ArticleFrontiers in pharmacology2024
Network pharmacology, molecular simulation, and binding free energy calculation-based investigation of Neosetophomone B revealed key targets for the treatment of cancer.
Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
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- AI and network biology for rational polypharmacology in signaling drug design: a review.NPJ precision oncology · 2026Review
- Endostemonine I as a Multi-Target Inhibitor of Kaposi's Sarcoma-Associated Herpesvirus Oncogenic Pathways: An Integrative Computational Study.Medical sciences (Basel, Switzerland) · 2026Article
- Ginsenoside F4 inhibits colorectal cancer progression by boosting dendritic cell maturation and remodeling the tumor microenvironment.World journal of gastrointestinal oncology · 2025Article
- Integrative approach to decipher pharmacological mechanism of Cinnamomum zeylanicum essential oil in prostate cancer.Medical oncology (Northwood, London, England) · 2025Article
- Mechanisms of QiShenYiQi in Inhibiting Blood-Brain Barrier Damage Following Stroke: A Network Pharmacology and Experimental Study.Combinatorial chemistry & high throughput screening · 2025Article
- Integrated Analysis of Metatranscriptome and Amplicon Sequencing to Reveal Distinctive Rhizospheric Microorganisms of Salt-Tolerant Rice.Plants (Basel, Switzerland) · 2024Article
- What is the Reason That the Pharmacological Future of Chemotherapeutics in the Treatment of Lung Cancer Could Be Most Closely Related to Nanostructures? Platinum Drugs in Therapy of Non-Small and Small Cell Lung Cancer and Their Unexpected, Possible Interactions. The Review.International journal of nanomedicine · 2024Review
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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.
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