AI in 3D compound design by Hadfield, TE, Deane, CM

Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding by Hadfield, TE, Scantlebury, J, Deane, CM

Current structure predictors are not learning the physics of protein folding by Outeiral, C, Nissley, DA, Deane, CM

Learning from the ligand: using ligand-based features to improve binding affinity prediction by Boyles, F, Deane, CM, Morris, GM

PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences by Buttenschoen, M, Morris, GM, Deane, CM

Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences by Olsen, TH, Boyles, F, Deane, CM

Current structure predictors are not learning the physics of protein folding by Outeiral, C, Nissley, DA, Deane, CM

Generating property-matched decoy molecules using deep learning by Imrie, F, Bradley, AR, Deane, CM

Learning from docked ligands: ligand-based features rescue structure-based scoring functions when trained on docked poses by Boyles, F, Deane, CM, Morris, GM

AbLang: an antibody language model for completing antibody sequences by Olsen, TH, Moal, IH, Deane, CM

Exploring peptide/MHC detachment processes using hierarchical natural move Monte Carlo by Knapp, B, Demharter, S, Deane, CM, Minary, P

Challenges and opportunities for Bayesian statistics in proteomics by Crook, OM, Chung, C-w, Deane, CM

Computationally profiling peptide: MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies by Raybould, MIJ, Nissley, DA, Kumar, S, Deane, CM

ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation by Abanades, B, Georges, G, Bujotzek, A, Deane, CM

DLAB: deep learning methods for structure-based virtual screening of antibodies by Schneider, C, Buchanan, A, Taddese, B, Deane, CM

Prospects for the computational humanization of antibodies and nanobodies by Gordon, GL, Raybould, MIJ, Wong, A, Deane, CM

KA-Search, a method for rapid and exhaustive sequence identity search of known antibodies by Olsen, TH, Abanades, B, Moal, IH, Deane, CM

Deep generative design with 3D pharmacophoric constraints by Imrie, F, Hadfield, TE, Bradley, AR, Deane, CM

p-IgGen: a paired antibody generative language model by Turnbull, OM, Oglic, D, Croasdale-Wood, R, Deane, CM

It is theoretically possible to avoid misfolding into non-covalent lasso entanglements using small molecule drugs by Jiang, Y, Deane, CM, Morris, GM, O’Brien, EP