AIMC Topic: Complementarity Determining Regions

Clear Filters Showing 11 to 20 of 24 articles

NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning.

Frontiers in immunology Aug 12, 2022
Antibodies are a rapidly growing class of therapeutics. Recently, single domain camelid VHH antibodies, and their recognition nanobody domain (Nb) appeared as a cost-effective highly stable alternative to full-length antibodies. There is a growing ne...
Deep Learning Antibodies Amino Acid Sequence Single-Domain Antibodies Complementarity Determining Regions
View on PubMed DOI

Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space.

Nature communications Jul 1, 2022
Therapeutic antibody development requires selection and engineering of molecules with high affinity and other drug-like biophysical properties. Co-optimization of multiple antibody properties remains a difficult and time-consuming process that impede...
Antibody Affinity Biophysics Complementarity Determining Regions Machine Learning Benchmarking
View on PubMed DOI

Use of machine learning to identify a T cell response to SARS-CoV-2.

Cell reports. Medicine Jan 16, 2021
The identification of SARS-CoV-2-specific T cell receptor (TCR) sequences is critical for understanding T cell responses to SARS-CoV-2. Accordingly, we reanalyze publicly available data from SARS-CoV-2-recovered patients who had low-severity disease ...
Complementarity Determining Regions Receptors, Antigen, B-Cell Sequence Analysis, DNA Cluster Analysis Amino Acid Sequence High-Throughput Nucleotide Sequencing Principal Component Analysis SARS-CoV-2 Humans T-Lymphocytes Machine Learning Receptors, Antigen, T-Cell COVID-19
View on PubMed DOI

Single T Cell Sequencing Demonstrates the Functional Role of TCR Pairing in Cell Lineage and Antigen Specificity.

Frontiers in immunology Jul 31, 2019
Although structural studies of individual T cell receptors (TCRs) have revealed important roles for both the α and β chain in directing MHC and antigen recognition, repertoire-level immunogenomic analyses have historically examined the β chain alone....
Humans Machine Learning Sequence Analysis, Protein CD4-Positive T-Lymphocytes CD8-Positive T-Lymphocytes Complementarity Determining Regions Antigens Receptors, Antigen, T-Cell, alpha-beta
View on PubMed DOI

Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning.

BMC bioinformatics May 28, 2019
BACKGROUND: The recent success of immunotherapy in treating tumors has attracted increasing interest in research related to the adaptive immune system in the tumor microenvironment. Recent advances in next-generation sequencing technology enabled the...
Databases, Genetic Area Under Curve Tumor Microenvironment Complementarity Determining Regions Humans Amino Acid Sequence Supervised Machine Learning Receptors, Antigen, B-Cell ROC Curve Immunoglobulins Algorithms High-Throughput Nucleotide Sequencing Immunity, Humoral Amino Acid Motifs
View on PubMed DOI

Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method.

mAbs Sep 25, 2018
Monoclonal antibodies (mAbs) have become a major class of protein therapeutics that target a spectrum of diseases ranging from cancers to infectious diseases. Similar to any protein molecule, mAbs are susceptible to chemical modifications during the ...
Antineoplastic Agents, Immunological Antibodies, Monoclonal Methionine Kinetics Computer Simulation Protein Binding Humans Antigens Complementarity Determining Regions Oxidation-Reduction Treatment Outcome Machine Learning
View on PubMed DOI

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...
Antigen-Antibody Complex Complementarity Determining Regions Epitope Mapping Molecular Docking Simulation Antibodies Artificial Intelligence
View on PubMed DOI

Heavy chain sequence-based classifier for the specificity of human antibodies.

Briefings in bioinformatics Jan 17, 2022
Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnostics. High-throughput sequencing technologies have promoted comprehensive profiling of the immune rep...
Antibodies Humans Amino Acid Sequence High-Throughput Nucleotide Sequencing Antibody Specificity Machine Learning Complementarity Determining Regions ROC Curve
View on PubMed DOI

Predicting antibody binders and generating synthetic antibodies using deep learning.

mAbs Jan 1, 2022
The antibody drug field has continually sought improvements to methods for candidate discovery and engineering. Historically, most such methods have been laboratory-based, but informatics methods have recently started to make an impact. Deep learning...
Deep Learning Antibodies Programmed Cell Death 1 Receptor Complementarity Determining Regions CTLA-4 Antigen
View on PubMed DOI

Geometric potentials from deep learning improve prediction of CDR H3 loop structures.

Bioinformatics (Oxford, England) Jul 1, 2020
MOTIVATION: Antibody structure is largely conserved, except for a complementarity-determining region featuring six variable loops. Five of these loops adopt canonical folds which can typically be predicted with existing methods, while the remaining l...
Models, Molecular Antibodies Deep Learning Complementarity Determining Regions Protein Conformation
View on PubMed DOI
Popular Topics
Recent Journals