ArticleNetwork modeling and analysis in health informatics and bioinformatics2018
A new insight into identification of in silico analysis of natural compounds targeting GPR120.
Article in Network modeling and analysis in health informatics and bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 24 citations in OpenAlex.
- Establishing FDA-approved oncology drugs as GPR176 inhibitor through homology modelling, molecular docking, MMGBSA, DFT, and molecular dynamics simulation.Scientific reports · 2026Article
- Cheminformatics-based screening and evaluation of phytochemicals as CDK2 inhibitors in colorectal cancer therapy.PloS one · 2025Article
- Computational exploration ofBiochemistry and biophysics reports · 2024Article
- OptNCMiner: a deep learning approach for the discovery of natural compounds modulating disease-specific multi-targets.BMC bioinformatics · 2022Article
- GPR120 prevents colorectal adenocarcinoma progression by sustaining the mucosal barrier integrity.Scientific reports · 2022Article
- The molecular mechanism of phytosphingosine binding to FFAR4/GPR120 differs from that of other fatty acids.FEBS open bio · 2021Article
- GPR120/FFAR4 Pharmacology: Focus on Agonists in Type 2 Diabetes Mellitus Drug Discovery.Journal of medicinal chemistry · 2021Article
- Review
- Computational Analysis ofCancer informatics · 2020Article
- Transcriptome profiling reveals Silibinin dose-dependent response network in non-small lung cancer cells.PeerJ · 2020Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
G-protein coupled receptor (GPR120) is an omega-3 fatty acid receptor that inhibits macrophage-induced tissue inflammation. Recent studies revealed GPR120 promotes colorectal carcinoma through modulation of VEGF, IL-8, PGE2, and NF-kB expression. However, three-dimensional structure of GPR120 is not yet available in Protein Data Bank (PDB). In the present study, we focused on a 3-D structural model of GPR120 has been constructed using homology modeling techniques. The structural quality of the predicted GPR120 model was verified using Procheck, Whatif, ProSA, and Verify 3D. After this chemical database of natural compounds have been constructed and screened for its druggability using molinspiration server. Molecular docking studies of natural compounds on GPR120 model revealed that silibinin (- 6.87 kcal/mol), withanolide (- 6.19 kcal/mol), limonene (- 6.17 kcal/mol), and cervical (- 6.15 kcal/mol) have shown good docking interactions with active site residues of the target. Active site residues of Arg280, Asp275, and Gly122 showed hydrogen-bonding interactions with predicted compounds. Based on these in silico findings, we proposed that virtual screening of natural compounds against of GPR120 is a novel approach to find potential anti-colorectal cancer therapeutics.
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