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 …
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 …
ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation
Motivation Antibodies are a key component of the immune system and have been
extensively used as biotherapeutics. Accurate knowledge of their structure is central to …
extensively used as biotherapeutics. Accurate knowledge of their structure is central to …
[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 …
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 …
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 …
therapeutics. Computational approaches to developing and designing these molecules are …
[HTML][HTML] Artificial intelligence in pharmaceutical sciences
Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …
impacts the pharmaceutical market. However, investments in a new drug often go …
SAbDab in the age of biotherapeutics: updates including SAbDab-nano, the nanobody structure tracker
C Schneider, MIJ Raybould… - Nucleic acids research, 2022 - academic.oup.com
In 2013, we released the Structural Antibody Database (SAbDab), a publicly available
repository of experimentally determined antibody structures. In the interim, the rapid …
repository of experimentally determined antibody structures. In the interim, the rapid …
Virtual screening algorithms in drug discovery: A review focused on machine and deep learning methods
Drug discovery and repositioning are important processes for the pharmaceutical industry.
These processes demand a high investment in resources and are time-consuming. Several …
These processes demand a high investment in resources and are time-consuming. Several …
The RESP AI model accelerates the identification of tight-binding antibodies
J Parkinson, R Hard, W Wang - Nature communications, 2023 - nature.com
High-affinity antibodies are often identified through directed evolution, which may require
many iterations of mutagenesis and selection to find an optimal candidate. Deep learning …
many iterations of mutagenesis and selection to find an optimal candidate. Deep learning …