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Computational Tools for Accelerated NP Discovery
Natural products or specialized metabolites (SMs) remain the most important source of drug leads. However, this potential is far from being exhausted, especially, SMs from understudied sources like marine-derived fungi.
Thus, we build and apply tools to facilitate LCMS/MS-based dereplication/prioritization of SMs as well as AI-tools that accelerate structure elucidation of SMs on the basis of NMR data in international and interdisciplinary collaborations. Please find a current review on AI for Natural Products Research published in Nature Reviews Drug Discovery (free access link)
Abbildung von: Reher et al. "Native metabolomics identifies the rivulariapeptolide family of protease inhibitors"
Recently, we developed a MassQL-Integrated Molecular Networking Approach for the Discovery and Substructure Annotation of Bioactive Cyclic Peptides from the marine sponge-derived fungus Stachylidium bicolor 293 K04.
Resources:
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LC-MS/MS-based molecular networking (GNPS)
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Molecular formula prediction, In-silico/structural database search (SIRIUS/ZODIAC/CSI:FingerID)
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SM Classification (CANOPUS) and MassQL-derived substructure annotation
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SM Structure elucidation via Small Molecule Accurate Recognition Technology (SMART) and DeepSat