Frizzled receptors (FZDs) in Wnt signaling: potential therapeutic targets for human cancers.

Frizzled receptors (FZDs) are key contributors intrinsic to the Wnt signaling pathway, activation of FZDs triggering the Wnt signaling cascade is frequently observed in human tumors and intimately associated with an aggressive carcinoma phenotype. It has been shown that the abnormal expression of FZD receptors contributes to the manifestation of malignant characteristics in human tumors such as enhanced cell proliferation, metastasis, chemotherapy resistance as well as the acquisition of cancer stemness. Given the essential roles of FZD receptors in the Wnt signaling in human tumors, this review aims to consolidate the prevailing knowledge on the specific status of FZD receptors (FZD1-10) and elucidate their respective functions in tumor progression. Furthermore, we delineate the structural basis for binding of FZD and its co-receptors to Wnt, and provide a better theoretical foundation for subsequent studies on related mechanisms. Finally, we describe the existing biological classes of small molecule-based FZD inhibitors in detail in the hope that they can provide useful assistance for design and development of novel drug candidates targeted FZDs.

[Pathogenesis of Secondary Pulmonary Tuberculosis and Role of Cord Factor in Secondary Infection].

The primary and secondary tuberculosis features two completely different pathogenesis.At present,the pathogenesis of primary tuberculosis has been clear,whereas that of secondary tuberculosis remains unclear.In order to decipher the mechanism of secondary infection of Mycobacterium tuberculosis and provide insights into vaccine research and drug development,this paper reviews the problems of the widely accepted mechanism of secondary infection,the new findings of the research on the mechanism,as well as the role of cord factors.

Proteome Profiling Identified Amyloid-ß Protein Precursor as a Novel Binding Partner and Modulator of VGLUT1.

BACKGROUND: The toxicity of excessive glutamate release has been implicated in various acute and chronic neurodegenerative conditions. Vesicular glutamate transporters (VGLUTs) are the major mediators for the uptake of glutamate into synaptic vesicles. However, the dynamics and mechanism of this process in glutamatergic neurons are still largely unknown. OBJECTIVE: This study aimed to investigate the candidate protein partners of VGLUT1 and their regulatory roles in the vesicles in rat brain. METHODS: Pull down assay, co-immunoprecipitation assay, or split-ubiquitin membrane yeast two hybrid screening coupled with nanoRPLC-MS/MS were used to identify the candidate protein partners of VGLUT1 in the vesicles in rat brain. The in vitro and in vivo models were used to test effects of AßPP, Atp6ap2, Gja1, and Synataxin on VGLUT1 expression. RESULTS: A total of 255 and 225 proteins and 172 known genes were identified in the pull down assay, co-immunoprecipitation assay, or split-ubiquitin yeast two-hybrid screening respectively. The physiological interactions of SV2A, Syntaxin 12, Gja1, AßPP, and Atp6ap2 to VGLUT1 were further confirmed. Knockdown of Atp6ap2, Gja1, and Synataxin increased VGLUT1 mRNA expression and only knockdown of AßPP increased both mRNA and protein levels of VGLUT1 in PC12 cells. The regulatory function of AßPP on VGLUT1 expression was further confirmed in the in vitro and in vivo models. CONCLUSION: These results elucidate that the AßPP and VGLUT1 interacts at vesicular level and AßPP plays a role in the regulation of VGLUT1 expression which is essential for maintaining vesicular activities.

Precision and accuracy of commercial assays for vancomycin therapeutic drug monitoring: evaluation based on external quality assessment scheme.

BACKGROUND: Vancomycin remains a mainstay of the treatment of Gram-positive bacterial infections. It is crucial to accurately determine vancomycin serum concentration for adequate dose adjustment. OBJECTIVES: To evaluate the precision and accuracy of commercial assay techniques for vancomycin concentration and to assess the comparability of vancomycin detection methods in Chinese laboratories. METHODS: Human serum samples spiked with known concentrations of vancomycin were provided to laboratories participating in the external quality assessment scheme (EQAS). Assay methods included chemiluminescence, enzyme immunoassay (EIA) and so on. The dispersion of the measurements was analysed and the robust coefficient of variation (rCV), relative percentage difference (RPD) and satisfactory rate for method groups were calculated. Moreover, performance of the Chinese laboratories was assessed. RESULTS: A total of 657 results from 75 laboratories were collected, including 84 samples from 10 Chinese laboratories. The median rCV, median RPD and satisfactory rates classified by methods ranged from 1.85% to 15.87%, -14.75% to 13.34% and 94.59% to 100.00%, respectively. Significant differences were seen in precision, between kinetic interaction of microparticles in solution (KIMS) and other methods, and in accuracy, between enzyme-multiplied immunoassay technique (EMIT), fluorescence polarization immunoassay (FPIA) and other techniques. Vancomycin detection in China mainly depended on the chemiluminescence and EMIT methods, which tended to result in lower measurements. CONCLUSIONS: Although almost all assays in this study achieved an acceptable performance for vancomycin serum concentration monitoring, obvious inconsistencies between methods were still observed. Chinese laboratories were more likely to underestimate vancomycin concentrations. Thus, recognizing inconsistencies between methods and regular participation in vancomycin EQAS are essential.

TF3P: Three-Dimensional Force Fields Fingerprint Learned by Deep Capsular Network.

Molecular fingerprints are the workhorse in ligand-based drug discovery. In recent years, an increasing number of research papers reported fascinating results on using deep neural networks to learn 2D molecular representations as fingerprints. It is anticipated that the integration of deep learning would also contribute to the prosperity of 3D fingerprints. Here, we unprecedentedly introduce deep learning into 3D small molecule fingerprints, presenting a new one we termed as the three-dimensional force fields fingerprint (TF3P). TF3P is learned by a deep capsular network whose training is in no need of labeled data sets for specific predictive tasks. TF3P can encode the 3D force fields information of molecules and demonstrates the stronger ability to capture 3D structural changes, to recognize molecules alike in 3D but not in 2D, and to identify similar targets inaccessible by other 2D or 3D fingerprints based on only ligands similarity. Furthermore, TF3P is compatible with both statistical models (e.g., similarity ensemble approach) and machine learning models. Altogether, we report TF3P as a new 3D small molecule fingerprint with a promising future in ligand-based drug discovery. All codes are written in Python and available at https://github.com/canisw/tf3p.

Functional Characterization and Structural Basis of an Efficient Di-C-glycosyltransferase from Glycyrrhiza glabra.

A highly efficient di-C-glycosyltransferase GgCGT was discovered from the medicinal plant Glycyrrhiza glabra. GgCGT catalyzes a two-step di-C-glycosylation of flopropione-containing substrates with conversion rates of >98%. To elucidate the catalytic mechanisms of GgCGT, we solved its crystal structures in complex with UDP-Glc, UDP-Gal, UDP/phloretin, and UDP/nothofagin, respectively. Structural analysis revealed that the sugar donor selectivity was controlled by the hydrogen-bond interactions of sugar hydroxyl groups with D390 and other key residues. The di-C-glycosylation capability of GgCGT was attributed to a spacious substrate-binding tunnel, and the G389K mutation could switch di- to mono-C-glycosylation. GgCGT is the first di-C-glycosyltransferase with a crystal structure, and the first C-glycosyltransferase with a complex structure containing a sugar acceptor. This work could benefit the development of efficient biocatalysts to synthesize C-glycosides with medicinal potential.

ETCM: an encyclopaedia of traditional Chinese medicine.

Traditional Chinese medicine (TCM) is not only an effective solution for primary health care, but also a great resource for drug innovation and discovery. To meet the increasing needs for TCM-related data resources, we developed ETCM, an Encyclopedia of Traditional Chinese Medicine. ETCM includes comprehensive and standardized information for the commonly used herbs and formulas of TCM, as well as their ingredients. The herb basic property and quality control standard, formula composition, ingredient drug-likeness, as well as many other information provided by ETCM can serve as a convenient resource for users to obtain thorough information about a herb or a formula. To facilitate functional and mechanistic studies of TCM, ETCM provides predicted target genes of TCM ingredients, herbs, and formulas, according to the chemical fingerprint similarity between TCM ingredients and known drugs. A systematic analysis function is also developed in ETCM, which allows users to explore the relationships or build networks among TCM herbs, formulas,ingredients, gene targets, and related pathways or diseases. ETCM is freely accessible at http://www.nrc.ac.cn:9090/ETCM/. We expect ETCM to develop into a major data warehouse for TCM and to promote TCM related researches and drug development in the future.

[Analysis of traditional Chinese medicine prescriptions based on support vector machine and analytic hierarchy process].

Combined use of drugs is a hot spot in the research of new drugs nowadays, and traditional Chinese medicine (TCM) is a classic practice in the combined use of drugs. In this paper, the compatibility of TCM prescriptions and the related properties of composed herbs were calculated and studied to verify and discuss the feasibility of the results in guiding compatibility. Research Group on New Drug Design, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences had established a structured database of TCM prescriptions by using traditional Chinese medicine inheritance support system (TCMISS V2.0), including 4 012 prescription compatibilities, 2 072 drug components, 381 kinds of TCM diseases, 316 kinds of TCM syndromes and 26 kinds of drug properties. On the basis of the created database above, Support Vector Machine (SVM) was used to analyze the prescription compatibility data and establish a model for predicting feasibility of drug compatibilities. Analytic Hierarchy Process (AHP) and cluster analysis were used to study the influence of drug properties in the rationality of prescription compatibility. The computational results showed that the accuracy in efficacy prediction of two data sets, i.e. prescription-disease and prescription-syndrome, was up to 90% in the linear SVM model. The macro₋averaging and micro₋averaging of the two models were around 0.92, 0.46, respectively. After AHP mapping, most of the incompatible combinations showed significant difference with other drug combinations during the clustering process in the vertical icicle, indicating that the proper machine learning algorithm can be used to lay the foundation for further exploring the combination rules in TCM and establishing more detailed drug-disease and syndrome predicting models, and provide theoretical guidance for the study of the combined use of drugs to a certain degree.

Small-molecule compounds targeting the STAT3 DNA-binding domain suppress survival of cisplatin-resistant human ovarian cancer cells by inducing apoptosis.

Constitutive activation of signal transducer and activator of transcription 3 (STAT3) plays important roles in oncogenic occurrence and transformation by regulating the expression of diverse downstream target genes important for tumor growth, metastasis, angiogenesis and immune evasion. Feasibility of targeting the DNA-binding domain (DBD) of STAT3 has been proven previously. With the aid of 3D shape- and electrostatic-based drug design, we identified a new STAT3 inhibitor, LC28, and its five analogs, based on the pharmacophore of a known STAT3 DBD inhibitor. Microscale thermophoresis assay shows that these compounds inhibits STAT3 binding to DNA with a Ki value of 0.74-8.87 µM. Furthermore, LC28 and its analogs suppress survival of cisplatin-resistant ovarian cancer cells by inhibiting STAT3 signaling and inducing apoptosis. Therefore, these compounds may serve as candidate compounds for further modification and development as anticancer therapeutics targeting the DBD of human STAT3 for treatment of cisplatin-resistant ovarian cancer.

[Exploiture and application of an internet-based Computation Platform for Integrative Pharmacology of Traditional Chinese Medicine].

Recently, integrative pharmacology(IP) has become a pivotal paradigm for the modernization of traditional Chinese medicines(TCM) and combinatorial drugs discovery, which is an interdisciplinary science for establishing the in vitro and in vivo correlation between absorption, distribution, metabolism, and excretion/pharmacokinetic(ADME/PK) profiles of TCM and the molecular networks of disease by the integration of the knowledge of multi-disciplinary and multi-stages. In the present study, an internet-based Computation Platform for IP of TCM(TCM-IP, www.tcmip.cn) is established to promote the development of the emerging discipline. Among them, a big data of TCM is an important resource for TCM-IP including Chinese Medicine Formula Database, Chinese Medical Herbs Database, Chemical Database of Chinese Medicine, Target Database for Disease and Symptoms, et al. Meanwhile, some data mining and bioinformatics approaches are critical technology for TCM-IP including the identification of the TCM constituents, ADME prediction, target prediction for the TCM constituents, network construction and analysis, et al. Furthermore, network beautification and individuation design are employed to meet the consumer's requirement. We firmly believe that TCM-IP is a very useful tool for the identification of active constituents of TCM and their involving potential molecular mechanism for therapeutics, which would wildly applied in quality evaluation, clinical repositioning, scientific discovery based on original thinking, prescription compatibility and new drug of TCM, et al.

Molecular interaction studies of acetylcholinesterase with potential acetylcholinesterase inhibitors from the root of Rhodiola crenulata using molecular docking and isothermal titration calorimetry methods.

(-)-Epicatechin gallate ((-)-ECG), 1,2,3,4,6-O-pentagalloylglucose (PGG), rhodionin, herbacetin and rhodiosin isolated from the root of Rhodiola crenulata exhibited potent, dose-dependent inhibitory effects on acetylcholinesterase (AChE) with IC50 ranged from 57.50±5.83 to 2.43±0.34µg/mL. With the aim of explaining the differences in activity of these active ingredients and clarifying how they inhibit AChE, the AChE-inhibitor interactions were further explored using molecular docking and isothermal titration calorimetry (ITC) methods in the present study. Molecular docking studies revealed that all compounds except PGG showed binding energy values ranging from -10.30 to -8.00kcal/mol while the binding energy of galantamine, a known AChE inhibitor, was -9.53kcal/mol; they inhibited the AChE by binding into the ligand pocket with the similar binding pattern to that of galantamine by interacting with Glu199 of AChE. Inhibition constant of these active ingredients had a positive correlation with binding energy. The interaction between AChE and PGG was further evaluated with the ITC method and the results indicated that the PGG-AChE interaction was relevant to AChE concentration. The results revealed a possible mechanism for the AChE inhibition activity of these bioactive ingredients, which may provide some help in lead compounds optimization in the future.

Urea-containing peptide boronic acids as potent proteasome inhibitors.

A novel class of urea-containing peptide boronic acids as proteasome inhibitors was designed by introducing a urea scaffold to replace an amido bond. Compounds were synthesized and their antitumor activities were evaluated. After two rounds of optimizations, the compound I-14 was found to be a potent proteasome inhibitor. Compared with Bortezomib, I-14 showed higher potency against the chymotrypsin-like activity of human 20S proteasome (IC50 < 1 pM), similar potency against four different cancer cell lines (IC50 < 10 nM), and better pharmacokinetic profile. Furthermore, I-14 significantly inhibited tumor growth in Bel7404 mouse xenograft model. The excellent proteasome inhibition by I-14 was rationalized through docking and molecular dynamics studies.

Cloning, expression, and characterization of a four-component O-demethylase from human intestinal bacterium Eubacterium limosum ZL-II.

Eubacterium limosum ZL-II was described to convert secoisolariciresinol (SECO) to its demethylating product 4,4'-dihydroxyenterodiol (DHEND) under anoxic conditions. However, the reaction cascade remains unclear. Here, the O-demethylase being responsible for the conversion was identified and characterized. Nine genes encoding two methyltransferase-Is (MT-I), two corrinoid proteins (CP), two methyltransferase-IIs (MT-II), and three activating enzymes (AE) were screened, cloned, and expressed in Escherichia coli. Four of the nine predicted enzymes, including ELI_2003 (MT-I), ELI_2004 (CP), ELI_2005 (MT-II), and ELI_0370 (AE), were confirmed to constitute the O-demethylase in E. limosum ZL-II. The complete O-demethylase (combining the four components) reaction system was reconstructed in vitro. As expected, the demethylating products 3-demethyl-SECO and DHEND were both produced. During the reaction process, ELI_2003 (MT-I) initially catalyzed the transfer of methyl group from SECO to the corrinoid of ELI_2004 ([CoI]-CP), yielding demethylating products and [CH3-CoIII]-CP; then ELI_2005 (MT-II) mediated the transfer of methyl group from [CH3-CoIII]-CP to tetrahydrofolate, forming methyltetrahydrofolate and [CoI]-CP. Due to the low redox potential of [CoII]/[CoI], [CoI]-CP was oxidized to [CoII]-CP immediately in vitro, and ELI_0370 (AE) was responsible for catalyzing the reduction of [CoII]-CP to its active form [CoI]-CP. The active-site residues in ELI_2003, ELI_2005, and ELI_0370 were subsequently determined using molecular modeling combined with site-directed mutagenesis. To our knowledge, this is the first study on the identification and characterization of a four-component O-demethylase from E. limosum ZL-II, which will facilitate the development of method to artificial synthesis of related bioactive chemicals.

N-(2,6-dimethoxypyridine-3-yl)-9-methylcarbazole-3-sulfonamide as a novel tubulin ligand against human cancer.

PURPOSE: We have synthesized a new tubulin ligand N-(2,6-dimethoxypyridine-3-yl)-9-methylcarbazole-3-sulfonamide (IG-105). This work investigates its anticancer effect and mechanism. EXPERIMENTAL DESIGN: Anticancer efficacy was evaluated at the molecular target, cancer cells and nude mice. The mechanism was explored at submolecular, molecular, and cellular levels. RESULTS: IG-105 showed a potent activity against human leukemia and solid tumors in breast, liver, prostate, lung, skin, colon, and pancreas with IC(50) values between 0.012 and 0.298 mumol/L. It was also active in drug-resistant tumor cells and not a P-glycoprotein substrate. It inhibited microtubule assembly followed by M-phase arrest, Bcl-2 inactivation, and then apoptosis through caspase pathways. The colchicine pocket on tubulin is the binding site of IG-105. Nude mice experiments showed that IG-105 monotherapy at 100 mg/kg i.p. (q2d) yielded 81% inhibition of Bel-7402 hepatoma growth and at 275 mg/kg i.p. (q2d) completely inhibited the tumor growth. MCF-7 breast cancer in nude mice showed a similar therapeutic response to IG-105. Acute toxicity of IG-105 was not found even at 1,000 mg/kg i.p. In combination with oxaliplatin or doxorubicin, IG-105 converted each of these subcurative compounds into a curative treatment with complete inhibition for tumor growth in the hepatoma-bearing nude mice. The combination was more active than either drug. In no experiment was toxicity increased by combination chemotherapy. CONCLUSIONS: IG-105 inhibits microtubule assembly by binding at colchicine pocket. It shows a potent anticancer activity in vitro and in vivo and has good safety in mice. We consider IG-105 merits further investigation.

Cucurbitane triterpenoids from Momordica charantia.

Three new cucurbitane-type triterpenoid saponins, 23-O-beta-D-allopyranosyl-5beta,19-epoxycucurbita-6,24-diene-3beta,22(S),23(S)-triol-3-O-beta-D-glucopyranoside (1), 23-O-beta-D-allopyranosyl-5beta,19-epoxycucurbita-6,24-diene-3beta,22(S),23(S)-triol-3-O-beta-D-allopyranoside (2), and 23-O-beta-D-allopyranosyl-5beta,19-epoxycucurbita-6,24-diene-3beta,19(R), 22(S),23(S)-tetraol-3-O-beta-D-allopyranoside (3), named momordicoside M, N, and O, respectively, along with one known saponin momordicoside L (4), were isolated from the fresh fruits of Momordica charantia. The structures of these saponins were elucidated on the basis of chemical properties and spectral data.

3D-QSAR studies on tripeptide aldehyde inhibitors of proteasome using CoMFA and CoMSIA methods.

The ubiquitin-proteasome pathway plays a crucial role in the regulation of many physiological processes and in the development of a number of major human diseases, such as cancer, Alzheimer's, Parkinson's, diabetes, etc. As a new target, the study on the proteasome inhibitors has received much attention recently. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using comparative molecule field analysis (CoMFA) and comparative molecule similarity indices analysis (CoMSIA) techniques were applied to analyze the binding affinity of a set of tripeptide aldehyde inhibitors of 20S proteasome. The optimal CoMFA and CoMSIA models obtained for the training set were all statistically significant with cross-validated coefficients (q(2)) of 0.615, 0.591 and conventional coefficients (r(2)) of 0.901, 0.894, respectively. These models were validated by a test set of eight molecules that were not included in the training set. The predicted correlation coefficients (r(2)) of CoMFA and CoMSIA are 0.944 and 0.861, respectively. The CoMFA and CoMSIA field contour maps agree well with the structural characteristics of the binding pocket of beta5 subunit of 20S proteasome, which suggests that the 3D-QSAR models built in this paper can be used to guide the development of novel inhibitors of 20S proteasome.