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Decoding the Language of Nature: It is time for Artificial Intelligence to predict the function of natural products based on structure


Project Description

The profound and specific biological activity of natural products coupled with their immediately recognizable structures suggests a code within these structures that we are not as yet aware of. The long-standing challenge is to be able to decode the functional information entangled in the structures of these metabolites, selected over millions of years by continuous evolution.

Aim
1. The project will address one of chemistry’s grand challenges: to find a function for every metabolite produced by Nature.
2. Develop a method to predict the function of a compound produced by nature by looking at its chemical structure.
3. Use artificial intelligence to build a metabolite-function knowledge base.
4. Use Native mass spectrometry to confirm the identify of protein-ligand complexes

Native mass spectrometry can be used to identify protein-ligand complexes. The technology is robust and relies on non-denaturing electrospray-ionization (ESI) to firstly recognize multi-charged proteins in their near-native states. High resolution, high mass accuracy measurements, coupled with soft ionization techniques to preserve the integrity of complexes, allows for the determination of ligand mass by measuring the mass of the protein and the mass of the intact protein-ligand complex. Native mass spectrometry has been shown to be a powerful tool for fragment-based drug discovery.

Research Plan
The work will involve developing the chemical information that can be applied to a Matrix for AI.
We will address the questions:
• What scaffolds are embedded in bioactive natural products?
• What fragments occur in larger natural products?
• What similarity exists between proteins detected by fragment-based approaches and other target ID methods.
• How can the information be used in AI?

Funding Notes

The 2019 Griffith University Postgraduate Research Scholarship has an annual stipend of $27,596 (indexed) for a period of up to three years of full-time study. Please see View Website for Conditions of Award.

A successful International applicant will also be awarded a Griffith University International Postgraduate Research Scholarship to cover tuition fees for up to three years. Please see View Website for Conditions of Award.

References

Medicinal Chemistry Communications doi: 10.1039/C9MD00128J Title: ‘Is it time for Artificial Intelligence to predict the function of natural products based on 2D-structure’

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