Bora Guloglu

Sep 26, 2024 | biorxiv.org | Timothy Atkinson |Thomas Barrett |Scott Cameron |Bora Guloglu

AbstractExploring the vast and largely uncharted territory of amino acid sequences is crucial for understanding complex protein functions and the engineering of novel therapeutic proteins. Whilst generative machine learning has advanced protein sequence modelling, no existing approach is proficient for both unconditional and conditional generation. In this work, we propose that Bayesian Flow Networks (BFNs), a recently introduced framework for generative modelling, can address these challenges.

Sep 26, 2024 | biorxiv.org | Timothy Atkinson |Thomas Barrett |Scott Cameron |Bora Guloglu

AbstractExploring the vast and largely uncharted territory of amino acid sequences is crucial for understanding complex protein functions and the engineering of novel therapeutic proteins. Whilst generative machine learning has advanced protein sequence modelling, no existing approach is proficient for both unconditional and conditional generation. In this work, we propose that Bayesian Flow Networks (BFNs), a recently introduced framework for generative modelling, can address these challenges.

May 21, 2024 | biorxiv.org | Bora Guloglu |Brennan Abanades |Vijaykumar Karuppiah |Nele P Quast

AbstractT-cell receptor (TCR) structures are currently under-utilised in early-stage drug discovery and repertoire-scale informatics. Here, we leverage a large dataset of solved TCR structures from Immunocore to evaluate the current state-of-the-art for TCR structure prediction, and identify which regions of the TCR remain challenging to model.

Jul 1, 2023 | biorxiv.org | Oliver Turnbull |Annabel Suter |Bora Guloglu |Charlotte M. Deane

New Results doi: https://doi.org/10.1101/2023.06.28.546839 AbstractAntibodies with lambda light chains (lambda-antibodies) are generally considered to be less developable than those with kappa light chains (kappa-antibodies), leading to substantial systematic biases in drug discovery pipelines. This has contributed to kappa dominance amongst clinical-stage therapeutics.

Jun 30, 2023 | biorxiv.org | Oliver Turnbull |Annabel Suter |Bora Guloglu |Charlotte M. Deane

New Results doi: https://doi.org/10.1101/2023.06.28.546839 AbstractAntibodies with lambda light chains (lambda-antibodies) are generally considered to be less developable than those with kappa light chains (kappa-antibodies), leading to substantial systematic biases in drug discovery pipelines. This has contributed to kappa dominance amongst clinical-stage therapeutics.