Discovery of Potential Natural STAT3 Inhibitors: An in silico Molecular Docking and Molecular Dynamics Study

分子动力学 化学 对接(动物) 立体化学 氢键 虚拟筛选 生物信息学 生物化学 生物物理学 计算化学 生物 分子 医学 基因 护理部 有机化学
作者
Sameena Gul,Shabbir Muhammad,Muhammad Irfan,Tareg M. Belali,Aijaz Rasool Chaudhry,Muhammad Noman Khan
出处
期刊:Journal of computational biophysics and chemistry [World Scientific]
卷期号:23 (02): 189-205 被引量:4
标识
DOI:10.1142/s2737416523500588
摘要

Cancer is a mechanistically complex and diverse disease with a plethora of fundamental genetic and epigenetic factors. Signal transducer and activator of transcription-3 (STAT3) is a transcription factor, and its constitutive activation executes promotion of cellular proliferation, cell cycle, angiogenesis, metastasis, immunosuppression, and chemo-resistance in cancer cells. Here, we aimed to design natural potential STAT3 inhibitors. For this purpose, we investigated 92 phytochemical compounds by molecular docking studies because they are diversified, multitargeted, affordable, easily available, and less- or non-toxic. We selected only 6 compounds such as sarsasapogenin (L3), peiminine (L9), solasodine (L10), tormentic acid (L23), obacunone (L29), and echinocystic acid (L34) due to their greater binding affinity than reference STAT3 inhibitor (S3I-201) with STAT3. The study was further continued by molecular dynamic (MD) simulations and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The results of molecular docking showed that all selected ligands exhibited binding affinity range from -9.3 Kcal/mol to -7.9 Kcal/mol and predicted inhibition constant ([Formula: see text].) values range from 0.14 [Formula: see text]M to 1.5 [Formula: see text]M. These compounds showed effective hydrogen bonding and hydrophobic interactions with DNA binding domain as well as SH2-domain of STAT3. The MD simulations performed by nanoscale molecular dynamics (NAMD) calculated root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration ([Formula: see text]), solvent accessible surface area (SASA) and number of hydrogen bond dynamics. All selected ligands with protein exhibited stability over 120 ns by MD simulation. Moreover, these ligands showed favorable ADMET profiling and drug likeness. So, our current computational investigations showed that these novel drug candidates can be potential STAT3 inhibitors and evoke the scientific interest for their further verification by in vitro and in vivo studies.
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