Biomedical subjects

Hsuan-Cheng Huang

Publications and source records attributed to Hsuan-Cheng Huang.

9 recordsLinked to original sources

PubMed2006

An agent-based system to discover protein-protein interactions, identify protein complexes and proteins with multiple peptide mass fingerprints.

Proteins "work together" by actually binding to form multicomponent complexes that carry out specific functions. Proteomic analyses based on the mass spectrum are now key methods to determine the components in protein complexes. The protein-protein interaction or functional association may be known to exist among the extracted protein spots while analyzing the proteins on the 2D gel. In this study, we develop an agent-based system, namely AgentMultiProtIdent, which integrated two protein identification tools and a variety of databases storing relations among proteins and used to discover protein-protein interactions and protein functional associations, and identify protein complexes and proteins with multiple peptide mass fingerprints as input. The system takes Multiple Peptide Mass Fingerprints (PMFs) as a whole in the protein complex or protein identification. With the relations among proteins, it may greatly improve the accuracy of identification of protein complexes. Also, possible relationship of the multiple peptide mass fingerprints, such as ontology relation, can be discovered by our system, especially in the identification of protein complexes. The agent-based system is now available on the Web at http://dbms104.csie.ncu.edu.tw/ approximately protein/NEW2/.

Animals↗

PubMed2006

Large-scale identification of protein-protein interaction of Escherichia coli K-12.

Protein-protein interactions play key roles in protein function and the structural organization of a cell. A thorough description of these interactions should facilitate elucidation of cellular activities, targeted-drug design, and whole cell engineering. A large-scale comprehensive pull-down assay was performed using a His-tagged Escherichia coli ORF clone library. Of 4339 bait proteins tested, partners were found for 2667, including 779 of unknown function. Proteins copurifying with hexahistidine-tagged baits on a Ni2+-NTA column were identified by MALDI-TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometry). An extended analysis of these interacting networks by bioinformatics and experimentation should provide new insights and novel strategies for E. coli systems biology.

Escherichia coli K12↗

PubMed2006

Proteomics analysis of a novel compound: cyclic RGD in breast carcinoma cell line MCF-7.

In studies of cell adhesion, migration, growth, differentiation, and apoptosis, synthetic peptides containing the RGD (Arg-Gly-Asp) motif have been extensively used as the inhibitors of integrin-ligand interactions. The RGD motif is an integrin-recognition motif found in many ligands, so that the RGD-containing peptides can be used to probe integrin functions in various biological systems. A linear RGD is a tripeptide consisting of a flexible structure that makes the motif bind to its receptor with inefficient chelating affinity. Therefore, we designed a cyclic-RGD peptide (Tpa-RGDWPC, cRGD) with rigid skeleton to closely bind with its receptor. The cRGD was obtained by solid-phase peptide synthesis method using Rink amide resin. We showed that the cRGD exerts more potency than linear RGD on inhibiting cell growth of MCF-7 breast carcinoma cells. This stimulated us to question how cRGD inhibits cell growth of MCF-7 cells. Moreover, understanding what molecular mechanism underlies the effect that RGD motif exerts on MCF-7 cells is also of considerable importance. We used proteomics and bioinformatics to survey the global changes in proteins after cRGD treatment in MCF-7 cells. The classification of these proteins is shown according to the different biological processes in which they are involved. Most of the proteins that appear to be strongly influenced by cRGD treatment are involved in metabolism, cell growth, responsive to external stimulus, cell communication, reproduction and cell death. This is the first report which monitors the protein expression profile of MCF-7 cells in response to treatment with RGD-containing peptides in a time-course analysis. The clustering data indicated temporal patterns of altered protein expression that can be categorized into early, intermediate and late response proteins. These patterns of protein expression may be important for predicting its response to cRGD. In summary, these results provide a molecular explanation for the properties of cRGD in breast cancer cells and present a valuable in-depth description of their possible impact on breast cancer therapy.

Antineoplastic Agents↗

PubMed2006

Lipopolysaccharide-stimulated responses in rat aortic endothelial cells by a systems biology approach.

The vascular endothelium plays an important role in regulating immune and inflammatory responses to resist pathogens infection. Although it has been known that lipopolysaccharide (LPS) is a critical inducer of sepsis or endotoxemia, the systematic responses of LPS-stimulation in endothelial cells (ECs) are still unclear. The present study aims to analyze the late-phase responses of LPS-induced rat aortic ECs by using systematic biology approaches, including rat cDNA microarray, 2-DE and MALDI-TOF MS/MS, and cytokine protein array. Furthermore, to improve the efficiency of analysis of the bulk systematic data of rat, we designed a set of bioinformatic tools to convert and integrate these rat data into the corresponding human genes or proteins IDs based on BioCarta, KEGG, and Gene Ontology databases. Using the systematic analysis, it was shown that LPS could promote some signaling or metabolic pathways as well as pathophysiologic phenomena of proliferation, atherogenesis, inflammation, and apoptosis through activated nuclear factor-kappaB pathway in ECs. Interestingly, ECs also activated the mediators of anti-inflammation, antiapoptosis, and antioxidation to protect themselves. Moreover, the expressions of altered genes, proteins, and their involvement in the hypothetical signaling pathway can provide further understanding of inflammation associated responses in ECs.

Animals↗

PubMed2006

Quantitative proteomic and genomic profiling reveals metastasis-related protein expression patterns in gastric cancer cells.

Gastric cancer is a leading cause of death worldwide, and patients have an overall 5-year survival rate of less than 10%. Using quantitative proteomic techniques together with microarray chips, we have established comprehensive proteome and transcriptome profiles of the metastatic gastric cancer TMC-1 cells and the noninvasive gastric cancer SC-M1 cell. Our qualitative protein profiling strategy offers the first comprehensive analysis of the gastric cancer cell proteome, identifying 926 and 909 proteins from SC-M1 and TMC-1 cells, respectively. Cleavable isotope-coded affinity tagging analysis allows quantitation of a total of 559 proteins (with a protein false-positive rate of <0.005), and 240 proteins were differentially expressed (>1.3-fold) between the SC-M1 and TMC-1 cells. We identified numerous proteins not previously associated with gastric cancer. Notably, a large subset of differentially expressed proteins was associated with tumor metastasis, including proteins functioning in cell-cell and cell-extracellular matrix (cell-ECM) adhesion, cell motility, proliferation, and tumor immunity. Gene expression profiling by DNA microarray revealed differential expression (of >2-fold) of about 1000 genes. The weak correlation observed between protein and mRNA profiles highlights the important complementarities of DNA microarray and proteomics approaches. These comparative data enabled us to map the disease-perturbed cell-cell and cell-ECM adhesion and Rho GTPase-mediated cytoskeletal pathways. Further validation of a subset of genes suggests the potential use of vimentin and galectin 1 as markers for metastasis. We demonstrate that combining proteomic and genomic approaches not only provides a rapid, robust, and sensitive platform to elucidate the molecular mechanisms underlying gastric cancer metastasis but also may identify candidate diagnostic markers and therapeutic targets.

Biomarkers, Tumor↗

PubMed2005

A new application of microwave technology to proteomics.

Two-dimensional electrophoresis (2-DE) combined with mass spectrometry has significantly improved the possibilities of large-scale identification of proteins. However, 2-DE is limited by its inability to speed up the in-gel digestion process. We have developed a new approach to speed up the protein identification process utilizing microwave technology. Proteins excised from gels are subjected to in-gel digestion with endoprotease trypsin by microwave irradiation, which rapidly produces peptide fragments. The peptide fragments were further analyzed by matrix-assisted laser desorption/ionization technique for protein identification. The efficacy of this technique for protein mapping was demonstrated by the mass spectral analyses of the peptide fragmentation of several proteins, including lysozyme, albumin, conalbumin, and ribonuclease A. The method reduced the required time for in-gel digestion of proteins from 16 hours to as little as five minutes. This new application of microwave technology to protein identification will be an important advancement in biotechnology and proteome research.

Albumins↗

PubMed2004

GeneNetwork: an interactive tool for reconstruction of genetic networks using microarray data.

UNLABELLED: Inferring genetic network architecture from time series data generated from high-throughput experimental technologies, such as cDNA microarray, can help us to understand the system behavior of living organisms. We have developed an interactive tool, GeneNetwork, which provides four reverse engineering models and three data interpolation approaches to infer relationships between genes. GeneNetwork enables a user to readily reconstruct genetic networks based on microarray data without having intimate knowledge of the mathematical models. A simple graphical user interface enables rapid, intuitive mapping and analysis of the reconstructed network allowing biologists to explore gene relationships at the system level. AVAILABILITY: Download from http://genenetwork.sbl.bc.sinica.edu.tw/. SUPPLEMENTARY INFORMATION: Supplement documentation of algorithms for the four approaches is downloadable at the above location.

Algorithms↗

PubMed2004

ProteMiner-SSM: a web server for efficient analysis of similar protein tertiary substructures.

Analysis of protein-ligand interactions is a fundamental issue in drug design. As the detailed and accurate analysis of protein-ligand interactions involves calculation of binding free energy based on thermodynamics and even quantum mechanics, which is highly expensive in terms of computing time, conformational and structural analysis of proteins and ligands has been widely employed as a screening process in computer-aided drug design. In this paper, a web server called ProteMiner-SSM designed for efficient analysis of similar protein tertiary substructures is presented. In one experiment reported in this paper, the web server has been exploited to obtain some clues about a biochemical hypothesis. The main distinction in the software design of the web server is the filtering process incorporated to expedite the analysis. The filtering process extracts the residues located in the caves of the protein tertiary structure for analysis and operates with O(nlogn) time complexity, where n is the number of residues in the protein. In comparison, the alpha-hull algorithm, which is a widely used algorithm in computer graphics for identifying those instances that are on the contour of a three-dimensional object, features O(n2) time complexity. Experimental results show that the filtering process presented in this paper is able to speed up the analysis by a factor ranging from 3.15 to 9.37 times. The ProteMiner-SSM web server can be found at http://proteminer.csie.ntu.edu.tw/. There is a mirror site at http://p4.sbl.bc.sinica.edu.tw/proteminer/.

Binding Sites↗

PubMed2004

Small molecules targeting severe acute respiratory syndrome human coronavirus.

Severe acute respiratory syndrome (SARS) is an infectious disease caused by a novel human coronavirus. Currently, no effective antiviral agents exist against this type of virus. A cell-based assay, with SARS virus and Vero E6 cells, was developed to screen existing drugs, natural products, and synthetic compounds to identify effective anti-SARS agents. Of >10,000 agents tested, approximately 50 compounds were found active at 10 microM; among these compounds, two are existing drugs (Reserpine 13 and Aescin 5) and several are in clinical development. These 50 active compounds were tested again, and compounds 2-6, 10, and 13 showed active at 3 microM. The 50% inhibitory concentrations for the inhibition of viral replication (EC(50)) and host growth (CC(50)) were then measured and the selectivity index (SI = CC(50)/EC(50)) was determined. The EC(50), based on ELISA, and SI for Reserpine, Aescim, and Valinomycin are 3.4 microM (SI = 7.3), 6.0 microM (SI = 2.5), and 0.85 microM (SI = 80), respectively. Additional studies were carried out to further understand the mode of action of some active compounds, including ELISA, Western blot analysis, immunofluorescence and flow cytometry assays, and inhibition against the 3CL protease and viral entry. Of particular interest are the two anti-HIV agents, one as an entry blocker and the other as a 3CL protease inhibitor (K(i) = 0.6 microM).

Animals↗