Antibody Sequence Prediction

Antibodies play a crucial role in the immune system, offering targeted defense against pathogens and foreign substances. The ability to predict and modify antibody sequences is fundamental in therapeutic antibody design, immunotherapy, and drug development. Traditional methods for antibody sequence prediction are often time-consuming and labor-intensive. However, with the integration of AI technologies, we have redefined this process, enabling rapid and precise prediction of antibody sequences with unparalleled accuracy.

At CD ComputaBio, we harness the power of artificial intelligence to revolutionize antibody sequence prediction. Our cutting-edge approach integrates advanced AI algorithms with biotechnology expertise to offer accurate and efficient antibody sequence prediction services. By leveraging the latest computational tools, we aim to expedite the process of antibody discovery, thereby contributing to the development of groundbreaking therapies and biologics. With a commitment to excellence and innovation, we empower our clients to accelerate their research and development initiatives.

Our Services

Fig 1: Our services of antibody sequence prediction

Antibody Sequence Prediction

Our service encompasses the comprehensive prediction of antibody sequences, tailored to meet the specific requirements of our clients. Whether it involves the prediction of variable regions, CDR loops, or full antibody sequences, our advanced AI algorithms yield efficient and reliable results.

Fig 2: Artificial intelligence-based HDX (AI-HDX) prediction reveals fundamental characteristics to protein dynamics: Mechanisms on SARS-CoV-2 immune escape

Sequence Optimization

In addition to prediction, we offer sequence optimization to enhance the functional properties of antibodies. By applying AI-aided algorithms, we can optimize sequences for improved binding affinity, specificity, and stability.

Fig 3: Our services of antibody sequence prediction

Structural Analysis

Beyond sequence prediction, we also provide structural analysis to elucidate the three-dimensional conformation of antibodies. Our integrated approach combines sequence data with structural modeling, offering insights into antibody-antigen interactions, epitope mapping, and structural stability.

Our Analysis Methods

At CD ComputaBio, we employ a multi-faceted approach, integrating advanced computational methodologies to deliver accurate antibody sequence predictions. Our analysis methods include:

Methods Description
Machine Learning Algorithms We utilize state-of-the-art machine learning models to decipher complex patterns within antibody sequences. By training these algorithms on vast datasets of known antibodies, we can extrapolate patterns and predict novel antibody sequences with high fidelity.
Homology Modeling Homology modeling enables the generation of three-dimensional structures of antibodies based on known homologous structures. This approach allows us to predict antibody sequences by leveraging the structural information of related antibodies, facilitating the prediction of variable regions and critical binding sites.
Sequence Alignment Our advanced sequence alignment algorithms enable the comparison of target antibody sequences with known databases, facilitating the identification of conserved regions, variable domains, and potential antigen-binding sites.

Result Delivery

Fig 4: Our delivery of antibody sequence prediction

CD ComputaBio leverages advanced AI technology to deliver precise and reliable antibody sequence predictions, employing machine learning algorithms, homology modeling, and sophisticated sequence analysis tools. If you are interested in our services or have any questions, please feel free to contact us.


  • Yu J, Uzuner U, Long B, et al. Artificial intelligence-based HDX (AI-HDX) prediction reveals fundamental characteristics to protein dynamics: Mechanisms on SARS-CoV-2 immune escape[J]. Iscience, 2023, 26(4).


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