AIMC Topic: Antibodies

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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...
Protein Binding Computational Biology Antibodies Machine Learning Deep Learning Binding Sites Antigen-Antibody Complex Binding Sites, Antibody Epitopes Antigens Humans
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Protein loop structure prediction by community-based deep learning and its application to antibody CDR H3 loop modeling.

PLoS computational biology Jun 24, 2024
As of now, more than 60 years have passed since the first determination of protein structures through crystallography, and a significant portion of protein structures can be predicted by computers. This is due to the groundbreaking enhancement in pro...
Humans Neural Networks, Computer Models, Molecular Antibodies Complementarity Determining Regions Protein Conformation Computational Biology Databases, Protein Algorithms Deep Learning
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Best practices for machine learning in antibody discovery and development.

Drug discovery today May 17, 2024
In the past 40 years, therapeutic antibody discovery and development have advanced considerably, with machine learning (ML) offering a promising way to speed up the process by reducing costs and the number of experiments required. Recent progress in ...
Drug Development Antibodies Humans Machine Learning Animals Drug Discovery Reproducibility of Results
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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 ...
Humans Neural Networks, Computer Molecular Docking Simulation Antibodies Machine Learning Antigen-Antibody Complex Binding Sites, Antibody Epitopes Antigens
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Accurate structure prediction of biomolecular interactions with AlphaFold 3.

Nature May 8, 2024
The introduction of AlphaFold 2 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design. Here we describe our AlphaFold 3 model with a substantially...
Ions Ligands Models, Molecular Antibodies Antigens Nucleic Acids Protein Conformation Reproducibility of Results Molecular Docking Simulation Protein Binding Proteins Deep Learning Humans Software
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A new era of antibody discovery: an in-depth review of AI-driven approaches.

Drug discovery today Apr 18, 2024
Given their high affinity and specificity for a range of macromolecules, antibodies are widely used in the treatment of autoimmune diseases, cancers, inflammatory diseases, and Alzheimer's disease (AD). Traditional experimental methods are time-consu...
Animals Humans Artificial Intelligence Drug Discovery Antibodies
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Beyond Natural Immune Repertoires: Synthetic Antibodies.

Cold Spring Harbor protocols Apr 1, 2024
Synthetic antibody libraries, in which the antigen-binding sites are precisely designed, offer unparalleled precision in antibody engineering, exceeding the potential of natural immune repertoires and constituting a novel generation of research tools...
Antibodies Antigens Artificial Intelligence Peptide Library
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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...
Amino Acid Sequence Antigens Deep Learning Antibodies Humans Algorithms
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Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms.

Frontiers in immunology Feb 28, 2024
Deep learning models have been shown to accurately predict protein structure from sequence, allowing researchers to explore protein space from the structural viewpoint. In this paper we explore whether "novel" features, such as distinct loop conforma...
Complementarity Determining Regions Deep Learning Antibodies Models, Molecular Protein Conformation
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AbImmPred: An immunogenicity prediction method for therapeutic antibodies using AntiBERTy-based sequence features.

PloS one Feb 23, 2024
Due to the unnecessary immune responses induced by therapeutic antibodies in clinical applications, immunogenicity is an important factor to be considered in the development of antibody therapeutics. To a certain extent, there is a lag in using wet-l...
Machine Learning Antibodies
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