采用基于结构的药效团模型和分子对接方法用于发现新的表皮生长因子受体抑制剂

Using Structure-Based Pharmacophore Model and Molecule Docking Method to Identify New EGFR Inhibitors

表皮生长因子受体与其配体结合后可以诱导细胞的分化与增殖。该受体位于细胞表面,与配体结合后能够活化该受体细胞内的酪氨酸激酶。酪氨酸激酶能够使许多细胞内的底物磷酸化后引起细胞增殖、DNA合成和fos及jun癌基因的表达,所以表皮生长因子受体是肿瘤治疗的潜在靶标。一些表皮生长因子受体抑制剂作为潜在的药物用于肿瘤的治疗。然而,一些上市的药物表现出某些副作用,因而限制了其使用。为了发现改进疗效的新的表皮生长抑制剂,基于表皮生长因子晶体复合物采用DS软件中的受体-配体药效团产生模块,一个高相关性的药效团模型被构建。该药效团模型包括3个氢键受体和1个疏水特征。然后,基于药效团和对接虚拟筛选用于筛选商业数据库,用于获得新的表皮生长抑制剂。最后,具有高对接打分的两个化合物被挑选出来作为新的候选抑制剂。该研究结果的报道,提供了一种基于一组蛋白-配体复合物的晶体结构来产生药效团去用于虚拟筛选的方法,这个研究也认为该方法对于合理的理解结构和理化特性提供了重要的信息。

The epidermal growth factor receptor （EGFR） is a growth factor receptor that induces cell differentiation and proliferation upon activation through the binding of one of its ligands. The receptor is located at the cell surface, where the binding of a ligand activates a tyrosine kinase in the intraeellular region of the receptor. This tyrosine kinase phosphorylates a number of intracellular substrates that activates pathways leading to cell growth, DNA synthesis and the expression of oncogenes such as los and jun. So EGFR has been proposed as a potential target in cancer therapy. Some EGFR inhibitors are now considered as the potential drugs for treatment of cancer diseases. However, some recently marketed inhibitors have shown adverse effects such as nausea and emesis,thus restricting its use. In order to identify novel EGFR inhibitors with improved therapeutic indexes, a highly correlating pharmaeophore model was established on the basis of crystallography structures of EGFR by using Receptor-Ligand Pharmaeophore Genenration Protocol of Discovery Studio （DS） software. The pharmacopbore included three hydrogen bond aeceptors （HBA） and a hydropbobic feature. Then structure-based pharmacophore model and docking-based virtual screening, are used for retrieving new EGFR inhibitors from commercially available chemical databases. Finaly two compounds were selected from the final hits with higest Libscore value. This research results are reported here and had provided an approach to generate a multicomplex-based pharmacophore-guided virtual screening based on a set of crystal structures of protein-ligand complexes, and the multicomplex-based pharmacophore-guided virtual screening can be used for further discovery to design more potent EGFR inhibitors and to evaluate the new compounds in de novo design. The studies also suggest that the multicomplex-based pharmacophore-guided virtual screening could be useful in getting the predictive models which may provide useful information required for proper understanding of the important structural and physico- chemical features.