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PROposing Action to ConTrol and Impede betacoronaVirus Emergencies

Project description

A proactive immunology approach to tackle viral variants before they emerge

The COVID-19 pandemic exposed vulnerability to rapidly evolving viruses, with emerging variants that outpaced vaccines and diverse treatments. The ERC-funded PROACTIVE project will focus on developing vaccines and monoclonal antibodies that could neutralise existing and future variants of SARS-CoV-2 and other coronaviruses. The emphasis will be on regions of the virus less likely to mutate. AI systems will analyse the immune system’s response to the virus, identifying stable parts of the virus that do not change much across different variants. Computer simulations will be used to design proteins that can bind to the virus effectively. These proteins (immunogens) will be placed on nanoparticles to deliver the vaccine more effectively. If successful, PROACTIVE could transform how we combat highly variable pathogens, including influenza and HIV.

Objective

The COVID-19 pandemic caught the world unprepared. Vaccines and monoclonal antibodies (mAbs), developed in record time, mitigated the health and economic damages, however our reaction has always been one step behind the virus evolution, and emerging variants repeatedly escaped our interventions. The omicron variant escaped humoral immunity generated by most vaccines and mAbs by mutating immunodominant epitopes. The extremely potent mAb developed by our laboratory also lost potency against omicron. Here we propose to develop vaccines and monoclonals neutralizing existing and future variants of SARS-CoV-2 and other coronaviruses, by targeting immunologically subdominant regions which are less susceptible to antigenic variation. We will isolate mAbs from individuals who had infection and multiple vaccinations, whose repertoire is enriched in B cells encoding broadly neutralizing antibodies, to build a map of the broadly shared epitopes. Structural prediction and clustering of the immune repertoire through deep neural networks will be used to improve the breadth of coverage of the mAbs. The Monte Carlo-based sequence design of Rosetta and free energy perturbation calculations will be used to in-silico design protein-binding proteins and identify newly designed immunogens which can be loaded on nanoparticles and used as vaccines. This approach will provide broadly protective mAbs and vaccines proactively designed to neutralize all variants of SARS-CoV-2 and new coronaviruses that are very likely to jump from animals to humans in the future. If successful, the approach to map subdominant epitopes and use of genomic and structural information to design mAbs and vaccines targeting subdominant, broadly conserved epitopes, will pave the way to approach other pathogens with high antigenic variability such as influenza and HIV viruses, Plasmodium spp. and antibiotic resistant bacteria. This will strongly increase European competitiveness in fighting infections.

Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2022-ADG

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Host institution

FONDAZIONE TOSCANA LIFE SCIENCES
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 498 750,00
Address
VIA FIORENTINA 1
53100 Siena
Italy

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Region
Centro (IT) Toscana Siena
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 498 750,00

Beneficiaries (1)

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