Conformational studies and solvent-accessible surface area analysis of known selective DNA G-Quadruplex binders
Conformational studies and solvent-accessible surface area analysis of known selective DNA G-Quadruplex binders
复制标题
DOI：
10.1016/j.biochi.2011.06.014
复制
发表时间：
2011-08-01
期刊：
影响因子：
3.9
通讯作者：
Parrotta, Lucia
中科院分区：
文献类型：
--
作者：
Alcaro, Stefano;Artese, Anna;Parrotta, Lucia
人类端粒由d（TTAGGG）重复序列组成，参与g -四重体DNA结构的形成。稳定这些g -四重体DNA结构的配体是癌细胞相关酶端粒酶的潜在抑制剂。在人类细胞中，端粒酶在端粒g链末端添加了多个5‘-GGTTAG-3’基序拷贝，在大多数肿瘤细胞中导致过表达。一些结构研究已经揭示了端粒四联体的多样性拓扑结构，正如沉积在蛋白质数据库中的不同构象所证实的那样。近年来，越来越多的端粒酶抑制剂被发现，包括天然的和合成的化合物。因此，端粒酶已被认为是癌症治疗中最具吸引力的靶点之一。在这篇论文中，为了使不同的端粒酶抑制剂的实验活性合理化，我们进行了计算研究，以研究它们的构象性质以及靶亲和力与配体溶剂可及表面积之间的关系。在分析的g -四重体结合物的不同支架中，该描述符为区分末端堆叠配体的结合亲和力提供了有用的初步信息，揭示了其在药物设计和先导物优化过程中的有用预测工具。(C) 2011年Elsevier Masson SAS出版。
Human telomeres are comprised of d(TTAGGG) repeats involved in the formation of G-quadruplex DNA structures. Ligands that stabilize these G-quadruplex DNA structures are potential inhibitors of the cancer cell-associated enzyme telomerase. In human cells, telomerase adds multiple copies of the 5'-GGTTAG-3' motif to the end of the G-strand of the telomere and in the majority of tumor cells it results over-expressed. Several structural studies have revealed a diversity of topologies for telomeric quadruplexes, as confirmed by the different conformations deposited in the Protein Data Bank. In recent years an increasing number of chemically diverse telomerase inhibitors have been identified, including both natural and synthetic compounds. Thus telomerase has been regarded as one of the most attractive targets in cancer treatment. In this manuscript, with the aim to rationalize the different experimental activities of known telomerase inhibitors, a computational study was carried out to investigate their conformational properties and the relationships between the target affinity and the ligands solvent-accessible surface area. Among the analyzed different scaffolds of G-quadruplex binders, such a descriptor provided helpful preliminary information to discriminate end-stacking ligand binding affinities, revealing itself as a useful predictive tool in drug design and lead optimization processes. (C) 2011 Published by Elsevier Masson SAS.