SUGARSmart: Smart design of recombinant antibody fragments specific for carbohydrate molecules

Informazioni relative al progetto

SUGARSmart

ID dell’accordo di sovvenzione: 747948

DOI

10.3030/747948

Progetto chiuso

Data della firma CE 11 Ottobre 2017

Data di avvio 10 Luglio 2018

Data di completamento 9 Agosto 2020

Finanziato da

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Costo totale

€ 175 866,00

Contributo UE

€ 175 866,00

Coordinato da

UNIVERSITY OF GALWAY
Ireland

Periodic Reporting for period 1 - SUGARSmart (SUGARSmart: Smart design of recombinant antibody fragments specific for carbohydrate molecules)

Periodo di rendicontazione: 2018-07-10 al 2020-07-09

Sintesi del contesto e degli obiettivi generali del progetto

Glycosylation is one of the most frequently used post-translational modifications (PTM), where proteins are altered with various glycan molecules. Such glycans are sometimes found only in particular groups, species, or organisms. For example, blood group antigens, Galα1,3Gal motif, and N-glycolylneuraminic acid (NeuGc) are not found in humans, and exposure to these non-self glycans can trigger severe allergic reactions in humans. Thus, it is essential to prevent the presence of any antigenic carbohydrate in biopharmaceuticals, and a majority of them are produced in animal cell lines. Therefore, it is crucial to design molecules that can be used to detect the presence of such antigenic carbohydrates in food or pharmaceuticals. Such biomolecules can be particular proteins called lectins, antibodies, and aptamers. The project “SUGARSmart” looks at the development of computational workflow to engineer glycan recognition molecules and enhance their binding affinity and specificity.

The objective of this Marie Skłodowska Curie Action (MSCA) has been to (1) improve computational methodologies for modeling antibody-glycan recognition and (2) develop a computation workflow for the rational design of glycan recognition molecules. A parallel goal of this MSCA Fellowship is to foster the development of the researcher’s career in the glycosciences.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

During this project, work toward fulfilling these objectives has been carried out to address some of the proposed project's key aims. A computational pipeline to model structures of glycan-binding antibodies using their protein sequences has been established. It further evaluates performance docking programs in terms of their binding affinity prediction capabilities for antibody-glycan complexes. We found that predicting antibody-glycan binding modes and their binding affinity may disagree with state-of-art, high-throughput experimental techniques such as microarray and ELISA, as the glycans are attached to a surface in such experiments, and only the terminal end is exposed for binding. In contrast, in docking computations, glycans are free to adopt any confirmation. This project highlights limitations of the computational approaches in exploring structure, dynamics, and binding energetics of antibody-glycan complexes and discusses future direction to mitigate these limitations.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

The scFv antibodies, which do not have a well-defined CDR region described by standard definitions, can be modeled using the proposed workflow. This work has addressed computational approaches' limits in predicting the experimental scFv-glycan binding data where glycans are conjugated to a surface. Important key observations have been made, and we can now approach a computational solution for mimicking experiment like conditions in predicting antibody-glycan binding.

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