Oxford Protein Informatics Group

Andrew D. Blevins and Ian K. Quigley, co-founders of Leash Bio, released a pre-print last year that I think deserves some more attention. Using a Bemis-Murcko scaffold split, the authors show that it is possible to train a machine learning model to identify which of 1,815 medicinal chemists produced a molecule from its structure alone, achieving a top 5 accuracy of 60% and a ...

For the final project of my PhD in OPIG, I developed the Therapeutic Nanobody Profiler, or ‘TNP’: a tool to characterise nanobody developability analogous to TAP (the Therapeutic Antibody Profiler). TNP uses 6 metrics, tailored to the unique features of nanobodies, to benchmark the structural and physicochemical properties of a candidate nanobody against 36 clinical-stage exa...

Those familiar with the immunoinformatics work of our group will know of our Observed Antibody Space (OAS) and Observed T-cell Receptor Space (OTS) databases, which compile and consistently process V(D)J transcriptomics datasets from across a range of studies on natural immune repertoires. These have provided a central community resource of training data for adaptive immune r...

Well by righteous democracy I’m once again given the privilege of inscribing Le Tour De Farce into the annals of history, this year being the 13th consecutive year of OPIG’s summer social cycling pub crawl extravagansa. I will try to recount as much as I can from pieces of other peoples memories (my own is a less reliable source). Here is a reasonable portion of the group sta...

At OpenBind, we’re working to generate large-scale, open experimental datasets of protein-ligand structures and binding measurements to support the development and evaluation of computational methods for drug discovery. One thing I’m particularly excited about is using these data not just for retro...