Molecular Docking and Network Pharmacology Analysis of Lophenol and Campesterol from Momordica charantia (Bitter gourd) Seeds Targeting HLA-DQ8 in Type 1 Diabetes
Momordica charantia (bitter gourd) seeds have usually used for their antidiabetic effects. The molecular mechanisms original their potential roles in Type 1 diabetes mellitus (T1DM) are not fully unstated. M.Charanita seed extract study aimed to identify phytosterol constituent and where examine poteintial interaction with HLA-DQ8. This important molecule involved in insulin autoantigen production in T1DM. Here we analyzed several bioactive Phytochemicals compounds, including 24(R)-methylcholesterol, lophenol, butyl methyl ketone, olean-12-en-3β-ol, and cis-9-octadecenoic acid. We select two molecule or compound Lophenol and campesterol for molecular docking based study where structural characteristics and potential immunomodulatory relevance. With the help of Autodock VIna Softwere were human HLA-DQ8-insulin B-peptide complex (PDB ID: 1JK8). Lophenol and campesterol compounds were positioned within the peptide-binding groove of the HLA-DQ8 α1/β1 domain, where with binding energies of liphenol is −7.9 kcal/mol and campesterol binding energies is −8.1 kcal/mol. Campesterol interact with hydrophobic , π-alkyl and residues from both HLA-DQ8 chains. No one compound produced hidrogen bond , instead the result or indicate that binding was driven by hydrophobic and van der Waals interactions. Network Pharmacology help to identify the inflammatory pathways and metabolic pathways related with campesterol involve. Were identify inflamotory and metabolic pathways molecules is NF-κB, TNF-α, IL-1β, IL-6, COX-2 and FABP4, NPC1L1. Lophenol has more specific alliance with HLA-DQ8-mediated antigen presentation. Allover these findings help or suggest that M. charantia seed phytosterols, particularly campesterol, may influence T1DM-related immune and metabolic pathways.
Authors
- Mrityunjay Singh
Publication Details
- Journal
- Journal of chemical health risks
- Published
- 2026-10-06
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00