药效团
分子动力学
广告
对接(动物)
虚拟筛选
化学
生物信息学
计算生物学
药物发现
分子模型
立体化学
计算化学
生物化学
生物
医学
护理部
基因
体外
作者
Gamal A. Mohamed,Hossam M. Abdallah,Ikhlas A. Sindi,Sabrin R. M. Ibrahim,Abdulrahim A. Alzain
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2024-08-20
卷期号:19 (8): e0308913-e0308913
被引量:2
标识
DOI:10.1371/journal.pone.0308913
摘要
Nuclear receptor binding SET domain protein 2 (NSD2) significantly contributes to the development of cancer, making it a promising target for cancer drug discovery. This research explores natural compounds as potential selective inhibitors for NSD2 in cancer treatment. Employing a comprehensive in silico approach, the study utilized pharmacophore modeling, molecular docking, pharmacokinetic profiling, and molecular dynamics simulations. An e-pharmacophore model-based screening using the first selective and potent ligand bound to NSD2 identified 49,248 natural compounds from the SuperNatural 3.0 database (containing 449,008 molecules) with acceptable alignment with the developed pharmacophore hypotheses. Subsequently, molecular docking was executed to assess the standout compounds which led to the selection of ten candidates that surpassed the reference inhibitor in accordance w the binding affinity expressed as a G score. Ligand-residue interaction analyses of the top three hits (SN0450102, SN0410255, and SN0142336) revealed diverse crucial interactions with the NSD2 active site, including hydrogen bonds, pi-pi stacking, and hydrophobic contacts with key amino acid residues in the NSD2-PWWP1 domain. Pharmacokinetic profiling confirmed the drug-likability for the refined hits, indicating good cellular permeability and minimal blood-brain barrier penetration. Molecular dynamics simulations for 200 nanoseconds affirmed the stability of protein-ligand complexes, with minimal fluctuations in root mean square deviation and root mean square fluctuation analyses. Overall, this study identified promising natural compounds as potential pharmaceutical agents in the treatment of NSD2-associated cancers.
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