Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, P.O. Box 17020, Jadavpur University, Kolkata 700032, India.
Department of Chemical Technology, University of Calcutta, 92, APC Ray Road, Kolkata 700009, India.
Eur J Med Chem. 2015 Jan 27;90:860-75. doi: 10.1016/j.ejmech.2014.12.011. Epub 2014 Dec 8.
Tumor suppressor protein p53 regulates the cell cycle and inhibits tumor growth. It is inactivated by mutation or binding with human double minute 2 (HDM2) protein. The HDM2 is a promising target for treatment of p53 protein related cancers. Molecular modeling techniques such as 2D-QSAR, pharmacophore mapping and 3D-QSAR analyses were performed on 155 structurally diverse HDM2 inhibitors to understand structural and physicochemical requirements for higher activity. The linear and spline 2D-QSAR models were developed through multiple linear regression and genetic functional algorithm methods. The 2D-QSAR models suggested that number of fluorine, chlorine, tertiary nitrogen atoms as well as donor feature, stereogenic centers and higher value of solvent accessible surface area are important features in defining activity. Monte Carlo method was applied to generate QSAR models that determined structural indicators (alerts) for increase or decrease of the biological activity. Ligand-based pharmacophore mapping showed importance of two hydrophobic, one hydrophobic aromatic, one ring aromatic and one donor features. The structure-based pharmacophore model demonstrated significance of two hydrophobic, one ring aromatic and two acceptor features. The pharmacophore (ligand) aligned structures were subjected to 3D-QSAR analyses. The structure-based pharmacophore was also used for pharmacophore restraint molecular docking to analyze ligand-receptor interactions and for adjudging predictability as well as validation of different modeling techniques. These comparative molecular modeling techniques may help to design novel HDM2 inhibitors.
抑癌蛋白 p53 调控细胞周期，抑制肿瘤生长。它会因突变或与人类双微体 2（HDM2）蛋白结合而失活。HDM2 是治疗与 p53 蛋白相关癌症的有希望的靶点。采用二维定量构效关系（2D-QSAR）、药效团映射和三维定量构效关系（3D-QSAR）分析等分子建模技术，对 155 种结构多样的 HDM2 抑制剂进行研究，以了解更高活性所需的结构和物理化学要求。通过多元线性回归和遗传功能算法方法开发了线性和样条 2D-QSAR 模型。2D-QSAR 模型表明，氟、氯、叔氮原子的数量以及供体特征、手性中心和更高的溶剂可及表面积值是定义活性的重要特征。应用蒙特卡罗方法生成 QSAR 模型，确定了增加或降低生物活性的结构指标（警报）。基于配体的药效团映射显示了两个疏水性、一个疏水性芳香性、一个环状芳香性和一个供体特征的重要性。基于结构的药效团模型表明了两个疏水性、一个环状芳香性和两个受体特征的重要性。药效团（配体）对齐结构进行了 3D-QSAR 分析。基于结构的药效团也用于药效团约束分子对接，以分析配体-受体相互作用，并判断不同建模技术的可预测性和验证。这些比较分子建模技术可能有助于设计新型 HDM2 抑制剂。
