Antibodies are currently the most important class of biotherapeutics and are used to treat
numerous diseases. Recent advances in computational methods are ushering in a new era …

Antibodies are versatile molecular binders with an established and growing role as
therapeutics. Computational approaches to develo** and designing these molecules are …

Attention-based models trained on protein sequences have demonstrated incredible
success at classification and generation tasks relevant for artificial-intelligence-driven …

Prediction methods inputting embeddings from protein language models have reached or
even surpassed state-of-the-art performance on many protein prediction tasks. In natural …

Antibodies have the capacity to bind a diverse set of antigens, and they have become critical
therapeutics and diagnostic molecules. The binding of antibodies is facilitated by a set of six …

1Program in Molecular Biophysics, Johns Hopkins University, Baltimore, MD, USA,
2Department of Chemical and Biomolecular Engineering, Johns Hopkins University …

Discovery and optimization of monoclonal antibodies for therapeutic applications relies on
large sequence libraries but is hindered by developability issues such as low solubility, high …

Generative machine learning (ML) has been postulated to become a major driver in the
computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to …

Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …

B cell and T cell receptor repertoires compose the adaptive immune receptor repertoire
(AIRR) of an individual. The AIRR is a unique collection of antigen-specific receptors that …