AIMC Topic: Antibodies

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AbEpiTope-1.0: Improved antibody target prediction by use of AlphaFold and inverse folding.

Science advances Jun 13, 2025
B cell epitope prediction tools are crucial for designing vaccines and disease diagnostics. However, predicting which antigens a specific antibody binds to and their exact binding sites (epitopes) remains challenging. Here, we present AbEpiTope-1.0, ...
Software Computational Biology Models, Molecular Humans Machine Learning Antigen-Antibody Complex Protein Folding Epitopes, B-Lymphocyte Antibodies Antigens
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Applying computational protein design to therapeutic antibody discovery - current state and perspectives.

Frontiers in immunology May 22, 2025
Machine learning applications in protein sciences have ushered in a new era for designing molecules in silico. Antibodies, which currently form the largest group of biologics in clinical use, stand to benefit greatly from this shift. Despite the prol...
Drug Design Machine Learning Humans Antibodies Computational Biology Drug Discovery Animals Protein Engineering
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Development of an mPBPK machine learning framework for early target pharmacology assessment of biotherapeutics.

Scientific reports Feb 4, 2025
Development of antibodies often begins with the assessment and optimization of their physicochemical properties, and their efficient engagement with the target of interest. Decisions at the early optimization stage are critical for the success of the...
Machine Learning Antibodies, Monoclonal Antibodies Humans Models, Biological
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Challenges and compromises: Predicting unbound antibody structures with deep learning.

Current opinion in structural biology Jan 24, 2025
Therapeutic antibodies are manufactured, stored and administered in the free state; this makes understanding the unbound form key to designing and improving development pipelines. Prediction of unbound antibodies is challenging, specifically modellin...
Models, Molecular Antibodies Deep Learning Protein Binding Protein Conformation Humans
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The Application of Machine Learning on Antibody Discovery and Optimization.

Molecules (Basel, Switzerland) Dec 16, 2024
Antibodies play critical roles in modern medicine, serving as diagnostics and therapeutics for various diseases due to their ability to specifically bind to target antigens. Traditional antibody discovery and optimization methods are time-consuming a...
Machine Learning Humans Antibodies Drug Discovery
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ParaAntiProt provides paratope prediction using antibody and protein language models.

Scientific reports Nov 25, 2024
Efficiently predicting the paratope holds immense potential for enhancing antibody design, treating cancers and other serious diseases, and advancing personalized medicine. Although traditional methods are highly accurate, they are often time-consumi...
Single-Domain Antibodies Humans Complementarity Determining Regions Deep Learning Antibodies Computational Biology Amino Acid Sequence Models, Molecular
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Prediction of antibody-antigen interaction based on backbone aware with invariant point attention.

BMC bioinformatics Nov 6, 2024
BACKGROUND: Antibodies play a crucial role in disease treatment, leveraging their ability to selectively interact with the specific antigen. However, screening antibody gene sequences for target antigens via biological experiments is extremely time-c...
Neural Networks, Computer Deep Learning Humans Antigens Computational Biology Antibodies
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ANTIPASTI: Interpretable prediction of antibody binding affinity exploiting normal modes and deep learning.

Structure (London, England : 1993) Oct 25, 2024
The high binding affinity of antibodies toward their cognate targets is key to eliciting effective immune responses, as well as to the use of antibodies as research and therapeutic tools. Here, we propose ANTIPASTI, a convolutional neural network mod...
Antigens Antigen-Antibody Complex Binding Sites, Antibody Antibody Affinity Models, Molecular Antibodies Deep Learning Protein Binding Humans Neural Networks, Computer
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AI-driven antibody design with generative diffusion models: current insights and future directions.

Acta pharmacologica Sinica Sep 30, 2024
Therapeutic antibodies are at the forefront of biotherapeutics, valued for their high target specificity and binding affinity. Despite their potential, optimizing antibodies for superior efficacy presents significant challenges in both monetary and t...
Antibodies Animals Complementarity Determining Regions Drug Design Humans Artificial Intelligence
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Pretrainable geometric graph neural network for antibody affinity maturation.

Nature communications Sep 6, 2024
Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody therapeutics development. This paper presents a pretrainable geometric graph neural network, GearBind, and explores its potential in in silico affinity...
Enzyme-Linked Immunosorbent Assay Neural Networks, Computer Models, Molecular Humans Computer Simulation Antibody Affinity Deep Learning Antibodies Protein Binding Antigens
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