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Predicting protein evolutionary trajectories toward resistance against antiretroviral treatments

Project description

Predicting pathogen evolution

The emergence of drug-resistant mutations poses a formidable challenge in combating pathogens. Selective pressure from pharmacological treatments drives the evolution of pathogen proteins, rendering them impervious to drugs. Current methods, which rely on genotypic resistance analyses, fail to anticipate evolutionary shifts, risking ineffective treatments. Supported by the Marie Skłodowska-Curie Actions (MSCA) programme, the PRERES project pioneers a predictive approach, leveraging molecular evolution and computational biology to forecast the evolution of HIV-1 drug targets and enhance therapy selection. This research offers hope in outmanoeuvring drug resistance, marking a significant leap in molecular evolution studies.

Objective

"Drug resistant mutations can appear when the selective pressure given by a pharmacological treatment causes the evolution of
pathogen proteins towards variants that become unaffected by the drug. Currently, to select therapies against pathogens, genotypic
resistance analyses and tables of resistance mutations are employed to decide the best treatment for the patients. However, these
screenings ignore evolutionary changes that can appear as pathogens adapt, potentially leading to drug resistance. To address this
limitation, the prediction of which variants are more probable to occur in the pathogen population can be useful in selecting ""a priori""
therapies active against those variants before their potential expansion toward reservoirs more inaccessible to drugs. In this proposed
work, I will apply molecular evolution and computational structural biology techniques to evaluate the evolutionary trajectories of
HIV-1 drug targets proteins that lead to resistance against common antiretroviral treatments. I will calculate protein fitness landscapes
based on protein folding stability and activity, also considering binding to inhibitors. Next, I will use evolutionary information from
protein fitness landscapes to improve substitution models of evolution. The evolutionary trajectories predicted by combining
substitution models and fitness landscapes will be validated through comparisons with real data from monitored HIV-1 populations
evolved ""in vitro"" and ""in vivo"". Finally, I will focus on calculating the probability of evolutionary trajectories toward resistance
variants. This research has the potential to improve the selection of therapies for pathogens by providing predictive tools that
consider the evolutionary dynamics of these microorganisms. Furthermore, the results of the project have the potential to be a
breakthrough in the field of molecular evolution as this methodology could also be applied to predict the evolution of other
pathogens."

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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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) HORIZON-MSCA-2023-PF-01

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Coordinator

UNIVERSIDAD DE VIGO
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.

€ 181 152,96
Address
LG CAMPUS LAGOAS MARCOSENDE
36310 VIGO PONTEVEDRA
Spain

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Region
Noroeste Galicia Pontevedra
Activity type
Higher or Secondary Education Establishments
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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.

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