AIMC Topic: Antigen-Antibody Reactions

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AlphaBind, a domain-specific model to predict and optimize antibody-antigen binding affinity.

mAbs Jul 22, 2025
Antibodies are versatile therapeutic molecules that use combinatorial sequence diversity to cover a vast fitness landscape. Designing optimal antibody sequences, however, remains a major challenge. Recent advances in deep learning provide opportuniti...
Humans Deep Learning Antibody Affinity Antigen-Antibody Reactions Antibodies, Monoclonal Antigens
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DeepInterAware: Deep Interaction Interface-Aware Network for Improving Antigen-Antibody Interaction Prediction from Sequence Data.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Feb 11, 2025
Identifying interactions between candidate antibodies and target antigens is a key step in developing effective human therapeutics. The antigen-antibody interaction (AAI) occurs at the structural level, but the limited structure data poses a signific...
Antigens Antigen-Antibody Reactions Deep Learning Computational Biology Humans
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Domain-Scan: Combinatorial Sero-Diagnosis of Infectious Diseases Using Machine Learning.

Frontiers in immunology Feb 10, 2021
The presence of pathogen-specific antibodies in an individual's blood-sample is used as an indication of previous exposure and infection to that specific pathogen (e.g., virus or bacterium). Measurement of the diagnostic antibodies is routinely achie...
Genetic Vectors HIV Antibodies AIDS Serodiagnosis Antigen-Antibody Reactions Hepatitis C Antibodies HIV Core Protein p24 Oligonucleotides Polymerase Chain Reaction Hepatitis C Hepatitis C Antigens Amino Acid Sequence DNA, Recombinant HIV Infections Machine Learning DNA Barcoding, Taxonomic HIV Envelope Protein gp160 Peptide Library Communicable Diseases Base Sequence Serologic Tests Peptide Fragments Humans High-Throughput Nucleotide Sequencing Epitopes
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MVSF-AB: accurate antibody-antigen binding affinity prediction via multi-view sequence feature learning.

Bioinformatics (Oxford, England) May 6, 2025
MOTIVATION: Predicting the binding affinity between antigens and antibodies accurately is crucial for assessing therapeutic antibody effectiveness and enhancing antibody engineering and vaccine design. Traditional machine learning methods have been w...
Humans Sequence Analysis, Protein Antigen-Antibody Reactions Computational Biology Antibodies Algorithms Antigens Protein Binding Antibody Affinity Machine Learning
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RLEAAI: improving antibody-antigen interaction prediction using protein language model and sequence order information.

Briefings in bioinformatics May 1, 2025
Antibody-antigen interactions (AAIs) are a pervasive phenomenon in the natural and are instrumental in the design of antibody-based drugs. Despite the emergence of various deep learning-based methods aimed at enhancing the accuracy of AAIs prediction...
Deep Learning Computational Biology Software Algorithms Antigen-Antibody Reactions Proteins Antibodies Humans Neural Networks, Computer
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In silico proof of principle of machine learning-based antibody design at unconstrained scale.

mAbs Jan 1, 2022
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 confirm this hypothesis have been hindered by the infeasibility of testing ...
Binding Sites, Antibody Machine Learning Antigen-Antibody Reactions Antibodies, Monoclonal Epitopes
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