Computer aided de novo design of nanobodies
The project aims to automate the design of fully de novo nanobodies with nanomolar affinity using AI-driven methods, eliminating animal use and enhancing efficiency in antibody development.
Projectdetails
Introduction
Antibodies have become major players in the pharmaceutical industry and were valued at 0.16 billion USD in 2023. Traditionally, antibodies are obtained after immunization of different animals and then produced in relevant cells for use in research, diagnostics, and therapy.
Shift in Public Opinion
In recent years, there is a growing public opinion in Europe to ban the use of animals for biomedical research. Therefore, there is increasing pressure to move from animal-produced antibodies to designing and producing them in vitro.
Advantages of Antibody Engineering
Antibody engineering has another important advantage, which is the possibility of targeting a precise epitope and not relying on serendipity as when injecting an animal with an antigen. In recent years, there have been significant advances in protein design based on the use of artificial intelligence and precise force fields.
Current Industry Practices
Despite this, the majority of the companies that work on antibody design combine rational engineering with massive proprietary screening methods. So far, there are no reported cases of fully de novo design of an antibody with nM affinity against a defined epitope.
Case Study
Using an interleukin receptor as a case study, we have shown that we can indeed fully design de novo a nanobody that recognizes the target with nM affinity, using our proprietary protein design software FoldX and ModelX. Experts consulted to date indicate that the results obtained so far are “truly impressive,” prompting us to continue validating and optimizing our process.
Objectives
Our proposal has two main objectives:
-
To fully automate our pipeline that involves:
- Epitope selection
- Antibody framework selection
- Docking
- Backbone move and side chain search
-
To demonstrate that our optimized pipeline can design fully de novo nanobodies against a defined target in a fast and cost-effective way.
Conclusion
Success in both objectives will open the way to fully de novo antibodies with desired properties and position ourselves in the search for funding and spin-off incorporation.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 150.000 |
Totale projectbegroting | € 150.000 |
Tijdlijn
Startdatum | 1-11-2024 |
Einddatum | 30-4-2026 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- FUNDACIO CENTRE DE REGULACIO GENOMICApenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
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---|---|---|---|---|
Computational design of synthetic antibody repertoires for accelerated therapeutic discoveryCADABRE aims to design and optimize diverse human antibody repertoires with enhanced stability and developability for therapeutic discovery using advanced protein design and AI-driven screening methods. | ERC Advanced... | € 2.741.000 | 2024 | Details |
Learning the interaction rules of antibody-antigen bindingThis project aims to enhance antibody-antigen binding prediction by generating large-scale sequence and structural data through high-throughput screening and machine learning techniques. | ERC Consolid... | € 2.000.000 | 2024 | Details |
Structure and Function-based Design of Vaccine Antigens and Antiviral ImmunotherapiesThis project aims to revolutionize vaccine antigen design by utilizing nanobody screening and deep learning to extract insights from viral glycoproteins, enhancing efficacy against high-risk viruses. | ERC Starting... | € 1.499.525 | 2025 | Details |
PROposing Action to ConTrol and Impede betacoronaVirus EmergenciesDevelop vaccines and monoclonal antibodies targeting subdominant epitopes of SARS-CoV-2 to ensure broad protection against current and future variants, enhancing global pandemic preparedness. | ERC Advanced... | € 2.498.750 | 2023 | Details |
Allosteric modulation of immune checkpoint complexes as a new mode of therapeutic intervention in immunotherapyThe project aims to develop novel Nanobodies as safe and effective modulators of immune checkpoint complexes for cancer and autoimmune diseases, potentially outperforming current therapies. | ERC Advanced... | € 2.499.674 | 2024 | Details |
Computational design of synthetic antibody repertoires for accelerated therapeutic discovery
CADABRE aims to design and optimize diverse human antibody repertoires with enhanced stability and developability for therapeutic discovery using advanced protein design and AI-driven screening methods.
Learning the interaction rules of antibody-antigen binding
This project aims to enhance antibody-antigen binding prediction by generating large-scale sequence and structural data through high-throughput screening and machine learning techniques.
Structure and Function-based Design of Vaccine Antigens and Antiviral Immunotherapies
This project aims to revolutionize vaccine antigen design by utilizing nanobody screening and deep learning to extract insights from viral glycoproteins, enhancing efficacy against high-risk viruses.
PROposing Action to ConTrol and Impede betacoronaVirus Emergencies
Develop vaccines and monoclonal antibodies targeting subdominant epitopes of SARS-CoV-2 to ensure broad protection against current and future variants, enhancing global pandemic preparedness.
Allosteric modulation of immune checkpoint complexes as a new mode of therapeutic intervention in immunotherapy
The project aims to develop novel Nanobodies as safe and effective modulators of immune checkpoint complexes for cancer and autoimmune diseases, potentially outperforming current therapies.
Vergelijkbare projecten uit andere regelingen
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Haalbaarheid van het Formula Y-platform voor versnelde antilichaam ontwikkelingHet project richt zich op het versnellen van de ontwikkeling van nieuwe antilichaamtherapieën door generatieve machine-learning algoritmes te gebruiken voor het ontwerpen van specifieke antilichamen. | Mkb-innovati... | € 20.000 | 2023 | Details |
Accelerated Discovery Nanobody PlatformThe ALADDIN project aims to revolutionize therapeutic antibody discovery for cancer by integrating nanobody technology, AI tools, and innovative models to enhance efficiency and reduce reliance on animal testing. | EIC Pathfinder | € 3.315.441 | 2024 | Details |
Precision control of glycosylation to open a new era of therapeutic antibodiesGlycoBoost aims to revolutionize monoclonal antibody design by producing therapeutics with uniform N-glycans, enhancing safety and efficacy for autoimmune disease treatments. | EIC Transition | € 2.499.540 | 2025 | Details |
InnomABsIPA onderzoekt de haalbaarheid van het ontwikkelen van menselijke eiwitten als alternatief voor antibiotica tegen antimicrobiële resistentie. | Mkb-innovati... | € 14.888 | 2023 | Details |
From A to BCR: B-Cell Receptor Repertoire Profiling for Antibody DevelopmentDit project ontwikkelt een geïntegreerde B-cel repertoire sequentiëringstechnologie om sneller en beter antilichamen te identificeren voor nieuwe geneesmiddelen en therapieën tegen kanker. | Mkb-innovati... | € 153.020 | 2020 | Details |
Haalbaarheid van het Formula Y-platform voor versnelde antilichaam ontwikkeling
Het project richt zich op het versnellen van de ontwikkeling van nieuwe antilichaamtherapieën door generatieve machine-learning algoritmes te gebruiken voor het ontwerpen van specifieke antilichamen.
Accelerated Discovery Nanobody Platform
The ALADDIN project aims to revolutionize therapeutic antibody discovery for cancer by integrating nanobody technology, AI tools, and innovative models to enhance efficiency and reduce reliance on animal testing.
Precision control of glycosylation to open a new era of therapeutic antibodies
GlycoBoost aims to revolutionize monoclonal antibody design by producing therapeutics with uniform N-glycans, enhancing safety and efficacy for autoimmune disease treatments.
InnomABs
IPA onderzoekt de haalbaarheid van het ontwikkelen van menselijke eiwitten als alternatief voor antibiotica tegen antimicrobiële resistentie.
From A to BCR: B-Cell Receptor Repertoire Profiling for Antibody Development
Dit project ontwikkelt een geïntegreerde B-cel repertoire sequentiëringstechnologie om sneller en beter antilichamen te identificeren voor nieuwe geneesmiddelen en therapieën tegen kanker.