Project description
Novel mechanistic variant effect predictor to decipher diseases’ molecular drivers
Despite advances in genome sequencing, predicting the consequences of variants remains a challenge. Recent machine learning predictors are able to quantify variants’ clinical pathogenicity, but they cannot reliably predict how mutations impact fitness and drive disease. Supported by the Marie Skłodowska-Curie Actions programme, the mechVEP project aims to address this issue by combining evolutionary-based variant tolerance predictors with protein folding models based on energy landscape theory. Through this approach, it seeks to distinguish between specific function alterations and local stability changes along proteins for single and multiple variants. To do so, it will establish a mechanistic variant effect predictor, integrating folding and evolutionary models into a single algorithm to identify and predict disease-causing mechanisms along the human proteome.
Objective
Genome sequencing has grown exponentially, but determining the phenotypic consequences of mutations remains a key challenge in human genetics. Recently, unsupervised methods, which model the distribution of sequence variation across organisms, have emerged as promising tools for quantifying the clinical pathogenicity of variants, rivaling the accuracy of experimental approaches. However, these machine learning predictors fall short in discerning the effects induced by pathogenic mutations that impact on organismal fitness and drive disease. I propose to address this knowledge gap by combining the evolutionary-based variant tolerance predictors with protein folding models derived from energy landscape theory. In order to fold in biological timescales, an amino acid chain must minimize energy conflicts within it. In natural proteins, remaining conflicts can be measured with a transferable energy function, pointing out regions that did not evolve maintaining foldability, as active or binding sites. Incorporating this approach, I will focus on disentangling the biophysical ambiguity between the alteration of specific functions and local stability changes along proteins, firstly for single variants from which thermodynamic data is available for testing. Furthermore, I will integrate the folding and evolutionary models into a single algorithm to characterize and predict disease-driving mechanisms along the human proteome, a Mechanistic Variant Effect Predictor (mechVEP). Finally, I will apply this pipeline for investigating the epistatic and dominance effects of multiple mutations, paving the way for fine-tuning disease predictors for different ancestries. In summary, findings from this study will provide completely new insight into deciphering the underlying molecular mechanisms driving disease, opening new opportunities for diagnosis and therapy.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences biochemistry biomolecules proteins proteomics
- natural sciences biological sciences genetics mutation
- natural sciences biological sciences genetics genomes
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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.
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-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2024-PF-01
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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.
08003 Barcelona
Spain
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