AIMC Topic: Antigen-Antibody Complex
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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, ...
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...
Machine-learning-based structural analysis of interactions between antibodies and antigens.
Bio Systems
Jul 2, 2024
Computational analysis of paratope-epitope interactions between antibodies and their corresponding antigens can facilitate our understanding of the molecular mechanism underlying humoral immunity and boost the design of new therapeutics for many dise...
Prediction of Paratope-Epitope Pairs Using Convolutional Neural Networks.
International journal of molecular sciences
May 16, 2024
Antibodies play a central role in the adaptive immune response of vertebrates through the specific recognition of exogenous or endogenous antigens. The rational design of antibodies has a wide range of biotechnological and medical applications, such ...
Historical perspective and future directions: computational science in immuno-oncology.
Journal for immunotherapy of cancer
Jan 8, 2024
Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, undersc...
Deep learning-based multi-model approach on electron microscopy image of renal biopsy classification.
BMC nephrology
May 9, 2023
BACKGROUND: Electron microscopy is important in the diagnosis of renal disease. For immune-mediated renal disease diagnosis, whether the electron-dense granule is present in the electron microscope image is of vital importance. Deep learning methods ...
Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.
Methods in enzymology
Dec 8, 2022
Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, structural characterization of antibody-antigen complexes remains challenging. On the one hand, X-ray...
Simultaneous prediction of antibody backbone and side-chain conformations with deep learning.
PloS one
Jun 15, 2022
Antibody engineering is becoming increasingly popular in medicine for the development of diagnostics and immunotherapies. Antibody function relies largely on the recognition and binding of antigenic epitopes via the loops in the complementarity deter...
Staged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences.
BMC genomics
Mar 14, 2017
BACKGROUND: The broad heterogeneity of antigen-antibody interactions brings tremendous challenges to the design of a widely applicable learning algorithm to identify conformational B-cell epitopes. Besides the intrinsic heterogeneity introduced by di...
Role of Antioxidants in Horse Serum-mediated Vasculitis in Swine: Potential Relevance to Early Treatment in Mitigation of Coronary Arteritis in Kawasaki Disease.
Pediatrics and neonatology
Dec 18, 2016
BACKGROUND: Horse serum-induced immune complex coronary vasculitis in swine is the first experimental model to mimic most of the pictures of Kawasaki disease. Immune complex mechanism has been implicated as one of the possible mechanisms in the patho...
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