AIMC Topic: Antibodies

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MVSF-AB: accurate antibody-antigen binding affinity prediction via multi-view sequence feature learning.

Bioinformatics (Oxford, England)
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...

RLEAAI: improving antibody-antigen interaction prediction using protein language model and sequence order information.

Briefings in bioinformatics
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...

AI-augmented physics-based docking for antibody-antigen complex prediction.

Bioinformatics (Oxford, England)
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...

Deep learning-based design and experimental validation of a medicine-like human antibody library.

Briefings in bioinformatics
Antibody generation requires the use of one or more time-consuming methods, namely animal immunization, and in vitro display technologies. However, the recent availability of large amounts of antibody sequence and structural data in the public domain...

Geometric epitope and paratope prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Identifying the binding sites of antibodies is essential for developing vaccines and synthetic antibodies. In this article, we investigate the optimal representation for predicting the binding sites in the two molecules and emphasize the ...

Antibody design using deep learning: from sequence and structure design to affinity maturation.

Briefings in bioinformatics
Deep learning has achieved impressive results in various fields such as computer vision and natural language processing, making it a powerful tool in biology. Its applications now encompass cellular image classification, genomic studies and drug disc...

AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences.

Briefings in bioinformatics
The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods ...

PD-1 Targeted Antibody Discovery Using AI Protein Diffusion.

Technology in cancer research & treatment
The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncological diseases. This checkpoint protein inhibits T lymphocytes from attacking other cells in the body and thus blocking it improves the clearance of tu...

Artificial intelligence-aided protein engineering: from topological data analysis to deep protein language models.

Briefings in bioinformatics
Protein engineering is an emerging field in biotechnology that has the potential to revolutionize various areas, such as antibody design, drug discovery, food security, ecology, and more. However, the mutational space involved is too vast to be handl...