MAOMAO: An Ontology-Guided FAIR Resource for Harmonized Peptide Toxicity Data

Authors

Soto-Garcia, N., Uribe-Paredes, R., Murgas, L., Orostica, K., Gonzalez-Puelma, J., Navarrete, M., Cadet, F., Medina-Ortiz, D.

Abstract

Peptide toxicity is a critical safety and developability parameter in peptide discovery and therapeutic development, yet relevant information remains fragmented across databases, literature resources, and curated datasets. Here, we present MAOMAO, an ontology-guided FAIR-oriented resource that integrates and harmonizes peptide toxicity data from 54 sources. MAOMAO contains 71,701 unique peptide sequences across seven toxicity-related endpoints, represented as 501,907 sequence endpoint combinations with endpoint-specific evidence states and explicit encoding of unavailable information. The resource combines standardized terminology, a hierarchical toxicity vocabulary, evidence-aware state resolution, provenance-aware metadata, 41 physicochemical descriptors, 10 protein language model representations, and a one-hot baseline. It provides endpoint-specific benchmark partitions across splitting strategies and random seeds, reusable with numerical representations. MAOMAO establishes a reusable framework for peptide toxicity research and data-driven toxicology.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 05 Aug 2026.

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