ENGRAB | Antibody engineering by natural selection and by design

Summary
Antibodies represent a powerful defense mechanism due to their capacity to link specific antigen recognition with effector functions and are currently developed as drugs for prophylaxis and therapy of infectious diseases. The generation of antibody diversity represents a remarkable example of protein engineering that is coupled to a stringent mechanism of clonal selection. In the ENGRAB project we propose first to develop an integrated bioinformatics platform to unravel the clonal dynamics of antibody responses and use it to formulate and test hypotheses on the factors that drive antibody selection in primary and recall responses, thus providing a rational basis for vaccination strategies. Second, we will establish the general relevance and impact of receptor-based antibodies, a new type of naturally engineered antibodies generated by templated DNA insertions into immunoglobulin genes. Third, we will use different bispecific antibody formats, including those produced by templated insertions, to engineer, in the same molecule, two binding sites for the HIV spike in order to increase neutralization potency and breadth. Fourth, we will engineer the Fc portion of antibodies to HSV, S. aureus and M. tuberculosis to increase their effector function through loss-of-binding to pathogen Fc receptors or gain-of-binding to human activatory Fc receptors. The program is strongly supported by preliminary findings and will deliver an innovative platform to interrogate natural antibody repertoires and new strategies to engineer antibodies to improve their therapeutic efficacy. The ENGRAB project deals with mechanisms of antibody diversification and engineering with implications for vaccination and immunotherapy. It is therefore submitted to LS6. Given its translational potential it also falls within the scope of LS7.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/885539
Start date: 01-11-2020
End date: 31-10-2025
Total budget - Public funding: 2 478 125,00 Euro - 2 478 125,00 Euro
Cordis data

Original description

Antibodies represent a powerful defense mechanism due to their capacity to link specific antigen recognition with effector functions and are currently developed as drugs for prophylaxis and therapy of infectious diseases. The generation of antibody diversity represents a remarkable example of protein engineering that is coupled to a stringent mechanism of clonal selection. In the ENGRAB project we propose first to develop an integrated bioinformatics platform to unravel the clonal dynamics of antibody responses and use it to formulate and test hypotheses on the factors that drive antibody selection in primary and recall responses, thus providing a rational basis for vaccination strategies. Second, we will establish the general relevance and impact of receptor-based antibodies, a new type of naturally engineered antibodies generated by templated DNA insertions into immunoglobulin genes. Third, we will use different bispecific antibody formats, including those produced by templated insertions, to engineer, in the same molecule, two binding sites for the HIV spike in order to increase neutralization potency and breadth. Fourth, we will engineer the Fc portion of antibodies to HSV, S. aureus and M. tuberculosis to increase their effector function through loss-of-binding to pathogen Fc receptors or gain-of-binding to human activatory Fc receptors. The program is strongly supported by preliminary findings and will deliver an innovative platform to interrogate natural antibody repertoires and new strategies to engineer antibodies to improve their therapeutic efficacy. The ENGRAB project deals with mechanisms of antibody diversification and engineering with implications for vaccination and immunotherapy. It is therefore submitted to LS6. Given its translational potential it also falls within the scope of LS7.

Status

SIGNED

Call topic

ERC-2019-ADG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2018
ERC-2019-ADG