Kumar Akhil, Srivastava Gaurava, Sharma Ashok
Biotechnology Division, CSIR-Central Institute of Medicinal and Aromatic Plants, P.O. CIMAP, Lucknow - 226015, U.P., India.
Comput Biol Chem. 2017 Dec;71:1-9. doi: 10.1016/j.compbiolchem.2017.09.001. Epub 2017 Sep 8.
Due to multifactorial nature of Alzheimer's disease one target-one ligand hypothesis often looks insufficient. BACE-1 and GSK-3β are well established therapeutic drug targets and interaction between BACE-1 and GSK-3β pathways has also been established. Thus, designing of dual inhibitor for these two targets seems rational and may provide effective therapeutic strategies against AD. Recent studies revealed that only two scaffolds i.e. triazinone and curcumin act as a dual inhibitor against BACE-1 and GSK-3β. Thus, this discovery set the path to screen new chemical entities from a vast chemical space (∼10 compounds) that inhibit both the targets. However, small part of the large chemical space will only show biological activity for specific targets. Virtual screening of large libraries is impractical and computational expensive especially in case of dual inhibitor design. In the case of dual or multi target inhibitor designing, we screened the database for each target that further increases time and resources. In this study we have done physicochemical descriptor based profiling to know the biological relevant chemical space for BACE-1 and GSK-3β inhibitors and proposed the suitable range of important physicochemical properties, occurrence of functional groups. We generated scaffolds tree of known inhibitors of BACE-1 and GSK-3β suggesting the common structure/fragment that can be used to design dual inhibitors. This approach can filter the potential dual inhibitor candidates of BACE-1 and GSK-3β from non inhibitors.
由于阿尔茨海默病具有多因素性质,单一靶点-单一配体假说往往显得不够充分。β-分泌酶1(BACE-1)和糖原合成酶激酶-3β(GSK-3β)是公认的治疗药物靶点,并且BACE-1与GSK-3β信号通路之间的相互作用也已得到证实。因此,设计针对这两个靶点的双重抑制剂似乎是合理的,并且可能提供针对阿尔茨海默病的有效治疗策略。最近的研究表明,只有三嗪酮和姜黄素这两种骨架作为针对BACE-1和GSK-3β的双重抑制剂。因此,这一发现为从庞大的化学空间(约10种化合物)中筛选抑制这两个靶点的新化学实体铺平了道路。然而,庞大化学空间中的一小部分才会对特定靶点显示出生物活性。对大型文库进行虚拟筛选是不切实际的,而且计算成本高昂,尤其是在设计双重抑制剂的情况下。在设计双重或多靶点抑制剂时,我们针对每个靶点筛选数据库,这进一步增加了时间和资源。在本研究中,我们基于物理化学描述符进行了分析,以了解BACE-1和GSK-3β抑制剂的生物学相关化学空间,并提出了重要物理化学性质的合适范围、官能团的出现情况。我们生成了BACE-1和GSK-3β已知抑制剂的骨架树,表明可用于设计双重抑制剂的共同结构/片段。这种方法可以从非抑制剂中筛选出BACE-1和GSK-3β潜在的双重抑制剂候选物。