Zhu L, Yang Y, Lu X
a Department of Neurosurgery , People's Hospital affiliated to Jiangsu University , Zhenjiang , China.
SAR QSAR Environ Res. 2016;27(1):47-65. doi: 10.1080/1062936X.2015.1132765.
The Rho-associated kinases (ROCKs) have long been recognized as an attractive therapeutic target for various neurological diseases; selective inhibition of ROCK1 and ROCK2 isoforms would result in distinct biological effects on neurogenesis, neuroplasticity and neuroregeneration after brain surgery and traumatic brain injury. However, the discovery and design of isoform-selective inhibitors remain a great challenge due to the high conservation and similarity between the kinase domains of ROCK1 and ROCK2. Here, a structure-based quantitative structure-selectivity relationship (SB-QSSR) approach was used to correlate experimentally measured selectivity with the difference in inhibitor binding to the two kinase isoforms. The resulting regression models were examined rigorously through both internal cross-validation and external blind validation; a nonlinear predictor was found to have high fitting stability and strong generalization ability, which was then employed to perform virtual screening against a structurally diverse, drug-like compound library. Consequently, five and seven hits were identified as promising candidates of 1-o-2 and 2-o-1 selective inhibitors, respectively, from which seven purchasable compounds were tested in vitro using a standard kinase assay protocol to determine their inhibitory activity against and selectivity between ROCK1 and ROCK2. The structural basis, energetic property and biological implication underlying inhibitor selectivity and promiscuity were also investigated systematically using a hybrid quantum mechanics/molecular mechanics (QM/MM) scheme.
Rho相关激酶(ROCKs)长期以来一直被认为是各种神经疾病的一个有吸引力的治疗靶点;选择性抑制ROCK1和ROCK2亚型会对脑手术和创伤性脑损伤后的神经发生、神经可塑性和神经再生产生不同的生物学效应。然而,由于ROCK1和ROCK2激酶结构域之间高度保守和相似,亚型选择性抑制剂的发现和设计仍然是一个巨大的挑战。在此,基于结构的定量结构-选择性关系(SB-QSSR)方法被用于将实验测量的选择性与抑制剂与两种激酶亚型结合的差异相关联。通过内部交叉验证和外部盲法验证对所得回归模型进行了严格检验;发现一个非线性预测器具有高拟合稳定性和强泛化能力,随后用于对一个结构多样的类药物化合物库进行虚拟筛选。因此,分别鉴定出5个和7个命中物作为1-o-2和2-o-1选择性抑制剂的有前景的候选物,使用标准激酶测定方案对其中7个可购买的化合物进行体外测试,以确定它们对ROCK1和ROCK2的抑制活性和选择性。还使用混合量子力学/分子力学(QM/MM)方案系统地研究了抑制剂选择性和混杂性背后的结构基础、能量性质和生物学意义。