complex (pMHC) data, I have found several Python packages to be very useful for eliminating tedious steps in data cleaning and feature engineering stages.
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New DPhil/PhD Programme in Pharmaceutical Science Joint with GSK!
Many OPIGlets found their way into a DPhil in Protein Informatics through our Systems Approaches to Biomedical Sciences Industrial Doctoral Landscape Award, which was open to applicants 2009-2024. This innovative course, based at the MPLS Doctoral Training Centre (DTC), offered six months of intensive taught modules prior to starting PhD-level research, allowing students to upskill across a diverse range of subjects (coding, mathematics, structural biology, etc.) and to go on to do research in areas significantly distinct from their formal Undergraduate training. All projects also benefited from direct co-supervision from researchers working in the Pharmaceutical industry, ensuring DPhil projects in areas with drug discovery translation potential. Regrettably, having twice successfully applied for renewal of funding, we were unsuccessful in our bid to refund SABS in 2024.
Happily though, we can now formally announce that our bid for a direct successor to SABS, the Transformative Technologies in Pharmaceutical Sciences IDLA, has been backed by the BBSRC, and we will shortly be opening for applications for entry this October [2026]. As someone who benefited from the interdisciplinary training and industry-adjacency of SABS, I’m thrilled to be a co-director of this new Programme and to help deliver this course to a new generation of talented students.
The Experimentally Relevant Future of Molecular Dynamics: Lessons from the Annual Danish Workshop on Advanced Molecular Simulations
I recently had the opportunity to present part of my PhD work on molecular dynamics (MD) studies of engineered T Cell Receptors at the Annual Danish Conference on Advanced Molecular Simulations in Aarhus, Denmark. The meeting had an emphasis on membrane biophysics, multi- & mesoscale simulations, with keynotes focusing on connecting MD to experimental relevance.
What I mainly got from the keynotes, Weria Pezeshkian, Mohsen Sadeghi, Matteo Degiacomi, Lucie Delemotte, and Ilpo Vattulainen is that the community is shifting from from exploratory, proof-of-concept simulations towards more quantitative, decision-ready modelling. i.e., multiscale workflows that admit their limits, report uncertainties, and actually talk to experiments. There was a shared way of thinking about multiscale simulations by first getting the chemistry and thermodynamics right with atomistic or coarse-grained MD, be honest about kinetics at the mesoscale, and only then claim mechanisms for membranes and proteins in ways that can be checked against data.
Here are the main things I took away:
Continue readingNanobodies® galore in Utrecht
At the end of September, I had the opportunity to present at the 4th Single-Domain Antibody (sdAb/VHH) Conference hosted in the city of Utrecht. The sdAb conference is a biennial event, and was held for the first time in Bonn (2019), then in Brussels (2021) and Paris (2023), before coming to the Netherlands this year.
This was the first time I’d attended a VHH-focused conference, and I was taken aback at just how large the community is; the Jaarbeurs ‘Supernova’ event hall was completely sold out, with over 400 researchers in attendance (pictures below courtesy of the organisers). The buzz reflects the ever growing interest in sdAbs as tools to discover new fundamental biology, vectors for diagnosing disease, and as prophylactic or curative therapeutics. Most every disease indication was represented at the conference, from anticancer and antiviral sdAbs to antivenom sdAbs (both for use in lateral flow tests to diagnose the snake that bit you, and as quick ‘epipen’-like therapeutics accessible even in the most remote parts of the world).
Continue readingAntibody developability datasets
Next to binding the antigen with high affinity, antibodies for therapeutic purposes need to be developable. These developability properties includes high expression, high stability, low aggregation, low immunogenicity, and low non-specificity [1]. These properties are often linked and therefore optimising for one property might be at the expense of another. Machine learning methods have been build to guide the optimistation process of one or multiple developability properties.
Performance of these methods is often limited by the amount and type of data available for training. These dataset contain experimental determined scores of biophysical assays related to developability. Some common experimental assays are described in a previous blog post by Matthew Raybould [2]. Here I will discuss some (commonly) used and new dataset related to antibody developability. This list is not exhaustive but might help you start understanding more about antibody developability.
Continue readingA Masterclass in Basic & Translational Immunology with Prof. Abul Abbas
On Thursday 17th April, a group of us made the journey ‘up the hill’ to the Richard Doll building to attend an immunology masterclass from Professor Abul Abbas. Prof. Abbas is an emeritus professor in Pathology at UCSF and author of numerous core textbooks including Basic Immunology: Functions and Disorders of the Immune System.
The whole-day course consisted of a series of lectures covering core topics in immunology, from innate immunity and antigen presentation through to B/T cell subsets, autoimmunity, and immunotherapy.
Continue readingTherapeutic antibodies and their function
Last week during a poster session in the Department of Statistics, I had an interesting discussing with Martin Buttenschoen (working on the other side of the group) regarding the difference between small molecules and antibodies as therapeutics. This discussion made me realise that even though I’m working on antibodies engineering and developability, I could use a little refresher on approved therapeutic antibodies and their mechanisms of action.
In case you also need this bigger picture, or want to get excited about therapeutic antibodies yourself, I will summarise the target, the development process, the molecular function, and the administration for three successful therapeutic antibodies.
Continue readingThe “AI-ntibody” Competition: benchmarking in silico antibody screening/design
We recently contributed to a communication in Nature Biotechnology detailing an upcoming competition coordinated by Specifica to evaluate the relative performance of in vitro display and in silico methods at identifying target-specific antibody binders and performing downstream antibody candidate optimisation.
Following in the footsteps of tournaments such as the Critical Assessment of Structure Prediction (CASP), which have led to substantial breakthroughs in computational methods for biomolecular structure prediction, the AI-ntibody initiative seeks to establish a periodic benchmarking exercise for in silico antibody discovery/design methods. It should help to identify the most significant breakthroughs in the space and orient future methods’ development.
Continue readingMaking your code pip installable
aka when to use a CutomBuildCommand or a CustomInstallCommand when building python packages with setup.py
Bioinformatics software is complicated, and often a little bit messy. Recently I found myself wading through a python package building quagmire and thought I could share something I learnt about when to use a custom build command and when to use a custom install command. I have also provided some information about how to copy executables to your package installation bin. **ChatGPT wrote the initial skeleton draft of this post, and I have corrected and edited.
Next time you need to create a pip installable package yourself, hopefully this can save you some time!
Continue readingConference Summary: AIRR Community Meeting VII – Learnings and Perspectives
At the start of June, we (Lewis and Benjie) attended the AIRR Community meeting in beautiful and sunny Porto, Portugal. This meeting was focused on collecting and analysing adaptive immune receptor repertoires. This comprised of two rivalling factions at the conference: the antibody (Ab) people or the T cell antigen receptor (TCR) people. The split was nearly fifty-fifty between these two topics throughout the conference. Overall, the conference was a fairly comfortable size, with approximately a hundred people in attendance, making it easy to visit all of the posters and talk with many people in your area, without feeling too niche. There was a wide variety of content formats throughout the conference including posters, scientific talks, lightning talks, software demos, and hands-on tutorials. In the following section, we highlight some of our favourite sessions to give a flavour of what this meeting entails.
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