Key findings

• Large-scale screening: 13,381 fungal-derived natural products were screened from the NPAtlas database.

• Reference compound: Acrivastine was used as the control ligand.

• Prioritized candidates: CID: 145975830 and CID: 145976597 showed promising predicted docking profiles, with scores of −13.654 and −13.997 kcal/mol, respectively, compared with −9.071 kcal/mol for acrivastine.

• Integrated evaluation: The candidates were further assessed through ADMET, SAR, DFT, MD simulation, MM/GBSA and DCCM analyses.

• Dynamic assessment: 100 ns MD simulations provided additional insights into the dynamic behaviour and interaction patterns of the prioritized complexes.

• Overall prioritization: CID: 145975830 demonstrated the most consistent computational profile across the evaluated analyses.

Why does this study matter?

This study highlights fungal natural products as a potentially valuable chemical space for exploring H1R ligand candidates. It also demonstrates how complementary computational approaches can support the systematic prioritization of natural products for further pharmacological investigation.

The next important step is experimental validation, including receptor-binding studies and functional assays to determine whether these computationally prioritized candidates demonstrate H1R antagonistic activity.

Read the full open-access article:

https://doi.org/10.1038/s41598-026-75139-2

Published in Scientific Reports (2026).

I welcome discussions, suggestions and collaborations from researchers working in natural-product chemistry, computational pharmacology, GPCR biology and allergy research.