论文部分内容阅读
肿瘤血管生成是肿瘤生长、浸润和转移过程中不可缺少的生物过程,整合素α_vβ_3对肿瘤血管生成起着重要作用。研发具有高亲和力和高特异性的整合素α_vβ_3受体配体在针对肿瘤血管生成进行靶向诊断与靶向治疗中具有重要意义。计算机辅助药物设计技术的问世,极大地推动了新型整合素α_vβ_3受体配体的研发。整合素α_vβ_3受体细胞外区X射线晶体衍射结构的获得为针对整合素α_vβ_3受体的药物设计奠定了基础。计算机辅助药物设计包括基于分子对接法(Docking)的直接药物设计和基于药效团的间接药物设计,Docking可预测配体-蛋白的相互作用、对受体-配体结合进行三维构效关系研究、设计具有高亲和力与选择性的新型配体。通过将小分子数据库与α_vβ_3受体(PDB号为1L5G)进行对接,筛选出具有较高亲和力的α_vβ_3受体拮抗剂-3(3-吡啶基)-3-[4-[2-(5,6,7,8-四氢[1,8]萘啶-2)乙基]吲哚-1]丙酸和3,4-二氯苯基双胍,后者与目前已知的配体具有不同的受体结合模式。在间接药物设计中,提出了以Arg的带正电荷的侧链、Asp的带负电荷的侧链和Gly的疏水基团为药效团特征的三点药效团模型和以氢键供体、氢键受体、芳环作用、疏水作用和负离子中心为特征的药效团模型,筛选出具有nM级及低于nM级亲和力的化合物。近年来,随着计算机技术的飞速发展,预测精确度更高的软件以及更为合理的设计方法,如5D-QSAR及6D-QSAR,正在研究中,这必将使药物设计更为准确、有效。本文对计算机辅助药物设计领域的研究现状和取得的进展进行综述。
Tumor angiogenesis is an indispensable biological process in tumor growth, invasion and metastasis. Integrin α_vβ_3 plays an important role in tumor angiogenesis. The development of integrin αvβ 3 receptor ligands with high affinity and specificity is of great importance in the targeted diagnosis and targeted therapy of tumor angiogenesis. The advent of computer-aided drug design technology, greatly promoted the development of a new integrin α_vβ_3 receptor ligand. Obtaining of the X-ray crystal diffraction structure in the extracellular region of integrin α_vβ_3 receptor lays the foundation for the design of a drug targeting the integrin α_vβ_3 receptor. Computer-aided drug design includes direct drug design based on Docking and pharmacophore-based indirect drug design. Docking predicts ligand-protein interactions and studies the three-dimensional structure-activity relationship of receptor-ligand binding , Designed with high affinity and selectivity of the new ligand. Through the docking of the small molecule database with the α_vβ_3 receptor (PDL No. 1L5G), the α_vβ_3 receptor antagonist-3 (3-pyridyl) -3- [4- [2- (5,6- Tetrahydro [1,8] naphthyridin-2) ethyl] indol-1] propionic acid and 3,4-dichlorophenylbiguanide, which differ from the currently known ligands Receptor binding patterns. In the indirect drug design, a three-point pharmacophore model was proposed that uses the positively charged side chains of Arg, the negatively charged side chains of Asp, and the hydrophobic groups of Gly as the pharmacophore characteristics, , Hydrogen bond acceptor, aromatic ring function, hydrophobic interaction and anion center. The compounds with nM level and lower than nM level were screened out. In recent years, with the rapid development of computer technology, more accurate prediction software and more reasonable design methods, such as 5D-QSAR and 6D-QSAR, are under study, which will surely make drug design more accurate and effective . This article reviews the research status and progress made in the field of computer-aided drug design.