Computational and artificial intelligence-based methods for antibody development
Due to their high target specificity and binding affinity, therapeutic antibodies are currently
the largest class of biotherapeutics. The traditional largely empirical antibody development …
the largest class of biotherapeutics. The traditional largely empirical antibody development …
[HTML][HTML] Advances in computational structure-based antibody design
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 …
numerous diseases. Recent advances in computational methods are ushering in a new era …
Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning
While AlphaFold2 can predict accurate protein structures from the primary sequence,
challenges remain for proteins that undergo conformational changes or for which few …
challenges remain for proteins that undergo conformational changes or for which few …
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
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 …
therapeutics and diagnostic molecules. The binding of antibodies is facilitated by a set of six …
Deciphering the language of antibodies using self-supervised learning
An individual's B cell receptor (BCR) repertoire encodes information about past immune
responses and potential for future disease protection. Deciphering the information stored in …
responses and potential for future disease protection. Deciphering the information stored in …
A MERS-CoV antibody neutralizes a pre-emerging group 2c bat coronavirus
The repeated emergence of zoonotic human betacoronaviruses (β-CoVs) dictates the need
for broad therapeutics and conserved epitope targets for countermeasure design. Middle …
for broad therapeutics and conserved epitope targets for countermeasure design. Middle …
ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins
Immune receptor proteins play a key role in the immune system and have shown great
promise as biotherapeutics. The structure of these proteins is critical for understanding their …
promise as biotherapeutics. The structure of these proteins is critical for understanding their …
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
1Program in Molecular Biophysics, Johns Hopkins University, Baltimore, MD, USA,
2Department of Chemical and Biomolecular Engineering, Johns Hopkins University …
2Department of Chemical and Biomolecular Engineering, Johns Hopkins University …
BioPhi: A platform for antibody design, humanization, and humanness evaluation based on natural antibody repertoires and deep learning
D Prihoda, J Maamary, A Waight, V Juan… - MAbs, 2022 - Taylor & Francis
Despite recent advances in transgenic animal models and display technologies,
humanization of mouse sequences remains one of the main routes for therapeutic antibody …
humanization of mouse sequences remains one of the main routes for therapeutic antibody …
Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery
W Wilman, S Wróbel, W Bielska… - Briefings in …, 2022 - academic.oup.com
Antibodies are versatile molecular binders with an established and growing role as
therapeutics. Computational approaches to develo** and designing these molecules are …
therapeutics. Computational approaches to develo** and designing these molecules are …