Research

Thesis title: "Proteome-level identification of mechanism of action (MoA) of natural compounds"

Thesis outline: Understanding the mechanisms of action of drugs requires system-level analytical approaches in addition to computational prediction methods. This project examines the MoA of natural compounds with activity against selected bacterial and fungal pathogens. It builds on prior in vitro phenotypic screening results and aims to provide detailed proteome-wide insights into anti-infective natural compounds.

The research will integrate proteomic, metabolomic, and in silico methodologies, applying advanced chemoproteomic techniques to identify drug targets and binding sites in complex proteomes using limited proteolysis-mass spectrometry (LiP-MS). Key goals include:

1. Predicting MoA by analyzing compound-induced proteome alterations (“proteome signatures”) and integrating these with metabolomic changes.
2. Identifying potential drug binding sites via structurally informative proteolytic fragment analysis.
3. Assessing possible toxicity and off-target effects by comparing data with known host proteomes.

Approach / Methods: The study will employ mass spectrometry-based quantitative proteomics to perform tailored chemoproteomics assays and LiP-MS experiments. Method validation will involve testing established reference drugs for each pathogen. MoA predictions will be derived from network analysis of proteome signatures and cross-referencing with open-access databases containing essential gene and druggability information.

Funding: AIDD-Project

Supervisor: Manuela Schmidt

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