ArticleMolecular diversity2025
Computational screening and molecular dynamics of natural compounds targeting the SH2 domain of STAT3: a multitarget approach using network pharmacology.
Article in Molecular diversity, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Computational techniques to study breast cancer scaffolds for antiangiogenesis: a review.Journal of molecular modeling · 2026Review
- Computational screening of Alternaria metabolites as potential DPP-4 inhibitors: ADMET, molecular docking, molecular dynamics, and network pharmacology analysis.Molecular diversity · 2026Article
- Structural insights into natural compound inhibitors of the human metapneumovirus nucleocapsid protein via molecular dynamics and free energy landscape analyses.Scientific reports · 2025Article
- Network Pharmacology-Guided Evaluation of Ginger and Cornelian Cherry Extracts Against Depression and Metabolic Dysfunction in Estrogen-Deficient Chronic Stressed Rats.International journal of molecular sciences · 2025Article
- Screening of antihyperglycemic and cytotoxic properties ofIn silico pharmacology · 2025Article
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6 authors.
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Abstract
SH2 (Src Homology 2) domains play a crucial role in phosphotyrosine-mediated signaling and have emerged as promising drug targets, particularly in cancer therapy. STAT3 (Signal Transducer and Activator of Transcription 3), which contains an SH2 domain, plays a pivotal role in cancer progression and immune evasion because it facilitates the dimerization of STAT3, which is essential for their activation and subsequent nuclear translocation. SH2 domain-mediated STAT3 inhibition disrupts this binding, reduces phosphorylation of STAT3, and impairs dimerization. This study employed an in silico approach to screen potential natural compounds that could target the SH2 domain of STAT3 and inhibit its function. The phytomolecules (182455) were retrieved from the ZINC 15 database and were docked using various modes like HTVS, SP, and XP. The phytomolecules exhibiting higher binding affinity were selected. MM-GBSA was performed to determine binding free energy, and the QikProp tool was utilized to assess the pharmacokinetic properties of potential hit compounds, narrowing down the list of candidates. Molecular dynamics simulations, thermal MM-GBSA, and WaterMap analysis were performed on compounds that exhibited favorable binding affinities and pharmacokinetic characteristics. Based on docking scores and binding interactions, ZINC255200449, ZINC299817570, ZINC31167114, and ZINC67910988 were identified as potential STAT3 inhibitors. ZINC67910988 demonstrated superior stability in molecular dynamics simulation and WaterMap analysis. Furthermore, DFT was performed to determine energetic and electronic properties, and HOMO and LUMO sites were predicted for electronic structure calculation. Additionally, network pharmacology was performed to map the compounds' interactions within biological networks, highlighting their multitarget potential. Compound-target networks elucidate the relationships between compounds and multiple targets, along with their associated pathways and help to minimize off-target effects. The identified lead compound showed strong potential as a STAT3 inhibitor, warranting further validation through in vitro and in vivo studies.
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