Stepwise development of structure-activity relationship of diverse PARP-1 inhibitors through comparative and validated in silico modeling techniques and molecular dynamics simulation
Stepwise development of structure-activity relationship of diverse PARP-1 inhibitors through comparative and validated in silico modeling techniques and molecular dynamics simulation
复制标题
DOI：
10.1080/07391102.2014.969772
复制
发表时间：
2015-08-03
影响因子：
4.4
通讯作者：
Jha, Tarun
中科院分区：
文献类型：
--
作者：
Halder, Amit K.;Saha, Achintya;Jha, Tarun
聚腺苷二磷酸核糖聚合酶-1(PARP-1)的抑制剂可用于包括癌症在内的各种疾病的治疗。对不同的基于配体的建模技术(2D-QSAR、基于核的偏最小二乘(KPLS)分析、药效团搜索引擎(阶段)药效团映射)和基于结构的(分子对接、MM-GBSA分析、基于对接姿势的基于高斯的3D-QSAR分析)建模技术进行了比较研究，以探索不同组PARP-1抑制剂的构效关系。二维(2D)-QSAR突出了电荷拓扑指数(JGI7)、分数极性表面积(JURS(FPSA3))和连接性指数(CIC2)以及不同分子片段的重要性。在KPLS分析中显示了有利和不利的指纹图谱，而在相基药效团模型中显示了重要的药效团特征(一个受体、一个供体和两个环芳烃)以及有利和不利的场效应。MM-GBSA分析表明，不同的极性、非极性和溶剂化能具有重要意义。基于对接的配基比对被用于进行基于高斯的3D-QSAR研究，进一步证明了不同场效应的重要性。总体而言，研究发现，极性相互作用(氢键、桥式氢键和阳离子)对高活性起主要作用。空间基团增加了总的接触表面积，但它应该具有更高的极性表面积分数来调节溶剂化能。基于结构的药效团图谱发现，配体的正电离特征是区分高活性化合物和非活性化合物的最重要特征。对高活性配体进行的分子动力学模拟描述了蛋白质复合体的动态行为，并支持从其他模拟分析中获得的解释。目前的研究可能对设计PARP-1抑制剂有用。
Inhibitors of poly (ADP-ribose) polymerase-1 (PARP-1) enzyme are useful for the treatment of various diseases including cancer. Comparative in silico studies were performed on different ligand-based (2D-QSAR, Kernel-based partial least square (KPLS) analysis, Pharmacophore Search Engine (PHASE) pharmacophore mapping), and structure-based (molecular docking, MM-GBSA analyses, Gaussian-based 3D-QSAR analyses on docked poses) modeling techniques to explore the structure-activity relationship of a diverse set of PARP-1 inhibitors. Two-dimensional (2D)-QSAR highlighted the importance of charge topological index (JGI7), fractional polar surface area (Jurs(FPSA3)), and connectivity index (CIC2) along with different molecular fragments. Favorable and unfavorable fingerprints were demonstrated in KPLS analysis, whereas important pharmacophore features (one acceptor, one donor, and two ring aromatic) along with favorable and unfavorable field effects were demonstrated in PHASE-based pharmacophore model. MM-GBSA analyses revealed significance of different polar, non-polar, and solvation energies. Docking-based alignment of ligands was used to perform Gaussian-based 3D-QSAR study that further demonstrated importance of different field effects. Overall, it was found that polar interactions (hydrogen bonding, bridged hydrogen bonding, and pi-cation) play major roles for higher activity. Steric groups increase the total contact surface area but it should have higher fractional polar surface area to adjust solvation energy. Structure-based pharmacophore mapping spotted the positive ionizable feature of ligands as the most important feature for discriminating highly active compounds from inactives. Molecular dynamics simulation, conducted on highly active ligands, described the dynamic behaviors of the protein complexes and supported the interpretations obtained from other modeling analyses. The current study may be useful for designing PARP-1 inhibitors.