Prediction of novel biochemical class disease related proteins and microRNAs by machine learning approach

Ph.DDOCTOR OF PHILOSOPH

NAD tagSeq reveals that NAD+-capped RNAs are mostly produced from a large number of protein-coding genes in Arabidopsis.

The 5' end of a eukaryotic mRNA transcript generally has a 7-methylguanosine (m7G) cap that protects mRNA from degradation and mediates almost all other aspects of gene expression. Some RNAs in Escherichia coli, yeast, and mammals were recently found to contain an NAD+ cap. Here, we report the development of the method NAD tagSeq for transcriptome-wide identification and quantification of NAD+-capped RNAs (NAD-RNAs). The method uses an enzymatic reaction and then a click chemistry reaction to label NAD-RNAs with a synthetic RNA tag. The tagged RNA molecules can be enriched and directly sequenced using the Oxford Nanopore sequencing technology. NAD tagSeq can allow more accurate identification and quantification of NAD-RNAs, as well as reveal the sequences of whole NAD-RNA transcripts using single-molecule RNA sequencing. Using NAD tagSeq, we found that NAD-RNAs in Arabidopsis were produced by at least several thousand genes, most of which are protein-coding genes, with the majority of these transcripts coming from <200 genes. For some Arabidopsis genes, over 5% of their transcripts were NAD capped. Gene ontology terms overrepresented in the 2,000 genes that produced the highest numbers of NAD-RNAs are related to photosynthesis, protein synthesis, and responses to cytokinin and stresses. The NAD-RNAs in Arabidopsis generally have the same overall sequence structures as the canonical m7G-capped mRNAs, although most of them appear to have a shorter 5' untranslated region (5' UTR). The identification and quantification of NAD-RNAs and revelation of their sequence features can provide essential steps toward understanding the functions of NAD-RNAs

Propofol affects the biological behavior of ovarian cancer SKOV3 cells via ERK1/2-MMP-2/9 signaling pathway

Purpose: To investigate the effect of propofol on the biological behavior of ovarian cancer SKOV3 cells, and the mechanism of action involved. Methods: SKOV3 cells cultured in vitro were randomly divided into control group, fat emulsion group, low-dose propofol group (LDPG, 25 μmol/L), medium-dose propofol group (MDPG) (50 μmol/L) and high-dose propofol group (HDPG) (100 μmol/L). Apoptosis was determined by flow cytometry, while Transwell assay was used to measure the migration and invasion abilities of the cells. The protein levels of ERK1/2, MMP-2, MMP-9 were assayed with Western blotting. Moreover, the cells were transfected with siERK, and the regulatory effect of propofol on ERK1/2-MMP-2/9 signaling pathway was determined. Results: Apoptosis in HDPG was significantly reduced, relative to MDPG, while migration and invasion were enhanced, relative to MDPG (p < 0.05). Moreover, MMP-2, ERK1/2, and MMP-9 proteins were significantly higher in MDPG and HDPG than in control, fat emulsion and LDPGs (p < 0.05), and were upregulated in HDPGs, relative to MDPG (p < 0.05). In contrast, propofol did not up-regulate these proteins in siRNA-treated cells. Conclusion: Propofol enhances the migration, proliferation, and invasive ability SKOV3 cells, and upregulates the expressions of MMP-2, ERK1/2, and MMP-9 in these cells, via a mechanism related to the activation of ERK1/2-MMP-2/9 signaling route. These properties provide novel leads for the development of new drugs for ovarian cancer Keywords: Propofol, ERK1/2-MMP-2/9 signal route, Ovarian cancer, Biological behavio

PDTD: a web-accessible protein database for drug target identification

<p>Abstract</p> <p>Background</p> <p>Target identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D) structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (<it>Tar</it>get <it>Fis</it>hing <it>Dock</it>ing) <url>http://www.dddc.ac.cn/tarfisdock</url>, which has been used widely by others. Recently, we have constructed a protein target database, <it>P</it>otential <it>D</it>rug <it>T</it>arget <it>D</it>atabase (PDTD), and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation.</p> <p>Description</p> <p>PDTD is a web-accessible protein database for <it>in silico </it>target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling) pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores.</p> <p>Conclusion</p> <p>PDTD serves as a comprehensive and unique repository of drug targets. Integrated with TarFisDock, PDTD is a useful resource to identify binding proteins for active compounds or existing drugs. Its potential applications include <it>in silico </it>drug target identification, virtual screening, and the discovery of the secondary effects of an old drug (i.e. new pharmacological usage) or an existing target (i.e. new pharmacological or toxic relevance), thus it may be a valuable platform for the pharmaceutical researchers. PDTD is available online at <url>http://www.dddc.ac.cn/pdtd/</url>.</p

TarFisDock: a web server for identifying drug targets with docking approach

TarFisDock is a web-based tool for automating the procedure of searching for small molecule–protein interactions over a large repertoire of protein structures. It offers PDTD (potential drug target database), a target database containing 698 protein structures covering 15 therapeutic areas and a reverse ligand–protein docking program. In contrast to conventional ligand–protein docking, reverse ligand–protein docking aims to seek potential protein targets by screening an appropriate protein database. The input file of this web server is the small molecule to be tested, in standard mol2 format; TarFisDock then searches for possible binding proteins for the given small molecule by use of a docking approach. The ligand–protein interaction energy terms of the program DOCK are adopted for ranking the proteins. To test the reliability of the TarFisDock server, we searched the PDTD for putative binding proteins for vitamin E and 4H-tamoxifen. The top 2 and 10% candidates of vitamin E binding proteins identified by TarFisDock respectively cover 30 and 50% of reported targets verified or implicated by experiments; and 30 and 50% of experimentally confirmed targets for 4H-tamoxifen appear amongst the top 2 and 5% of the TarFisDock predicted candidates, respectively. Therefore, TarFisDock may be a useful tool for target identification, mechanism study of old drugs and probes discovered from natural products. TarFisDock and PDTD are available at

Seroprevalence and risk factors of Toxoplasma gondii infection in children with leukemia in Shandong Province, Eastern China: a case—control prospective study

Limited information is available concerning the epidemiology of Toxoplasma gondii infection in children with leukemia in Eastern China. Therefore, a case-control study was conducted to estimate the seroprevalence of toxoplasmosis in this patient group and to identify risk factors and possible routes of infection. Serum samples were collected from 339 children with leukemia and 339 age matched health control subjects in Qingdao from September 2014 to March 2018. Enzyme linked immunoassays were used to screen anti- T. gondii IgG and anti- T. gondii IgM antibodies. Forty-eight (14.2%) children with leukemia and 31 (9.1%) control subjects were positive for anti-T. gondii IgG antibodies (P < 0.05), while 13 (3.8%) patients and 14 (4.1%) controls were positive for anti-T. gondii IgM antibodies (P = 0.84). Multivariate analysis showed exposure to soil and a history of blood transfusion were risk factors for T. gondii infection. Compared with IgG, patients with a history of blood transfusion were more likely to present anti- T. gondii IgM (P = 0.003). Moreover, patients with chronic lymphocytic leukemia and acute lymphocytic leukemia had higher T. gondii seroprevalence in comparison to control subjects (P = 0.002 and P = 0.016, respectively). The results indicated that the seroprevalence of T. gondii infection in children with leukemia is higher than that of healthy children in Eastern China. This information may be used to guide future research and clinical management, and further studies are necessary to elucidate the role of T. gondii in children with leukemia

The Integrated Genomic Landscape of Thymic Epithelial Tumors

Thymic epithelial tumors (TETs) are one of the rarest adult malignancies. Among TETs, thymoma is the most predominant, characterized by a unique association with autoimmune diseases, followed by thymic carcinoma, which is less common but more clinically aggressive. Using multi-platform omics analyses on 117 TETs, we define four subtypes of these tumors defined by genomic hallmarks and an association with survival and World Health Organization histological subtype. We further demonstrate a marked prevalence of a thymoma-specific mutated oncogene, GTF2I, and explore its biological effects on multi-platform analysis. We further observe enrichment of mutations in HRAS, NRAS, and TP53. Last, we identify a molecular link between thymoma and the autoimmune disease myasthenia gravis, characterized by tumoral overexpression of muscle autoantigens, and increased aneuploidy