Construction of the Pharmacophore Model of Glycogen Synthase Kinase-3 Inhibitors

A three dimensional pharmacophore model has been generated for glycogen synthase kinase-3 （GSK-3） inhibitots. A dataset consisting of 89 compounds was selected on the basis of the information content of the structures and activity data as required by the CATALYST system. The optimum model with four features （one hydrogen-bond acceptor unit, one ring aromatic unit, and two hydrophobic aromatic units） was selected with a good correlation coefficient （0.95）. This model is able to predict the activity of other known GSK-3 inhibitors not included in the model generation, and can be further used to identify structurally diverse compounds with desired biological activity by virtual screening.     

Design,Synthesis, Molecular Modeling and Antitumor Evaluation of Novel Indolyl-Pyrimidine Derivatives with EGFR Inhibitory Activity

Scaffolds hybridization is a well-known drug design strategy for antitumor agents. Herein, series of novel indolyl-pyrimidine hybrids were synthesized and evaluated in vitro and in vivo for their antitumor activity. The in vitro antiproliferative activity of all compounds was obtained against MCF-7, HepG2, and HCT-116 cancer cell lines, as well as against WI38 normal cells using the resazurin assay. Compounds 1–4 showed broad spectrum cytotoxic activity against all these cancer cell lines compared to normal cells. Compound 4g showed potent antiproliferative activity against these cell lines (IC₅₀ = 5.1, 5.02, and 6.6 μM, respectively) comparable to the standard treatment (5-FU and erlotinib). In addition, the most promising group of compounds was further evaluated for their in vivo antitumor efficacy against EAC tumor bearing mice. Notably, compound 4g showed the most potent in vivo antitumor activity. The most active compounds were evaluated for their EGFR inhibitory (range 53–79%) activity. Compound 4g was found to be the most active compound against EGFR (IC₅₀ = 0.25 µM) showing equipotency as the reference treatment (erlotinib). Molecular modeling study was performed on compound 4g revealed a proper binding of this compound inside the EGFR active site comparable to erlotinib. The data suggest that compound 4g could be used as a potential anticancer agent.     

吲哚与亚胺的Friedel-Crafts反应的研究进展

由于吲哚类化合物具有许多生物特性等优点,在众多天然产物和相应的具有生物活性的化合物中起重要的骨架构筑作用,其合成方法的研究格外令人注目.近年来,关于吲哚与亚胺在催化剂作用下发生Friedel-Crafts反应来制备3-取代吲哚甲胺衍生物的报道剧增.对近年来吲哚与亚胺Friedel-Crafts反应的研究情况进行了综述.     

Synthesis and Antiproliferative Activity against Cancer Cells of Indole-Aryl-Amide Derivatives

Indoles constitute a large family of heterocyclic compounds widely occurring in nature which are present in a number of bioactive natural and synthetic compounds, including anticancer agents or atypical opioid agonists. As a result, exponential increases in the development of novel methods for the synthesis of indole-containing compounds have been reported in the literature. A series of indole-aryl amide derivatives 1–7 containing tryptamine or an indolylacetic acid nucleus were designed, synthesized, and evaluated as opioid ligands. These new indole derivatives showed negligible to very low affinity for μ- and δ-opioid receptor (OR). On the other hand, compounds 2, 5 and 7 showed Ki values in the low μM range for κ-OR. Since indoles are well known for their anticancer potential, their effect against a panel of tumor cell lines was tested. The target compounds were evaluated for their in vitro cytotoxicity in HT29, HeLa, IGROV-1, MCF7, PC-3, and Jurkat J6 cells. Some of the synthesized compounds showed good activity against the selected tumor cell lines, with the exception of IGROV1. In particular, compound 5 showed a noteworthy selectivity towards HT29 cells, a malignant colonic cell line, without affecting healthy human intestinal cells. Further studies revealed that 5 caused the cell cycle arrest in the G1 phase and promoted apoptosis in HT29 cells.     

先导化合物的发现——整合计算机虚拟筛选、化学合成和生物测试方法

先导化合物的发现在药物研究中起关键作用。基于分子对接的虚拟筛选是创新药物研究的新方法和新技术,已成为一种与高通量筛选互补的方法,广泛应用于先导化合物的发现中。本文将结合本课题组的研究实例,综述了通过计算机虚拟筛选、化学合成和生物测试相结合的方法来发现先导化合物的一些研究工作。     

含吲哚的吡唑并[3,4-d]嘧啶衍生物的设计合成及其生物活性研究

利用药物设计中的生物活性基团拼接原理,设计合成了13个含吲哚的吡唑并[3,4-d]嘧啶衍生物.目标化合物均经核磁共振氢谱(1H NMR)、核磁共振碳谱(13C NMR)和高分辨质谱仪(HRMS)进行了结构确证.对4株肿瘤细胞(HeLa、MGC-803、MCF-7、BEL-7404)的体外抗增殖活性实验结果表明,目标化合物均表现出一定的抗肿瘤活性,MCF-7、MGC-803肿瘤细胞株敏感度高于HeLa和BEL-7404.其中, 6-[(6-甲氧羰基吲哚-3-基)硫基]-1-苯基-吡唑并[3,4-d]嘧啶-4-酮(5m)表现出较好的体外肿瘤抑制活性,对MCF-7、MGC-80和HeLa细胞的IC50均小于30μmol·L^-1,对MCF-7的IC50值为(4.02±0.92)μmol·L^-1,优于对照药物依托泊苷(10.1±0.62μmol·L^-1)和羟喜树碱(5.93±0.56μmol·L^-1).拓扑异构酶抑制实验结果表明,此类化合物对TopoII有选择性抑制活性,所有化合物对TopoⅡ表现出不同程度抑制活性,对Topo Ⅰ未表现出抑制活性.     

Virtual Screening with Gnina 1.0

Virtual screening—predicting which compounds within a specified compound library bind to a target molecule, typically a protein—is a fundamental task in the field of drug discovery. Doing virtual screening well provides tangible practical benefits, including reduced drug development costs, faster time to therapeutic viability, and fewer unforeseen side effects. As with most applied computational tasks, the algorithms currently used to perform virtual screening feature inherent tradeoffs between speed and accuracy. Furthermore, even theoretically rigorous, computationally intensive methods may fail to account for important effects relevant to whether a given compound will ultimately be usable as a drug. Here we investigate the virtual screening performance of the recently released Gnina molecular docking software, which uses deep convolutional networks to score protein-ligand structures. We find, on average, that Gnina outperforms conventional empirical scoring. The default scoring in Gnina outperforms the empirical AutoDock Vina scoring function on 89 of the 117 targets of the DUD-E and LIT-PCBA virtual screening benchmarks with a median 1% early enrichment factor that is more than twice that of Vina. However, we also find that issues of bias linger in these sets, even when not used directly to train models, and this bias obfuscates to what extent machine learning models are achieving their performance through a sophisticated interpretation of molecular interactions versus fitting to non-informative simplistic property distributions.     

Design,Synthesis, Molecular Docking,and Tumor Resistance Reversal Activity Evaluation of Matrine Derivative with Thiophene Structure

Nasopharyngeal carcinoma (NPC) frequently occurs in Southern China. The main treatments of NPC are chemotherapy and radiotherapy. However, chemo-resistance arises as a big obstacle in treating NPC. Therefore, there is a great need to develop new compounds that could reverse tumor drug resistance. In this study, eight matrine derivatives containing thiophene group were designed and synthesized. Structures of these 8 compounds were characterized by ¹H-NMR, ¹³C-NMR, and high-resolution mass spectrometer (HRMS). The cytotoxicity and preliminary synergistic effects of these 8 compounds were detected against nasopharyngeal carcinoma (NPC) cells and cisplatin-resistant NPC cells (CNE2/CDDP), respectively. Furthermore, the in vivo and in vitro tumor resistance reversal effects of compound 3f were evaluated. Moreover, docking studies were performed in Bclw (2Y6W). The results displayed that compound 3f showed synergistic inhibitory effects with cisplatin against CNE2/CDDP cells proliferation via apoptosis induction. Docking results revealed that compound 3f may exert its effects via inhibiting anti-apoptosis protein Bcl-w.     

糖原合成激酶-3β马来酰胺类抑制剂构效关系的理论研究

建立糖原合成激酶-3β(GSK-3β)抑制剂的三维构效关系,可预测新的糖原合成激酶-3β抑制剂.通过确定分子的药效构象,与选定的模板分子进行叠合,采用比较分子力场分析法(Co MFA)和比较分子相似性指数分析法(Co MSIA)分别建立38个糖原合成激酶-3β抑制剂的3D-QSAR模型.比较分子力场分析法所建立的模型的决定系数q2=0.711,非交叉验证系数r2=0.887,标准偏差ES=0.411,显著系数F=109.856;比较分子相似性指数分析法所建立模型的决定系数q2=0.605,非交叉验证系数r2=0.931,标准偏差ES=0.326,显著系数F=122.122.该模型在一定程度上反映了结合部位的性质要求,解释马来酰胺类抑制剂的构效关系,具有较好的预测能力.     

新型沙美特罗衍生物的合成

以沙美特罗的缩酮保护产物为原料,经长链仲氨的叔丁氧羰基保护、分子内酯交换反应选择性保护氨基间位的苄羟基、脱缩酮保护、与昔萘酸甲酯的Friedel-Crafts反应后再经碱水解合成了一个新型的沙美特罗衍生物——1-羟基-4-【2-羟基-5-【1-羟基-2-{[6-(4-苯丁氧基)]己氨基}乙基】苯甲基】-2-萘甲酸,总收率16.3%,其结构经1H NMR和MS表征。     

An Unusual Intramolecular Halogen Bond Guides Conformational Selection

PIK‐75 is a phosphoinositide‐3‐kinase (PI3K) α‐isoform‐selective inhibitor with high potency. Although published structure–activity relationship data show the importance of the NO₂ and the Br substituents in PIK‐75, none of the published studies could correctly determine the underlying reason for their importance. In this publication, we report the first X‐ray crystal structure of PIK‐75 in complex with the kinase GSK‐3β. The structure shows an unusual U‐shaped conformation of PIK‐75 within the active site of GSK‐3β that is likely stabilized by an atypical intramolecular Br???NO₂ halogen bond. NMR and MD simulations show that this conformation presumably also exists in solution and leads to a binding‐competent preorganization of the PIK‐75 molecule, thus explaining its high potency. We therefore suggest that the site‐specific incorporation of halogen bonds could be generally used to design conformationally restricted bioactive substances with increased potencies.     

Critical evaluation of search algorithms for automated molecular docking and database screening

The DOCK program explores possible orientations of a molecule within a macromolecular active site by superimposing atoms onto precomputed site points. Here we compare a number of different search methods, including an exhaustive matching algorithm based on a single docking graph. We evaluate the performance of each method by screening a small database of molecules to a variety of macromolecular targets. By varying the amount of sampling, we can monitor the time convergence of scores and rankings. We not only show that the site point–directed search is tenfold faster than a random search, but that the single graph matching algorithm boosts the speed of database screening up to 60-fold. The new algorithm, in fact, outperforms the bipartite graph matching algorithm currently used in DOCK. The results indicate that a critical issue for rapid database screening is the extent to which a search method biases run time toward the highest-ranking molecules. The single docking graph matching algorithm will be incorporated into DOCK version 4.0. © 1997 John Wiley & Sons, Inc. J Comput Chem 18: 1175–1189     

Computer-Aided Drug Design Boosts RAS Inhibitor Discovery

The Rat Sarcoma (RAS) family (NRAS, HRAS, and KRAS) is endowed with GTPase activity to regulate various signaling pathways in ubiquitous animal cells. As proto-oncogenes, RAS mutations can maintain activation, leading to the growth and proliferation of abnormal cells and the development of a variety of human cancers. For the fight against tumors, the discovery of RAS-targeted drugs is of high significance. On the one hand, the structural properties of the RAS protein make it difficult to find inhibitors specifically targeted to it. On the other hand, targeting other molecules in the RAS signaling pathway often leads to severe tissue toxicities due to the lack of disease specificity. However, computer-aided drug design (CADD) can help solve the above problems. As an interdisciplinary approach that combines computational biology with medicinal chemistry, CADD has brought a variety of advances and numerous benefits to drug design, such as the rapid identification of new targets and discovery of new drugs. Based on an overview of RAS features and the history of inhibitor discovery, this review provides insight into the application of mainstream CADD methods to RAS drug design.     

α-咔啉类GSK-3β抑制剂的合成、活性评价和分子对接研究

糖原合成酶激酶3β(GSK-3β)是神经退化性疾病如早老性痴呆、II型糖尿病、癌症等多种重复杂性疾病的药物靶标,α-咔啉类化合物具有多种生物活性.以GSK-3β为作用靶点,利用Graebe-Ullmann反应合成了α-咔啉,并采用Buchwald-Hartwig偶联反应合成了9个4位取代的α-咔啉胺类衍生物.体外的GSK-3β激酶酶抑制活性测试表明其中4个化合物具有一定的抑制活性,其中化合物3c的IC50值达到了5.1μmol L-1.同时采用了分子对接方法分别研究了化合物2,3c与大分子蛋白的作用模式,初步探讨了影响抑制活性的原因,为进一步的研究提供了依据.     

新型吲哚抗癌试剂的设计与合成

以邻碘苯胺和苯乙炔为原料,经10步反应合成了2,3-二取代的新型吲哚抗癌试剂,总收率33%~37%,其结构经1H NMR和MS表征。     

Bridging the Gap in Malaria Parasite Resistance,Current Interventions,and the Way Forward from in Silico Perspective: A Review

The past decade has seen most antimalarial drugs lose their clinical potency stemming from parasite resistance. Despite immense efforts by researchers to mitigate this global scourge, a breakthrough is yet to be achieved, as most current malaria chemotherapies suffer the same fate. Though the etiology of parasite resistance is not well understood, the parasite’s complex life has been implicated. A drug-combination therapy with artemisinin as the central drug, artemisinin-based combination therapy (ACT), is currently the preferred malaria chemotherapy in most endemic zones. The emerging concern of parasite resistance to artemisinin, however, has compromised this treatment paradigm. Membrane-bound Ca²⁺-transporting ATPase and endocytosis pathway protein, Kelch13, among others, are identified as drivers in plasmodium parasite resistance to artemisinin. To mitigate parasite resistance to current chemotherapy, computer-aided drug design (CADD) techniques have been employed in the discovery of novel drug targets and the development of small molecule inhibitors to provide an intriguing alternative for malaria treatment. The evolution of plasmepsins, a class of aspartyl acid proteases, has gained tremendous attention in drug discovery, especially the non-food vacuole. They are expressed at multi-stage of the parasite’s life cycle and involve in hepatocytes’ egress, invasion, and dissemination of the parasite within the human host, further highlighting their essentiality. In silico exploration of non-food vacuole plasmepsin, PMIX and PMX unearthed the dual enzymatic inhibitory mechanism of the WM382 and 49c, novel plasmepsin inhibitors presently spearheading the search for potent antimalarial. These inhibitors impose structural compactness on the protease, distorting the characteristic twist motion. Pharmacophore modeling and structure activity of these compounds led to the generation of hits with better affinity and inhibitory prowess towards PMIX and PMX. Despite these headways, the major obstacle in targeting PM is the structural homogeneity among its members and to human Cathepsin D. The incorporation of CADD techniques described in the study at early stages of drug discovery could help in selective inhibition to augment malaria chemotherapy.     

介孔硅铝酸盐的合成及其在傅克反应中的催化性能

采用溶胶凝胶法合成了一系列有序性好且酸性较强的介孔硅铝酸盐材料。利用X射线粉末衍射(XRD)、透射电镜(TEM)、²⁷Al核磁共振(²⁷Al NMR)、氨气程序升温脱附(HN₃-TPD)及吡啶吸附红外光谱(Py-FT-IR)对制备的介孔硅铝酸盐材料的结构和性能进行表征,并考察了材料在苯甲醚和苯甲醇的傅克烷基化反应中的催化活性。实验结果表明：合成过程中,表面活性剂的用量、硅铝物质的量的比会影响材料结构的有序性,醋酸用量对材料结构有序性影响很小;进一步研究结果表明,n_Si / n_Al比会影响材料的酸催化活性,当n_Si / n_Al=10时材料的酸催化活性最高。氨气程序升温脱附和吡啶吸附红外光谱表明n_Si / n_Al=10的材料含有最多的B酸酸量。     

介孔硅铝酸盐的合成及其在傅克反应中的催化性能

采用溶胶凝胶法合成了一系列有序性好且酸性较强的介孔硅铝酸盐材料。利用X射线粉末衍射(XRD)、透射电镜(TEM)、27Al核磁共振(27Al NMR)、氨气程序升温脱附(HN3-TPD)及吡啶吸附红外光谱(Py-FT-IR)对制备的介孔硅铝酸盐材料的结构和性能进行表征,并考察了材料在苯甲醚和苯甲醇的傅克烷基化反应中的催化活性。实验结果表明:合成过程中,表面活性剂的用量、硅铝物质的量之比会影响材料结构的有序性,醋酸用量对材料结构有序性影响很小;进一步研究结果表明,nSi/nAl比会影响材料的酸催化活性,当nSi/nAl=10时材料的酸催化活性最高。氨气程序升温脱附和吡啶吸附红外光谱表明nSi/nAl=10的材料含有最多的B酸酸量。