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!
Continue readingCategory Archives: Molecular Recognition
Inverse Vaccines
One of the nice things about OPIG, is that you can talk about something which is outside of your wheelhouse without feeling that the specialists in the group are going to eat your lunch. Last week, I gave an overview of the Hubbell group‘s Nature paper Synthetically glycosylated antigens for the antigen-specific suppression of established immune responses. I am not an immunologist by any stretch of the imagination, but sometimes you come across a piece of really interesting science and just want to say to people: Have you seen this, look at this, it’s really clever!
Continue reading9th Joint Sheffield Conference on Cheminformatics
Over the next few days, researchers from around the world will be gathering in Sheffield for the 9th Joint Sheffield Conference on Cheminformatics. As one of the organizers (wearing my Molecular Graphics and Modeling Society ‘hat’), I can say we have an exciting array of speakers and sessions:
- De Novo Design
- Open Science
- Chemical Space
- Physics-based Modelling
- Machine Learning
- Property Prediction
- Virtual Screening
- Case Studies
- Molecular Representations
It has traditionally taken place every three years, but despite the global pandemic it is returning this year, once again in person in the excellent conference facilities at The Edge. You can download the full programme in iCal format, and here is the conference calendar:
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.
Continue readingCryoEM is now the dominant technique for solving antibody structures
Last year, the Structural Antibody Database (SAbDab) listed a record-breaking 894 new antibody structures, driven in no small part by the continued efforts of the researchers to understand SARS-CoV-2.
In this blog post I wanted to highlight the major driving force behind this curve – the huge increase in cryo electron microscopy (cryoEM) data – and the implications of this for the field of structure-based antibody informatics.
Continue readingNew review on BCR/antibody repertoire analysis out in MAbs!
In our latest immunoinformatics review, OPIG has teamed up with experienced antibody consultant Dr. Anthony Rees to outline the evidence for BCR/antibody repertoire convergence on common epitopes post-pathogen exposure, and all the ways we can go about detecting it from repertoire gene sequencing data. We highlight the new advances in the repertoire functional analysis field, including the role for OPIG’s latest tools for structure-aware antibody analytics: Structural Annotation of AntiBody repertoires+ (SAAB+), Paratyping, Ab-Ligity, Repertoire Structural Profiling & Structural Profiling of Antibodies to Cluster by Epitope (‘SPACE’).
Continue readingAutomated intermolecular interaction detection using the ODDT Python Module
Detecting intermolecular interactions is often one of the first steps when assessing the binding mode of a ligand. This usually involves the human researcher opening up a molecular viewer and checking the orientations of the ligand and protein functional groups, sometimes aided by the viewer’s own interaction detecting functionality. For looking at single digit numbers of structures, this approach works fairly well, especially as more experienced researchers can spot cases where the automated interaction detection has failed. When analysing tens or hundreds of binding sites, however, an automated way of detecting and recording interaction information for downstream processing is needed. When I had to do this recently, I used an open-source Python module called ODDT (Open Drug Discovery Toolkit, its full documentation can be found here).
My use case was fairly standard: starting with a list of holo protein structures as pdb files and their corresponding ligands in .sdf format, I wanted to detect any hydrogen bonds between a ligand and its native protein crystal structure. Specifically, I needed the number and name of the the interacting residue, its chain ID, and the name of the protein atom involved in the interaction. A general example on how to do this can be found in the ODDT documentation. Below, I show how I have used the code on PDB structure 1a9u.
Continue readingVisualising macromolecules and grids in Jupyter Notebooks with nglview
If you do most of your work in Jupyter notebooks, it can be convenient to have a quick visualisation tool to view the results of your latest computation from within the notebook, without having to flick between the notebook and your favourite molecule viewer.
I have recently started using NGLview, an IPython/Jupyter widget, to do this. It is based on the NGL viewer, an embeddable webapp for macromolecular visualisation. The nglvew module documentation can be found here, and in addition to handling the usual formats for molecular structure (.pdb, .mol2, .sdf, .pqr, etc.) and map density(.ccp4 and more), it supports visualising trajectories and even making movies.
Continue readingThe Coronavirus Antibody Database (CoV-AbDab)
We are happy to announce the release of CoV-AbDab, our database tracking all coronavirus binding antibodies and nanobodies with molecular-level metadata. The database can be searched and downloaded here: http://opig.stats.ox.ac.uk/webapps/coronavirus
Continue readingWhat are Hotspots in Structural Biology?
“Hotspot” is one of those extremely versatile words, similar to “model” and “buffer”, which can mean a variety of things depending on context. According to Merriam-Webster, a hotspot is “a place of more than usual interest, activity, or popularity”. This is the most general definition of the concept I could find in a quick search, and the one I find closest in spirit to the way hotspots are perceived in a structural biology context. What this blog post is definitely not about are hotspots as “areas of political, military, or civil unrest” (my experience with them has so far been mostly peaceful), or anything to do with geology, WiFi connections, or forest fires.
However, even within the context of structural biology and structure-based drug design, the word “hotspot” has multiple meanings. In this blog post, I will try to summarise the main ones I have come across, the (sometimes subtle) differences between them, and provide a few useful papers to serve as an entry point for interested readers. Continue reading