Computational prioritization of fungal-derived H1 receptor ligand candidates for allergy-related research

Activation of the G-protein-coupled histamine H1 receptor (H1R) contributes to allergic responses such as bronchoconstriction, vasodilation, and pruritus. This study aimed to computationally prioritize novel fungal-derived compounds for H1R-targeted investigation based on predicted binding characteristics, pharmacokinetic and toxicity profiles, and BBB permeability. A comprehensive workflow incorporating SP and XP molecular docking, ADMET, SAR, DFT, molecular dynamics (MD) simulation, MM/GBSA, and Dynamic Cross-Correlation Matrix (DCCM) analyses was employed. A total of 13,381 fungal-derived natural products from the NPAtlas database were screened using acrivastine as the control. The top ten docking-ranked compounds were further evaluated by ADMET analysis, leading to the prioritization of CID:145,975,830 and CID:145,976,597, which showed docking scores of − 13.654 and − 13.997 kcal/mol, respectively, compared with − 9.071 kcal/mol for the control. Post-docking and post-simulation MM/GBSA analyses provided complementary binding free-energy estimates for the prioritized complexes. PASS prediction associated the leads with anti-eczematic, antipruritic, and vasoprotective activities, while DFT analysis revealed broadly comparable electronic profiles. The 100 ns MD simulations showed differences in dynamic behavior and residue-level interaction persistence, while DCCM analysis indicated differences in correlated residue motions. Overall, CID:145,975,830 exhibited the most consistent computational profile and was prioritized as a candidate for further H1R investigation. Experimental validation is required to establish H1R binding, antagonistic activity, and therapeutic potential.