An innovative peptide system for novel drugs targeting microbial Repeats-In-Toxin adhesins

Grant number: 899942

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Key facts

  • Disease

    Cholera
  • Start & end year

    2020
    2022
  • Known Financial Commitments (USD)

    $179,805
  • Funder

    European Commission
  • Principal Investigator

    N/A

  • Research Location

    Netherlands
  • Lead Research Institution

    TECHNISCHE UNIVERSITEIT EINDHOVEN
  • Research Priority Alignment

    N/A
  • Research Category

    Therapeutics research, development and implementation

  • Research Subcategory

    Pre-clinical studies

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Despite progress in infection treatment in the last decades, the prevalence and mortality of infections still poses a heavy burden over humankind. The development of antimicrobial resistance and the rapid mutagenesis of bacteria that leads to inefficiency of vaccines, play an important role in maintaining infections high level of threat. Even diseases that have plagued us for centuries, such as cholera, still challenge medical professionals and cause a significant social cost. New therapeutic approaches that promise a higher success rate are a pressing need. We recently discovered a high similarity between an ice-binding protein and the RTX adhesin (FrhA) used by the bacteria of cholera to attach to and infect the human intestine. Moreover, we discovered compounds that bind to FrhA and successfully block it, suggesting these could help prevent cholera's infection. If these can also detach already adhered bacteria, cholera could be effectively removed and cured. In this ERC PoC PEPTOX project, we aim to optimise the synthesis and characterization of the newly discovered compounds and demonstrate blockage of cholera adhesion in an in vitro cellular model.