Computational and artificial intelligence-based methods for antibody development

J Kim, M McFee, Q Fang, O Abdin, PM Kim - Trends in pharmacological …, 2023 - cell.com
Due to their high target specificity and binding affinity, therapeutic antibodies are currently
the largest class of biotherapeutics. The traditional largely empirical antibody development …

Designing antibodies as therapeutics

PJ Carter, A Rajpal - Cell, 2022 - cell.com
Antibody therapeutics are a large and rapidly expanding drug class providing major health
benefits. We provide a snapshot of current antibody therapeutics including their formats …

Antibody structure prediction using interpretable deep learning

JA Ruffolo, J Sulam, JJ Gray - Patterns, 2022 - cell.com
Therapeutic antibodies make up a rapidly growing segment of the biologics market.
However, rational design of antibodies is hindered by reliance on experimental methods for …

Deciphering the language of antibodies using self-supervised learning

J Leem, LS Mitchell, JHR Farmery, J Barton, JD Galson - Patterns, 2022 - cell.com
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 …

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

R Akbar, H Bashour, P Rawat, PA Robert, E Smorodina… - MAbs, 2022 - Taylor & Francis
Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs)
are tremendous, the design and discovery of new candidates remain a time and cost …

[HTML][HTML] Advances in computational structure-based antibody design

AM Hummer, B Abanades, CM Deane - Current opinion in structural biology, 2022 - Elsevier
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 …

Computational optimization of antibody humanness and stability by systematic energy-based ranking

A Tennenhouse, L Khmelnitsky, R Khalaila… - Nature biomedical …, 2024 - nature.com
Conventional methods for humanizing animal-derived antibodies involve grafting their
complementarity-determining regions onto homologous human framework regions …

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 …

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 developing and designing these molecules are …

Assessing antibody and nanobody nativeness for hit selection and humanization with AbNatiV

A Ramon, M Ali, M Atkinson, A Saturnino… - Nature Machine …, 2024 - nature.com
Monoclonal antibodies have emerged as key therapeutics. In particular, nanobodies, small,
single-domain antibodies that are naturally expressed in camelids, are rapidly gaining …