Computational epitope binning reveals functional equivalence of sequence-divergent paratopes

Mahita, Jarjapu; Kim, Dong-Gun; Son, Sumin; Choi, Yoonjoo; Kim, Kwang Ho; Bailey‐Kellogg, Chris

doi:10.1016/j.csbj.2022.04.036

Cited by 4 publications

(3 citation statements)

References 57 publications

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“…In addition, recently artificial-intelligence (AI)-based methods have been used to predict epitopes for Abs with unknown 3D structures. 11 , 12 , 13 , 14 …”

Section: Introductionmentioning

confidence: 99%

Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted

Acar,

Witkowski,

Wejda

et al. 2024

eBioMedicine

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“…In addition, recently artificial-intelligence (AI)-based methods have been used to predict epitopes for Abs with unknown 3D structures. 11 , 12 , 13 , 14 …”

Section: Introductionmentioning

confidence: 99%

Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted

Acar,

Witkowski,

Wejda

et al. 2024

eBioMedicine

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“…Several computational approaches have been developed for predicting antibodies with similar epitopes, and these methods are applicable to antibodies featuring both similar sequences and dissimilar sequences 16 – 19 . However, the limited accuracy and the lack of consideration for epitope variability under physiological conditions significantly restrict their practical application.…”

Section: Introductionmentioning

confidence: 99%

Epitope binning for multiple antibodies simultaneously using mammalian cell display and DNA sequencing

Lin,

Miyamoto,

Ogawara

et al. 2024

Commun Biol

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Epitope binning, an approach for grouping antibodies based on epitope similarities, is a critical step in antibody drug discovery. However, conventional methods are complex, involving individual antibody production. Here, we established Epitope Binning-seq, an epitope binning platform for simultaneously analyzing multiple antibodies. In this system, epitope similarity between the query antibodies (qAbs) displayed on antigen-expressing cells and a fluorescently labeled reference antibody (rAb) targeting a desired epitope is analyzed by flow cytometry. The qAbs with epitope similar to the rAb can be identified by next-generation sequencing analysis of fluorescence-negative cells. Sensitivity and reliability of this system are confirmed using rAbs, pertuzumab and trastuzumab, which target human epidermal growth factor receptor 2. Epitope Binning-seq enables simultaneous epitope evaluation of 14 qAbs at various abundances in libraries, grouping them into respective epitope bins. This versatile platform is applicable to diverse antibodies and antigens, potentially expediting the identification of clinically useful antibodies.

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“… 11 In addition, several works rely on structural complementary and docking methods, some in combination with machine learning, to predict epitope-paratope engagement. 12 , 13 , 14 , 15 , 16 , 17 …”

Section: Introductionmentioning

confidence: 99%

Structure-free antibody paratope similarity prediction for in silico epitope binning via protein language models

Ghanbarpour¹,

Jiang²,

Foster³

et al. 2023

iScience

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Computational epitope binning reveals functional equivalence of sequence-divergent paratopes

Cited by 4 publications

References 57 publications

Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted

Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted

Epitope binning for multiple antibodies simultaneously using mammalian cell display and DNA sequencing

Structure-free antibody paratope similarity prediction for in silico epitope binning via protein language models

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