Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies
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 …
are tremendous, the design and discovery of new candidates remain a time and cost …
[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 …
Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences
The antibody repertoires of individuals and groups have been used to explore disease
states, understand vaccine responses, and drive therapeutic development. The arrival of B …
states, understand vaccine responses, and drive therapeutic development. The arrival of B …
In silico proof of principle of machine learning-based antibody design at unconstrained scale
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 …
computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to …
Machine learning for biologics: opportunities for protein engineering, developability, and formulation
Successful biologics must satisfy multiple properties including activity and particular
physicochemical features that are globally defined as developability. These multiple …
physicochemical features that are globally defined as developability. These multiple …
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 …
Deep geometric representations for modeling effects of mutations on protein-protein binding affinity
Modeling the impact of amino acid mutations on protein-protein interaction plays a crucial
role in protein engineering and drug design. In this study, we develop GeoPPI, a novel …
role in protein engineering and drug design. In this study, we develop GeoPPI, a novel …
A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding
Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …
epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo …
Immunogenicity and humanization of single‐domain antibodies
MA Rossotti, K Bélanger, KA Henry… - The FEBS Journal, 2022 - Wiley Online Library
Single‐domain antibodies (sdAbs), the autonomous variable domains of camelid and shark
heavy‐chain antibodies, have many desirable properties as components of biologic drugs …
heavy‐chain antibodies, have many desirable properties as components of biologic drugs …
Assessing developability early in the discovery process for novel biologics
Beyond potency, a good developability profile is a key attribute of a biological drug.
Selecting and screening for such attributes early in the drug development process can save …
Selecting and screening for such attributes early in the drug development process can save …