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基于网络药理学、分子模拟和结合自由能计算对新色二孢菌素B的研究揭示了癌症治疗的关键靶点。

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

作者信息

Khan Abbas, Waheed Yasir, Kuttikrishnan Shilpa, Prabhu Kirti S, El-Elimat Tamam, Uddin Shahab, Alali Feras Q, Agouni Abdelali

机构信息

Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha, Qatar.

Office of Research, Innovation, and Commercialization (ORIC), Shaheed Zulfiqar Ali Bhutto Medical University (SZABMU), Islamabad, Pakistan.

出版信息

Front Pharmacol. 2024 Feb 15;15:1352907. doi: 10.3389/fphar.2024.1352907. eCollection 2024.

Abstract

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.

摘要

在本研究中,利用网络药理学、量子极化配体对接、分子模拟和结合自由能计算,对新座壳孢菌素B(NSP-B)的抗癌潜力进行了研究。使用SwissTarget预测和Superpred预测了NSP-B的分子靶点,同时从DisGeNet获得了癌症相关基因。在所有预测的蛋白质中,只有25种被报道与疾病相关基因重叠。利用Cytoscape和STRING数据库构建了蛋白质-蛋白质相互作用网络。使用MCODE检测紧密连接的子网,结果显示有三个子簇。Cytohubba预测了四个靶点,即成纤维细胞生长因子FGF20、FGF22和FGF23作为枢纽基因。基于量子极化对接方法,NSP-B与FGF6、FGF20、FGF22和FGF23进行分子对接,结果显示与关键热点残基有更强的相互作用。此外,分子模拟显示每个复合物具有稳定的动态行为、良好的结构堆积和残基灵活性。还观察到每个复合物中的氢键高于最小值。此外,使用分子力学/广义玻恩表面积(MM/GBSA)和分子力学/泊松-玻尔兹曼表面积(MM/PBSA)方法计算了结合自由能。使用MM/GBSA方法计算的总结合自由能显示,FGF6-NSP-B复合物的值为-36.85千卡/摩尔,FGF20-NSP-B复合物的值为-43.87千卡/摩尔,FGF22-NSP-B复合物的值为-37.42千卡/摩尔,FGF23-NSP-B复合物的值为-41.91千卡/摩尔。使用MM/PBSA方法计算的总结合自由能显示,FGF6-NSP-B复合物的值为-30.05千卡/摩尔,FGF20-NSP-B复合物的值为-39.62千卡/摩尔,FGF22-NSP-B复合物的值为-34.89千卡/摩尔,FGF23-NSP-B复合物的值为-37.18千卡/摩尔。这些发现强调了NSP-B对FGF6、FGF20、FGF22和FGF23具有有前景的潜力,据报道这些因子对癌症信号传导至关重要。这些结果显著支持了NSP-B作为一种有前景的癌症治疗候选药物的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0ad/10905267/0d8c232d4007/fphar-15-1352907-g001.jpg

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