AIMC Topic: Antigen-Antibody Complex
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AI-augmented physics-based docking for antibody-antigen complex prediction.
Bioinformatics (Oxford, England)
Mar 29, 2025
MOTIVATION: Predicting the structure of antibody-antigen complexes is a challenging task with significant implications for the design of better antibody therapeutics. However, the levels of success have remained dauntingly low, particularly when high...
AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences.
Briefings in bioinformatics
May 23, 2024
The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods ...
proABC-2: PRediction of AntiBody contacts v2 and its application to information-driven docking.
Bioinformatics (Oxford, England)
Dec 22, 2020
MOTIVATION: Monoclonal antibodies are essential tools in the contemporary therapeutic armory. Understanding how these recognize their antigen is a fundamental step in their rational design and engineering. The rising amount of publicly available data...
Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties.
Advances in experimental medicine and biology
Jan 1, 2020
Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas. Although several approaches have been proposed for antibody clustering, still no consensus has been reached. Numerous attempts use information from g...
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