Antibody–antigen complex modelling in the era of immunoglobulin repertoire sequencing

Raybould, Matthew I. J.; Wong, Wing Ki; Deane, Charlotte M.

doi:10.1039/c9me00034h

Cited by 21 publications

(26 citation statements)

References 130 publications

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“…The predictability of paratope-epitope binding is a prerequisite for predicting antibody specificity and in silico antibody and vaccine design. So far, however, it remains unclear whether paratope-epitope binding is predictable (Brown et al, 2019;Raybould et al, 2019a;Sela-Culang et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Recently, computational and machine learning approaches for the sequence-based prediction of paratopes (Deac et al, 2018;Kunik et al, 2012b;Liberis et al, 2018), epitopes (Kringelum et al, 2012) or paratope-epitope (antibody-antigen) interaction (Baran et al, 2017;Deac et al, 2018;Jespersen et al, 2019;Kilambi and Gray, 2017;Krawczyk et al, 2013) are accumulating (for a more complete list of references see here: (Brown et al, 2019;EL-Manzalawy et al, 2017;Esmaielbeiki et al, 2016;Raybould et al, 2019a)). While the accuracy for the sequence-based prediction of paratopes seems generally higher than that for epitopes, overall, prediction accuracy has remained suboptimal -especially with regard to sequence-based prediction of epitope sites and paratope-epitope interaction (Brown et al, 2019;Greenbaum et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

“…This long-standing belief has its roots in the works of Karl Landsteiner and colleagues showing that antibodies can recognize a nearly infinite number of antigens (Landsteiner, 1947). The complexity paradigm was reinforced over the subsequent decades by sequencing and crystallography studies suggesting that not only the interaction space is infinite, but also the sequence and structural space (with minor constraints on the antibody side) (Elhanati et al, 2015;Greiff et al, 2017a;Raybould et al, 2019a).…”

Section: Introductionmentioning

confidence: 99%

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A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

Akbar

Jeliazkov

Robert

et al. 2019

Preprint

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Antibody recognition of antigen relies on the specific interaction of amino acids at the paratopeepitope interface. A long-standing question in the fields of immunology and structural biology is whether paratope-epitope interaction is predictable. A fundamental premise for the predictability of paratope-epitope binding is the existence of structural units that are universally shared among antibody-antigen binding complexes. Here, we identified structural interaction motifs, which together compose a vocabulary of paratope-epitope binding that is shared among investigated antibody-antigen complexes. The vocabulary (i) is finite with less than 10 4 motifs, (ii) mediates specific and non-redundant interactions between paratope-epitope pairs, (iii) is immunity-specific (distinct from the motif vocabulary used by non-immune protein-protein interactions), and (iv) enables the machine learning prediction of paratope or epitope. The discovery of a vocabulary of paratope-epitope interaction demonstrates the learnability and predictability of paratope-epitope interaction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

Akbar

Jeliazkov

Robert

et al. 2019

Preprint

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“…[15]). However, this process is slow and not scalable to the large datasets of antibody sequences available in the early discovery stage [16].…”

Section: Introductionmentioning

confidence: 99%

Ab-Ligity: Identifying sequence-dissimilar antibodies that bind to the same epitope

Wong

Robinson

Bujotzek

et al. 2020

Preprint

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Motivation: Solving the structure of an antibody-antigen complex gives atomic level information of the interactions between an antibody and its antigen, but such structures are expensive and hard to obtain. Alternative experimental sources include epitope mapping and binning experiments which can be used as a surrogate to identify key interacting residues. However, their resolution is usually not sufficient to identify if two antibodies have identical interactions. Computational approaches to this problem have so far been based on the premise that antibodies with similar sequences behave similarly. Such approaches will fail to identify sequence-distant antibodies that target the same epitope. Results: We present Ab-Ligity, a structure-based similarity measure tailored to antibodyantigen interfaces. Using predicted paratopes on model antibody structures, we assessed our ability to identify those antibodies that target highly similar epitopes. Most antibodies adopting similar binding modes can be identified from sequence similarity alone, using methods such as clonotyping. In the challenging subset where the antibody sequences differ significantly, Ab-Ligity is still able to predict antibodies that would bind to highly similar epitopes (area under the precision-recall curve of 0.86). We compared Ab-Ligity's performance to an existing tool InterComp, and showed improved performance alongside a significant speed-up. These results suggest that Ab-Ligity will allow the identification of diverse (sequence-dissimilar) antibodies that bind to the same epitopes from large datasets such as immune repertoires. Availability: http://opig.stats.ox.ac.uk/resources Contact: deane@stats.ox.ac.uk Supplementary information: Supplementary Materials are available at Biorxiv.

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“…However, while sequence information is available on each therapeutic summary page, it is not possible to query these databases by sequence, nor to bulk-download relevant sets of therapeutic sequences for direct bioinformatic analysis. Structural knowledge about both the intended target and the therapeutic lead compound is of high importance for rational drug discovery (12,13). For example, co-crystal complexes reveal where a drug binds to its target (the surface 'epitope'), and separately-solved structures enable more accurate D R A F T docking experiments.…”

Section: Introductionmentioning

confidence: 99%

Thera-SAbDab: the Therapeutic Structural Antibody Database

Raybould

Marks

Lewis

et al. 2019

Preprint

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The Therapeutic Structural Antibody Database (Thera-SAbDab; http://opig.stats.ox.ac.uk/webapps/therasabdab) tracks all antibody-and nanobody-related therapeutics recognised by the World Health Organisation (WHO), and identifies any corresponding structures in the Structural Antibody Database (SAbDab) with near-exact or exact variable domain sequence matches. Thera-SAbDab is synchronised with SAbDab to update weekly, reflecting new Protein Data Bank entries and the availability of new sequence data published by the WHO. Each therapeutic summary page lists structural coverage (with links to the appropriate SAbDab entries), alignments showing where any near-matches deviate in sequence, and accompanying metadata, such as intended target and investigated conditions. Thera-SAbDab can be queried by therapeutic name, by a combination of metadata, or by variable domain sequencereturning all therapeutics that are within a specified sequence identity over a specified region of the query. The sequences of all therapeutics listed in Thera-SAbDab (461 unique molecules, as of 18 th July 2019) are downloadable as a single file with accompanying metadata. Antibody Therapeutic Structures | Nanobody Therapeutic StructuresCorrespondence: deane@stats.ox.ac.uk

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Antibody–antigen complex modelling in the era of immunoglobulin repertoire sequencing

Abstract: This review describes a pipeline to find antigen binders in large immunoglobulin gene sequencing datasets via high-throughput antibody–antigen complex modelling.

Cited by 21 publications

References 130 publications

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

Ab-Ligity: Identifying sequence-dissimilar antibodies that bind to the same epitope

Thera-SAbDab: the Therapeutic Structural Antibody Database

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