AIMC Topic: Antigens
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AbDPP: Target-oriented antibody design with pretraining and prior biological structure knowledge.
Proteins
Mar 5, 2024
Antibodies represent a crucial class of complex protein therapeutics and are essential in the treatment of a wide range of human diseases. Traditional antibody discovery methods, such as hybridoma and phage display technologies, suffer from limitatio...
DeepAIR: A deep learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis.
Science advances
Aug 9, 2023
Structural docking between the adaptive immune receptors (AIRs), including T cell receptors (TCRs) and B cell receptors (BCRs), and their cognate antigens are one of the most fundamental processes in adaptive immunity. However, current methods for pr...
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies.
Nature communications
Apr 25, 2023
Antibodies have the capacity to bind a diverse set of antigens, and they have become critical therapeutics and diagnostic molecules. The binding of antibodies is facilitated by a set of six hypervariable loops that are diversified through genetic rec...
AbAgIntPre: A deep learning method for predicting antibody-antigen interactions based on sequence information.
Frontiers in immunology
Dec 22, 2022
INTRODUCTION: Antibody-mediated immunity is an essential part of the immune system in vertebrates. The ability to specifically bind to antigens allows antibodies to be widely used in the therapy of cancers and other critical diseases. A key step in a...
T cell immune responses deciphered.
Science (New York, N.Y.)
May 19, 2022
A machine-learning approach reveals antigen encoding that predicts T cell responses.
Simultaneous phenotyping of five Rh red blood cell antigens on a paper-based analytical device combined with deep learning for rapid and accurate interpretation.
Analytica chimica acta
Apr 5, 2022
Both the ABO and Rhesus (Rh) blood groups play crucial roles in blood transfusion medicine. Herein, we report a simple and low-cost paper-based analytical device (PAD) for phenotyping red blood cell (RBC) antigens. Using this Rh typing format, 5 Rh a...
Single B cell technologies for monoclonal antibody discovery.
Trends in immunology
Nov 4, 2021
Monoclonal antibodies (mAbs) are often selected from antigen-specific single B cells derived from different hosts, which are notably short-lived in ex vivo culture conditions and hence, arduous to interrogate. The development of several new technique...
Protein design and variant prediction using autoregressive generative models.
Nature communications
Apr 23, 2021
The ability to design functional sequences and predict effects of variation is central to protein engineering and biotherapeutics. State-of-art computational methods rely on models that leverage evolutionary information but are inadequate for importa...
Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning.
Nature biomedical engineering
Apr 15, 2021
The optimization of therapeutic antibodies is time-intensive and resource-demanding, largely because of the low-throughput screening of full-length antibodies (approximately 1 × 10 variants) expressed in mammalian cells, which typically results in fe...
Prediction of Specific TCR-Peptide Binding From Large Dictionaries of TCR-Peptide Pairs.
Frontiers in immunology
Aug 25, 2020
Current sequencing methods allow for detailed samples of T cell receptors (TCR) repertoires. To determine from a repertoire whether its host had been exposed to a target, computational tools that predict TCR-epitope binding are required. Currents too...
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