Network pharmacology, molecular simulation, and binding free energy calculation-based investigation of Neosetophomone B revealed key targets for the treatment of cancer

被引:4
|
作者
Khan, Abbas [1 ]
Waheed, Yasir [2 ,3 ]
Kuttikrishnan, Shilpa [4 ]
Prabhu, Kirti S. [4 ]
El-Elimat, Tamam [5 ]
Uddin, Shahab [4 ,6 ]
Alali, Feras Q. [1 ,7 ]
Agouni, Abdelali [1 ]
机构
[1] Qatar Univ, Coll Pharm, Dept Pharmaceut Sci, QU Hlth, Doha, Qatar
[2] Shaheed Zulfiqar Ali Bhutto Med Univ SZABMU, Off Res Innovat & Commercializat ORIC, Islamabad, Pakistan
[3] Lebanese Amer Univ, Gilbert & Rose Marie Chagoury Sch Med, Byblos, Lebanon
[4] Hamad Med Corp, Translat Res Inst, Acad Hlth Syst, Doha, Qatar
[5] Jordan Univ Sci & Technol, Fac Pharm, Dept Med Chem & Pharmacognosy, Irbid, Jordan
[6] Hamad Med Corp, Dermatol Inst, Acad Hlth Syst, Doha, Qatar
[7] Qatar Univ, Off Vice President Med & Hlth Sci, Doha, Qatar
关键词
network pharmacology; protein-protein interactions; hub gene; quantumpolarized ligand docking; molecular simulation; free energy calculation; Neosetophomone B; cancer; AMBER; PERSPECTIVE; STATISTICS; DOCKING; RISK;
D O I
10.3389/fphar.2024.1352907
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
In the current study, Neosetophomone B (NSP-B) was investigated for its anti-cancerous potential using network pharmacology, quantum polarized ligand docking, molecular simulation, and binding free energy calculation. Using SwissTarget prediction, and Superpred, the molecular targets for NSP-B were predicted while cancer-associated genes were obtained from DisGeNet. Among the total predicted proteins, only 25 were reported to overlap with the disease-associated genes. A protein-protein interaction network was constructed by using Cytoscape and STRING databases. MCODE was used to detect the densely connected subnetworks which revealed three sub-clusters. Cytohubba predicted four targets, i.e., fibroblast growth factor , FGF20, FGF22, and FGF23 as hub genes. Molecular docking of NSP-B based on a quantum-polarized docking approach with FGF6, FGF20, FGF22, and FGF23 revealed stronger interactions with the key hotspot residues. Moreover, molecular simulation revealed a stable dynamic behavior, good structural packing, and residues' flexibility of each complex. Hydrogen bonding in each complex was also observed to be above the minimum. In addition, the binding free energy was calculated using the MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) and MM/PBSA (Molecular Mechanics/Poisson-Boltzmann Surface Area) approaches. The total binding free energy calculated using the MM/GBSA approach revealed values of -36.85 kcal/mol for the FGF6-NSP-B complex, -43.87 kcal/mol for the FGF20-NSP-B complex, and -37.42 kcal/mol for the FGF22-NSP-B complex, and -41.91 kcal/mol for the FGF23-NSP-B complex. The total binding free energy calculated using the MM/PBSA approach showed values of -30.05 kcal/mol for the FGF6-NSP-B complex, -39.62 kcal/mol for the FGF20-NSP-B complex, -34.89 kcal/mol for the FGF22-NSP-B complex, and -37.18 kcal/mol for the FGF23-NSP-B complex. These findings underscore the promising potential of NSP-B against FGF6, FGF20, FGF22, and FGF23, which are reported to be essential for cancer signaling. These results significantly bolster the potential of NSP-B as a promising candidate for cancer therapy.
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页数:13
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