Summary
Multidrug resistant (MDR) bacteria represent a global public health threat against which new drugs are urgently needed. Antimicrobial peptides (AMPs), mostly derived from naturally occurring linear or cyclic peptides, can contribute to solving the problem. AMPs are already in clinical use, do not easily lead to resistance, and can rely on a strong manufacturing sector and established protocols for clinical development. However, most AMPs are degraded by proteases and have poor pharmacokinetics.
SPACE4AMPS aims to identify new AMPs with diverse peptide chain topologies and building blocks and with the following characteristics: i) Broad activity spectrum, ii) High activity, iii) Low probability for induced resistance, iv) Low proteolysis, v) Better pharmacokinetics.
To reach its goal SPACE4AMPS will create computational tools to explore the extremely vast chemical space of large molecules such as peptides and natural products, which now lies within reach of the latest computer hardware developments.
To better understand antimicrobial drugs, we will design a molecular fingerprint relating antimicrobial activity to molecular structure and use it to draw a tree-map of the antimicrobial chemical space. We will enrich this map with new compounds from generative models using neural networks.
To identify new AMPs, we will use a genetic algorithm carrying out cycles of molecule generation and similarity calculations to select cyclic peptides and peptide dendrimers including lipidated, peptoid (N-alkyl glycines) and N-methylated residues, synthesize and test these molecules against MDR bacteria, fungi and parasites, screen actives for toxicity, and study their structure and mode of action.
By its ground-breaking and unprecedented computational/synthetic/biological approach, SPACE4AMPS can help solve the antibiotics crisis, revolutionize knowledge on antimicrobial compounds, and create new methods enabling computer-aided drug discovery for large molecules.
SPACE4AMPS aims to identify new AMPs with diverse peptide chain topologies and building blocks and with the following characteristics: i) Broad activity spectrum, ii) High activity, iii) Low probability for induced resistance, iv) Low proteolysis, v) Better pharmacokinetics.
To reach its goal SPACE4AMPS will create computational tools to explore the extremely vast chemical space of large molecules such as peptides and natural products, which now lies within reach of the latest computer hardware developments.
To better understand antimicrobial drugs, we will design a molecular fingerprint relating antimicrobial activity to molecular structure and use it to draw a tree-map of the antimicrobial chemical space. We will enrich this map with new compounds from generative models using neural networks.
To identify new AMPs, we will use a genetic algorithm carrying out cycles of molecule generation and similarity calculations to select cyclic peptides and peptide dendrimers including lipidated, peptoid (N-alkyl glycines) and N-methylated residues, synthesize and test these molecules against MDR bacteria, fungi and parasites, screen actives for toxicity, and study their structure and mode of action.
By its ground-breaking and unprecedented computational/synthetic/biological approach, SPACE4AMPS can help solve the antibiotics crisis, revolutionize knowledge on antimicrobial compounds, and create new methods enabling computer-aided drug discovery for large molecules.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/885076 |
| Start date: | 01-01-2021 |
| End date: | 31-12-2025 |
| Total budget - Public funding: | 2 495 285,00 Euro - 2 495 285,00 Euro |
Cordis data
Original description
Multidrug resistant (MDR) bacteria represent a global public health threat against which new drugs are urgently needed. Antimicrobial peptides (AMPs), mostly derived from naturally occurring linear or cyclic peptides, can contribute to solving the problem. AMPs are already in clinical use, do not easily lead to resistance, and can rely on a strong manufacturing sector and established protocols for clinical development. However, most AMPs are degraded by proteases and have poor pharmacokinetics.SPACE4AMPS aims to identify new AMPs with diverse peptide chain topologies and building blocks and with the following characteristics: i) Broad activity spectrum, ii) High activity, iii) Low probability for induced resistance, iv) Low proteolysis, v) Better pharmacokinetics.
To reach its goal SPACE4AMPS will create computational tools to explore the extremely vast chemical space of large molecules such as peptides and natural products, which now lies within reach of the latest computer hardware developments.
To better understand antimicrobial drugs, we will design a molecular fingerprint relating antimicrobial activity to molecular structure and use it to draw a tree-map of the antimicrobial chemical space. We will enrich this map with new compounds from generative models using neural networks.
To identify new AMPs, we will use a genetic algorithm carrying out cycles of molecule generation and similarity calculations to select cyclic peptides and peptide dendrimers including lipidated, peptoid (N-alkyl glycines) and N-methylated residues, synthesize and test these molecules against MDR bacteria, fungi and parasites, screen actives for toxicity, and study their structure and mode of action.
By its ground-breaking and unprecedented computational/synthetic/biological approach, SPACE4AMPS can help solve the antibiotics crisis, revolutionize knowledge on antimicrobial compounds, and create new methods enabling computer-aided drug discovery for large molecules.
Status
SIGNEDCall topic
ERC-2019-ADGUpdate Date
27-04-2024
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