药效团
虚拟筛选
李宾斯基五定律
生物信息学
对接(动物)
化学
计算生物学
小分子
配体(生物化学)
车站3
体外
立体化学
生物化学
生物
信号转导
基因
受体
医学
护理部
作者
Kaviarasan Lakshmanan,Praveen Thaggikuppe Krishnamurthy,K. Sreedhara Ranganath Pai,Kalirajan Rajagopal,Gowramma Byran
标识
DOI:10.1080/07391102.2021.1957717
摘要
A large analysis of the signal transducer and activator of transcription (STAT3) in cancer is currently being carried out. It regulates gene expression, which is required for normal cellular functions such as differentiation, cell growth, proliferation, survival, maturation, and immunity. A ligand-based pharmacophore model was created using 3 D QSAR pharmacophore generation methodology in Discovery studio 4.1 clients to imagine structurally diverse novel chemical entities as STAT3 inhibitors with improved efficacy. Chemical properties of 48 different derivatives were included in the training package. Hypo1 was chosen as the query model for screening 1,45,000 drug-like molecules from the SPECS database, with these molecules subjected to the Lipinski rule of 5, Verber's rule, and SMART filtration. After filtration, the molecule was examined further using molecular docking analysis on the active site of STAT3. The binding interaction(s) and pharmacophore mapping were used to select the 19 possible inhibitory molecules. These 19 hits were then tested for toxicity using the TOPKAT software. In MD simulations and MM-PBSA calculations, the tested compound specs 28 provided the best results, suggesting that this ligand has the ability to inhibit more effectively. Based in-silico finding 19 compounds are subjected to in vitro anticancer activity against MDA-MB-231 and MCF-7 cell lines. Based on results compounds specs 11 and specs 13 shows significant activity compared to other compounds and these compounds were subjected to apoptosis assay. The tested compounds induced morphologic changes were dose and time dependent by which all the tested compound exhibits stronger anti-tumor effects.Communicated by Ramaswamy H. Sarma
科研通智能强力驱动
Strongly Powered by AbleSci AI