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PMconv: How to Compare Proteomes and Metabolomes?

Anna Kozlova¹, Anna Kliuchnikova¹, Arina Gordeeva¹

¹Institute of Biomedical Chemistry, 119121 Moscow, Russia.

International Journal of Molecular Sciences

|June 12, 2026

Summary

PMconv is a new web tool that maps proteomic and metabolomic data, overcoming challenges in multi-omics integration. It helps generate hypotheses by linking molecules and proteins within cellular compartments.

Keywords:

data integration mass-spectrometry multi-omics proteometabolomics

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Area of Science:

Biochemistry
Bioinformatics
Systems Biology

Background:

Integrating proteomic and metabolomic data is complex due to intricate molecular relationships and cellular compartmentalization.
Existing methods struggle to bridge the gap between protein and metabolite datasets effectively.

Purpose of the Study:

To develop a novel web-based application, PMconv, for bidirectional knowledge-based mapping of proteomic and metabolomic datasets.
To facilitate hypothesis generation and feature engineering in multi-omics research by inferring potential biochemical connections.

Main Methods:

PMconv leverages curated associations from the Human Metabolome Database (HMDB) and protein interaction data from STRING.
The application infers biochemical connections between detected molecules and pathway-annotated partners.
It supports interactive network visualization and integrates compartment annotations from the Human Protein Atlas.

Main Results:

PMconv enables the bidirectional mapping of proteomic and metabolomic data, addressing integration challenges.
The tool infers potential biochemical links by integrating protein interaction and metabolite databases.
Spatial contextualization is enhanced through the export of compartment annotations.

Conclusions:

PMconv serves as a valuable exploratory resource for multi-omics research, aiding hypothesis generation.
The application facilitates the understanding of complex molecular interactions within cellular contexts.
Knowledge-derived associations require experimental validation for compartment-specific interpretation.