Di(2-ethylhexyl) phthalate (DEHP), a widely employed exogenous plasticizer, has become pervasive in the environment and living organisms due to its extensive use in food packaging, medical devices, and daily consumer products, and is established as a typical endocrine-disrupting chemical. Growing evidence indicates a strong association between DEHP exposure and the incidence of chronic bone disorders, including osteoporosis (OP), osteoarthritis (OA), and osteonecrosis of the femoral head (ONFH). However, the molecular mechanisms underlying its pathogenic effects across these diseases remain poorly defined. In this study, we applied an environmental network toxicology approach to integrate predicted protein targets of DEHP with known disease-associated targets of the three bone disorders using multiple databases. Through Venn analysis, protein–protein interaction (PPI) network construction, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, we identified core targets and key signaling pathways. Molecular docking and molecular dynamics (MD) simulations were further employed to validate the binding modes and stability between DEHP and the core targets, thereby elucidating common and distinct mechanisms of DEHP across these bone diseases. A total of 109 overlapping targets of DEHP and the three bone diseases were identified, among which 7 core targets—AKT1, SRC, ESR1, CASP3, MMP9, BCL2, and BCL2L1—were common to all three disorders. These are implicated in critical biological processes such as apoptosis regulation, inflammation, extracellular matrix degradation, and estrogen signaling. KEGG enrichment analysis revealed significant involvement of the PI3K-Akt, MAPK, Ras, TNF, and estrogen signaling pathways across all three diseases. Molecular docking and MD simulations confirmed stable binding of DEHP to key targets including AKT1, ESR1, and MMP9, supporting its potential to disrupt bone metabolic homeostasis via multi-target and multi-pathway mechanisms. Further analysis indicated that DEHP exerts both shared and disease-specific effects: it disrupts osteoblast/osteoclast balance in OP, amplifies inflammatory responses and matrix degradation in OA, and contributes to impaired angiogenesis and osteocyte necrosis in ONFH. This study systematically reveals how DEHP disrupts bone homeostasis through a multi-target and multi-pathway network, constructing a cross-disease osteotoxicity framework. It is the first to delineate the common and distinct molecular mechanisms of DEHP in OP, OA, and ONFH. Although these insights are derived from computational models and require further experimental validation, they provide a novel theoretical basis for combined intervention strategies targeting multiple bone diseases and for environmental health risk assessment.

Respiratory syncytial virus (RSV) is a major pathogen responsible for severe lower respiratory tract infections in infants, the elderly, and immunocompromised individuals. Because the RSV F protein mediates viral entry and 15-lipoxygenase (15-LOX) amplifies virus-induced inflammatory responses, dual targeting of these proteins may provide both antiviral and anti-inflammatory benefits. In this study, we combined computational prediction with experimental validation to identify natural dual-target inhibitors from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). A total of 13,131 natural compounds were screened by drug-likeness evaluation, molecular docking, ADME assessment, and molecular dynamics simulations, yielding 31 potential dual-target candidates with favorable drug-like properties. Among them, rhoeadine (MOL001473) maintained stable binding conformations with both targets throughout 100 ns simulations. In BEAS-2B cells, rhoeadine exhibited significant anti-RSV activity (EC50 = 1.82 µM), low cytotoxicity (IC50 = 34.50 µM), and a selectivity index (SI) of 18.97. Time-of-addition experiments suggested that rhoeadine primarily acts at the early stage of viral infection. Additionally, ELISA results indicated that rhoeadine significantly inhibited RSV-induced secretion of CCL5 and IL-6, highlighting its anti-inflammatory potential. In summary, this study identified rhoeadine as a promising natural compound with antiviral and anti-inflammatory activities against RSV. Computational analyses suggested its potential association with RSV F protein and 15-LOX, although direct target-level validation is still required.

Deer Horn Glue is rich in collagen- and tissue-derived proteins, but the link between its experimentally observed proteome, the theoretical peptide sequence space derived from that proteome, and bone-related molecular targets remains poorly defined. This study established a proteomics-guided multiscale computational workflow to prioritize putative receptor activator of nuclear factor-κB ligand (RANKL)-binding peptide candidates generated from proteins identified in one Deer Horn Glue sample. The Deer Horn Glue proteome was characterized by liquid chromatography–tandem mass spectrometry (LC-MS/MS). Experimentally identified proteins were subjected to in silico tryptic digestion and stepwise activity, safety, and physicochemical screening. All 49 retained candidates underwent global and interface-focused docking. Five prioritized peptides were examined by AlphaFold 3, three independently seeded 200 ns molecular dynamics simulations per complex, entropy-omitted molecular mechanics/generalized Born surface area (MM/GBSA) analysis, residue decomposition, and locally relaxed computational alanine substitution analysis. Proteomic analysis retained 707 target protein groups and generated 24,575 nonredundant theoretical peptide sequences. Stepwise screening retained 49 candidates. Global and interface-focused docking rankings showed modest agreement, and the expanded interface analysis identified additional candidates while retaining GASLQDWDFGK as the top-ranked sequence. Across three independent simulations, GASLQDWDFGK showed consistently low peptide root-mean-square deviation (RMSD), whereas HEFSVDMTCEGCSNAVTR formed the largest mean number of interfacial hydrogen bonds. Their entropy-omitted MM/GBSA estimates were generally the most favorable, although the order varied among simulations. Locally relaxed alanine substitutions highlighted reproducible energy-sensitive positions for experimental testing. By linking an experimentally observed Deer Horn Glue proteome to multiscale structural analysis, this workflow provides a traceable and reproducible strategy for prioritizing testable peptide–RANKL interaction hypotheses. The five candidates remain theoretical products of in silico digestion and require targeted detection, direct binding, and functional validation.