Exploring the molecular grammar of IDP assembly and condensation at ultra-high throughput
EMMA aims to revolutionize the understanding of intrinsically disordered proteins by using mRNA display to evaluate the assembly kinetics and thermodynamics of vast sequence libraries.
Projectdetails
Introduction
The last years have seen unprecedented breakthroughs in protein structural biology, with the resolution revolution in cryo-electron microscopy and the release of AlphaFold. The combination of advanced experimental structural biology, machine learning algorithms, and molecular simulations has put the fully quantitative description of how the structure and interactions of folded proteins are defined by their amino acid sequence within close reach.
The Challenge of Intrinsically Disordered Proteins
This leaves us with a final frontier in protein science, namely to achieve a similar level of understanding for intrinsically disordered proteins (IDPs). The energy landscapes of IDPs often comprise a multitude of nearly isoenergetic states that include assembled forms, such as amyloid fibrils and liquid condensate droplets.
Current Understanding and Limitations
Much effort has been spent in order to achieve an understanding of the molecular grammar of IDP assembly and condensation, i.e., how amino acid sequence defines both kinetics and thermodynamics of these processes. Current state of the art is to evaluate a few dozens of sequence perturbations quantitatively in vitro.
Proposed Approach: EMMA
In EMMA, I propose to develop a fundamentally new approach that will ultimately allow us to improve on current methods by more than 8 orders of magnitude. This ground-breaking improvement will be achieved by exploiting the power of mRNA display, in which the biophysical behavior of each individual sequence within large libraries of protein-mRNA constructs can be evaluated in a “one pot” reaction.
Methodology
We will combine quantitative screening of the energetics of liquid condensate droplet formation of up to 10^10 sequences by mRNA display with a multiparametric biophysical toolbox that allows the key thermodynamic and kinetic parameters of binding and assembly to be evaluated for thousands of selected sequence variants.
Impact of EMMA
EMMA will transform our ability to probe the mechanisms and interrelationships of the interactions and assembly processes that define IDP function and disease-related malfunction.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.995.554 |
Totale projectbegroting | € 1.995.554 |
Tijdlijn
Startdatum | 1-6-2023 |
Einddatum | 31-5-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- DANMARKS TEKNISKE UNIVERSITETpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
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Mechanisms of co-translational assembly of multi-protein complexes
This project aims to uncover the mechanisms of co-translational protein complex assembly using advanced techniques to enhance understanding of protein biogenesis and its implications for health and disease.
Integrative, AI-aided Inference of Protein Structure and Dynamics
The project aims to develop bAIes, a novel modeling approach combining AI, experimental data, and molecular simulations to enhance protein structure and dynamics characterization, particularly for SARS-CoV-2.
A new technology to probe molecular interaction in cells at high throughput
The DiffusOMICS project aims to develop a high-throughput fluorescence-based method to map molecular interactions and detect protein aggregates in neurons for improved drug screening.
Deciphering co-translational protein folding, assembly and quality control pathways, in health and disease
This project aims to elucidate co-translational protein folding and degradation mechanisms to understand misfolding diseases and improve therapeutic strategies.
Global Amyloid Mapping: Solving Amyloid Nucleation by Deep Mutagenesis
This project aims to map mutations affecting amyloid nucleation, model transition states, and identify stress-responsive sequences to enhance understanding and treatment of amyloid-related diseases.