Systematic Profiling and Evaluation of Structure-based Kinase–Inhibitor Interactome in Cervical Cancer by Integrating In Silico Analyses and In Vitro Assays at Molecular and Cellular Levels

Various protein kinases are implicated in the pathogenesis of human cervical cancer and many kinase inhibitors have been used to regulate the activity of protein kinases involved in the disease signaling networks. In the present study, a systematic kinase–inhibitor interactome is created for various small-molecule inhibitors across diverse cervical cancer-related kinases by using ontology enrichment, molecular docking, dynamics simulation and energetics analysis. The interactome profile is examined in detail with heatmap analysis and heuristic clustering to derive promising inhibitors that are highly potential to target the kinome of human cervical cancer in a multi-target manner. A number of hit and unhit inhibitors are selected and their cell-suppressing effects are tested against human cervical carcinoma HeLa, from which several inhibitor compounds with high cytotoxicity are successfully identified. A further kinase assay confirms that these inhibitors can generally target their noncognate kinases HER3 and BRaf in cervical cancer with a high or moderate activity; the activity profile are comparable with or even better than that of cognate kinases inhibitors, with IC₅₀ values ranging between 4.8 and 340.6 nM for HER3 and between 37.2 and 638.2 nM for BRaf. This work would help to identify those unexpected kinase–inhibitor interactions in human cervical cancer and to develop new and efficient therapeutic strategy combating the disease.     

An improved cell membrane chromatography method for the simultaneous screening of two epidermal growth factor receptor antagonists from radix scutellariae

A high‐expression epidermal growth factor receptor cell membrane chromatography using the silica gel with the average particle size of 3 μm as the stationary phase carrier coupled with high‐performance liquid chromatography and mass spectrometry was established for the online screening of epidermal growth factor receptor antagonists from Radix Scutellariae (Huang Qin in Chinese), a traditional Chinese medicine. In this study, the growth factor receptor cell membrane chromatography model using the smaller particle size carrier showed a higher efficiency for simultaneous screening baicalein, another one of the potential epidermal growth factor receptor antagonists from Radix Scutellariae extract besides wogonin, which was found in our previous work. The molecular docking result showed the occupancy site and binding mode of baicalein and wogonin with epidermal growth factor receptor tyrosine kinase were similar to gefitinib. The result of the assay for the in vitro inhibitory activity showed that baicalein and wogonin inhibited the growth of the high‐expression epidermal growth factor receptor cell in a dose‐dependent manner and even achieved a better inhibition effect than gifitinib in the low‐dosage range.     

A Versatile Strategy for Screening Custom-Designed Warhead-Armed Cyclic Peptide Inhibitors

Demand for peptide-based pharmaceuticals has been steadily increasing, but only limited success has been achieved to date. To expedite peptide-based drug discovery, we developed a general scheme for cell-based screening of cyclic peptide inhibitors armed with a user-designed warhead. We combined unnatural amino acid incorporation and split intein-mediated peptide cyclization techniques and integrated a yeast-based colorimetric screening assay to generate a new scheme that we call the custom-designed warhead-armed cyclic peptide screening platform (CWCPS). This strategy successfully discovered a potent inhibitor, CY5-6Q, that targets human histone deacetylase 8 (HDAC8) with a K_D value of 15 nM. This approach can be a versatile and general platform for discovering cyclic peptide inhibitors.     

高通量虚拟筛选CDK2/Cyclin A2靶点抑制剂

CDK2/Cyclin A2复合蛋白的异常表达与乳腺癌、 口腔癌、 食管鳞状细胞癌的发生密切相关. CDK2/ Cyclin A2复合蛋白的活性位点不同于CDK2单体. 至今临床上尚无靶向此复合蛋白的药物分子. 针对CDK2/Cyclin A2复合蛋白, 以实验报道的10个抑制剂分子构建药效团模型, 通过药物体外药代动力学（ADME）、 Docking、 聚类分析、 毒性预测, 从DrugBank, ChEMBL和TCM@Taiwan 3个数据库约90万组数据中进行高通量虚拟筛选, 进一步进行MD模拟、 MM/PBSA结合自由能计算、 能量分解和平均非共价作用(aNCI)分析, 筛选出3个抑制效果优于阳性实验药Roscovitine的先导分子: DrugBank-2004, DrugBank-583和ChEMBL-7122. 与CDK2蛋白相比, CDK2/Cyclin A2复合蛋白结合位点空间变大, 先导分子与Lys33, Asp86, Lys129和Asp145残基之间的排斥作用有所降低, 导致结合自由能更大.     

Sensitive colorimetric assays for α-glucosidase activity and inhibitor screening based on unmodified gold nanoparticles

A colorimetric sensor has been developed in this work to sensitively detect α-glucosidase activity and screen α-glucosidase inhibitors (AGIs) utilizing unmodified gold nanoparticles (AuNPs). The sensing strategy is based on triple-catalytic reaction triggered by α-glucosidase. In the presence of α-glucosidase, aggregation of AuNPs is prohibited due to the oxidation of cysteine to cystine in the system. However, with addition of AGIs, cysteine induced aggregation of AuNPs occurs. Thus, a new method for α-glucosidase activity detection and AGIs screening is developed by measuring the UV–vis absorption or visually distinguishing. A well linear relation is presented in a range of 0.0025–0.05 U mL⁻¹. The detection limit is found to be 0.001 U mL⁻¹ for α-glucosidase assay, which is one order of magnitude lower than other reports. The IC₅₀ values of four kinds of inhibitors observed with this method are in accordance with other reports. The using of unmodified AuNPs in this work avoids the complicated and time-consuming modification procedure. This simple and efficient colorimetric method can also be extended to other enzymes assays.     

Effect of an inhibitor on high-speed turbulent flames and the transition to detonation

The influence of an inhibitor (CF₃Br or Halon 1301) on the propagation of high-speed turbulent flames, quasi-detonations and the transition to detonation has been investigated for methane-air, propane-air and acetylene-air mixtures. The experiments are carried out in a 13 m tube (15 cm diameter) filled with regularly spaced orifice plates (blockage ratio of 0.39) to ensure rapid flame acceleration. In all cases, the addition of the inhibitor reduces the turbulent flame velocity and extinguishes the flame with sufficient inhibitor concentration (2.7% and 7.5% for methane-air and propane-air, respectively). For acetylene-air mixtures, the quasi-detonation speed is progressively reduced with increasing inhibitor concentration and eventually causes the failure of the quasi-detonation and transition back to a fast turbulent flame. The inhibitor also narrows the propagation limits in all cases. To elucidate the inhibition mechanism, detailed modelling of both the turbulent flame structure as well as the chemical kinetics are required.     

Improved Experimental Procedure for the Synthesis of the Potent MEK Inhibitor PD184352

An improved synthesis of the potent MEK inhibitor PD184352 (2-(2-Chloro-4-iodo-phenylamino)-N-cyclopropylmethoxy-3,4-difluoro-benzamide)) is herein reported. This new and reproducible protocol provides a simple and efficient way of generating gram quantities of PD184352 with minimal purification.     

新型多巴胺D3受体抑制剂的发现

根据最新解析的多巴胺D3受体的晶体结构进行活性位点分析,建立了基于受体的药效团模型,并对Asinex Gold Collection数据库进行筛选,选择7个化合物进行生物活性测试,得到了高活性新型多巴胺受体抑制剂(04932482),它对多巴胺D3受体抑制率达85.45％,其Ki值为(806.75±34.58) nmo...     

冠状病毒抑制剂的研究进展

冠状病毒是一类广泛存在且对人及家畜具有严重危害的病原体,其中于2003年全球爆发的严重急性呼吸综合征病毒(SARS-CoV)以及2012年被发现并传播的中东呼吸综合征病毒(MERS-CoV)给人们的生命健康以及全球经济造成了严重威胁以及重大损失,特别是2019年末爆发的新型冠状病毒(SARS-CoV-2),截至目前为止已经造成了几百万的感染病例以及几十万人的死亡。可以看出,冠状病毒具有较高的传播性以及较高的致死率,时刻威胁着人们的健康安全,但是针对冠状病毒的感染目前还没有批准上市的有效药物,也没有用于预防的疫苗。本文围绕目前关于冠状病毒的潜在成药性靶点,详细介绍了针对这些靶点的具有代表性的抑制剂的结构设计及其化学合成方法,以期为目前抗冠状病毒药物的研发提供一些参考。     

Prediction of 5-hydroxytryptamine transporter inhibitors based on machine learning

In patients with depression, the use of 5-HT reuptake inhibitors can improve the condition. Machine learning methods can be used in ligand-based activity prediction processes. In order to predict SERT inhibitors, the SERT inhibitor data from the ChEMBL database was screened and pre-processed. Then 4 machine learning methods (LR, SVM, RF, and KNN) and 4 molecular fingerprints (CDK, Graph, MACCS, and PubChem) were used to build 16 prediction models. The top 5 models of accuracy (Q) in the cross-validation of training set were used to build three different ensemble learning models. In the test1 set, the VOT_CLF3 model had the largest SP (0.871), Q (0.869), AUC (0.919), and MCC (0.728). In the unbalanced test2 set, VOT_CLF3 had the largest SE (0.857), SP (0.867), Q (0.865) and MCC (0.639). VOT_CLF3 was recommended for the virtual screening process of SERT inhibitors. In addition, 12 molecular structural alerts that frequently appear in SERT inhibitors were found (P < 0.05), which provided important reference value for the design work of SERT inhibitors.