Novel thienopyridine derivatives as specific anti-hepatocellular carcinoma (HCC) agents: Synthesis,preliminary structure–activity relationships,and in vitro biological evaluation

Novel thienopyridine derivatives 1b–1r were synthesized, based on a hit compound 1a that was found in a previous cell-based screening of anticancer drugs. Compounds 1a–1r have the following features: (1) their anticancer activity in vitro was first reported by our group. (2) The most potent analog 1g possesses hepatocellular carcinoma (HCC)-specific anticancer activity. It can specifically inhibit the proliferation of the human hepatoma HepG2 cells with an IC₅₀ value of 0.016 μM (compared with doxorubicin as a positive control, whose IC₅₀ was 0.37 μM). It is inactive toward a panel of five different types of human cancer cell lines. (3) Compound 1g remarkably induces G₀/G₁ arrest and apoptosis in HepG2 cells in vitro at low micromolar concentrations. These results, especially the HCC-specific anticancer activity of 1g, suggest their potential in targeted chemotherapy for HCC.     

Synthesis,characterization and preliminary analysis of in vivo biological activity of chitosan/celecoxib microcapsules

The use of chitosan as the wall of microcapsule designed for delivery of encapsulated celecoxib is reported. Microcapsules were characterised with respect to size and encapsulation efficiency of celecoxib. In vivo animals demonstrated that both free celecoxib administration and chitosan/celecoxib microcapsules administration lead to a significant inhibition of cyclooxygenase-2 protein expression in the hepatocytes when compared with vehicle control mice. Interestingly, microcapsule containing celecoxib showed a better inhibition of cyclooxygenase-2 protein expression when compared with a simple oral administration of free celecoxib. Gas-chromatography–mass-spectrometry analysis showed that in mice treated with free celecoxib or chitosan/celecoxib microcapsules, their plasma concentration of celecoxib was similar. Microcapsules-based biomaterials as oral drug delivery vehicles may help to improve the absorption efficiency of therapeutic drugs.     

Mechanism of CDK5 activation revealed by steered molecular dynamics simulations and energy calculations

In the current work, CDK5/p25 complexes were pulled apart by applying external forces with steered molecular dynamics (SMD) simulations. The crucial interactions between the kinase and the activation protein were investigated and the SMD simulations showed that several activation-relevant motifs of CDK5 leave p25 in sequence during the pulling and lead to an apo-CDK2 like CDK5 structure after separation. Based on systematic examination of hydrogen bond breaking and classical MD/molecular mechanics-generalized Born/surface area) (MM-GBSA) calculations, a CDK5 activation mechanism by p25 is suggested. This is the first step towards the systemic development of CDK inhibitors and the mechanism proposed could lead to a better understanding of the protein–protein recognition characteristics between the kinase and its activator.     

Translationally optimal codons associate with aggregation-prone sites in proteins

We analyze the relationship between codon usage bias and residue aggregation propensity in the genomes of four model organisms, Escherichia coli, yeast, fly, and mouse, as well as the archaeon Halobacterium species NRC-1. Using the Mantel-Haenszel procedure, we find that translationally optimal codons associate with aggregation-prone residues. Our results are qualitatively and quantitatively similar to those of an earlier study where we found an association between translationally optimal codons and buried residues. We also combine the aggregation-propensity data with solvent-accessibility data. Although the resulting data set is small, and hence statistical power low, results indicate that the association between optimal codons and aggregation-prone residues exists both at buried and at exposed sites. By comparing codon usage at different combinations of sites (exposed, aggregation-prone sites versus buried, non-aggregation-prone sites; buried, aggregation-prone sites versus exposed, non-aggregation-prone sites), we find that aggregation propensity and solvent accessibility seem to have independent effects of (on average) comparable magnitude on codon usage. Finally, in fly, we assess whether optimal codons associate with sites at which amino acid substitutions lead to an increase in aggregation propensity, and find only a very weak effect. These results suggest that optimal codons may be required to reduce the frequency of translation errors at aggregation-prone sites that coincide with certain functional sites, such as protein-protein interfaces. Alternatively, optimal codons may be required for rapid translation of aggregation-prone regions.     

The Prediction of Nasopharyngeal Carcinoma Mortality Based on Soil Element Levels in China

The relationship between the mortality of nasopharyngeal carcinoma (NPC) and soil trace elements of 29 regions of China was investigated. A total of 29 elements (i.e., Mn, Na, K, Mg, Ca, Sr, Ba, Hg, Pb, Se, In, Yb, Lu, Th, U, Sn, Ti, Zr, Hf, Bi, Ta, Te, Br, I, As, Cr, Cu, Fe, and Zn) were considered. A hybrid strategy called genetic algorithm-partial least squares was used to screen out important elements. As a result, only six elements, i.e., Mn, Ti, Mg, K, Na, and I, were picked out, based on which, a PLS model containing two latent variables exhibited the best performance. According to whether the mortality is larger than 2/100,000 (2?×?10^?5), all the 29 regions were divided into the low-mortality group with 23 regions and the high-mortality group with six regions. Based on the optimal PLS model, all high-mortality regions were successfully classified while only two low-mortality regions were misclassified, i.e., an accuracy of 93%, implying that the selected six elements are effective and successful for predicting the NPC mortality of a region.     

Development of microsatellite markers for the moss Ptychomitrium gardneri (Ptychomitriaceae)

? Premise of the study: Microsatellite markers were developed for Ptychomitrium gardneri to study population genetics of this eastern Asian-North American disjunct moss. ? Methods and Results: A total of 13 microsatellite markers were developed in Chinese populations of P. gardneri, using the Fast Isolation by AFLP of Sequences COntaining Repeats protocol. Eight of the markers showed polymorphism when assessed in a sample of four populations of 29 individuals from China. These markers amplified three to four alleles per locus. Five primers also amplified in P. linearifolium and P. wilsonii. ? Conclusions: These markers may be useful for further investigation of population genetics of P. gardneri.     

Biochemical Characterization of the Cell-Biomaterial Interface by Quantitative Proteomics

Surface topography and texture of cell culture substrata can affect the differentiation and growth of adherent cells. The biochemical basis of the transduction of the physical and mechanical signals to cellular responses is not well understood. The lack of a systematic characterization of cell-biomaterial interaction is the major bottleneck. This study demonstrated the use of a novel subcellular fractionation method combined with quantitative MS-based proteomics to enable the robust and high-throughput analysis of proteins at the adherence interface of Madin-Darby canine kidney cells. This method revealed the enrichment of extracellular matrix proteins and membrane and stress fibers proteins at the adherence surface, whereas it shows depletion of extracellular matrix belonging to the cytoplasmic, nucleus, and lateral and apical membranes. The asymmetric distribution of proteins between apical and adherence sides was also profiled. Apart from classical proteins with clear involvement in cell-material interactions, proteins previously not known to be involved in cell attachment were also discovered.The growth and differentiation of cells in multicellular organisms are regulated by the complex interplay of biochemical and mechanical signals. In the past decades, a plethora of data on the roles of mechanical and structural cues in modulating cellular behaviors has emerged (1–5). It is increasingly evident that cell fates can be changed by engineering the physical properties of the microenvironment to which the cells are exposed (6–8). These observations have inspired the development of functionalized biomaterials that can directly and specifically interact with tissue components, and support or even direct the appropriate cellular activities (9, 10). Although promising progress has been observed in the past few years, several gaps in knowledge in this field have hindered the development of such ”intelligent” biomaterials. In particular, the understanding of the mechanism in which the cell orchestrates physiological and morphological changes by translating mechanical and structural information into biochemical signals is still very limited.As a standard experimental model, cell lines cultured in vitro as a monolayer over solid substrata are usually used to study the effects of biomaterial surfaces on cellular phenotypes. With this simple model system, ingenious experiments have shown that physical forces applied through the extracellular matrix (ECM)1 can induce changes in cell adhesion molecules and stress-induced ion channels, which then lead to changes in the cytoskeleton and gene expressions (11–13). We term the biochemical structure present at the interface between the substratum and the cellular interior the adherence surface (AS), which is composed of the basal plasma membrane with associated structures such as the ECM on one side and the focal adherence complexes on the other. In monolayer cell culture systems, the AS is the only part of the cells in direct contact with the substratum, and is therefore responsible for the first line of communication between the cells and the biomaterial. It is likely that the AS is the organelle that mediates the communication of mechanical and tectonic signals from the substratum to biochemical transducers in the cells. Given the complexity of this process, it is clear that the understanding of this phenomenon cannot be achieved merely by studying individual biological parts in isolation. It is necessary, therefore, to systematically characterize the biochemical factors that mediate the interactions between cells and materials to yield insights into intracellular signaling processes that are responsible for such cellular responses. Toward this goal, we seek to investigate the biochemical basis of how different biomaterials may impose changes in the composition of the AS of adherent cells.MS-based proteomics have recently emerged as a standard technique in modern cell biology. Various techniques based on the chemical conjugation of isotopically labeled reporters to proteins or peptides, such as the isobaric tag for relative and absolute quantitation (iTRAQ) and the isotope-coded affinity tags, enable MS-based proteomics to quantify and compare proteome changes between biological samples. As an attractive alternative, stable isotope labeling with amino acids in cell culture (SILAC) is a metabolic labeling technique that enables isotopically encoded cells to be mixed before lysis and fractionation, thus eliminating inherent quantification biases in these steps, and also enables a simpler procedure and more accurate quantitation (14). SILAC MS-based proteomics have recently contributed to organellar proteomes (15, 16), accurate measurement of protein-protein interactions (17), and the characterization of proteome dynamics during cell differentiation (18). The use of MS-based proteomics has enabled the systematic evaluation of proteome changes on the adhesion of cells to substrata of interest. Kantawong et al. (19) applied DIGE and LC-MS/MS to identify proteome changes in cells on surface with nanotopography. Xu et al. (20) investigated proteome differences of human osteoblasts on various nano-sized hydroxyapatite powders with different shapes and chemical compositions using iTRAQ-based two-dimensional LC-MS/MS.One advantage of proteomics is that it can effectively be combined with subcellular fractionation and allow the comprehensive characterization of the proteins enriched in targeted cellular structures. To yield new insight in molecular interactions in cell-biomaterial interfaces, we aimed to develop a robust protocol for the proteomic characterization of the AS of adherent cells on a biomaterial surface and use it for discovering new cell-biomaterial interface specific biomarkers. Our approach was to develop an isolation technique for AS with high yields and purity for proteomic analysis. The isolated AS on substratum was analyzed by confocal microscopy and Western blotting. SILAC was then used to characterize the fold-enrichment of proteins in the purified AS compared with whole cells and to discover new biomolecules in the cell-biomaterial interface. This study introduces a novel cell-biomaterial interface proteomic procedure, which can be used to identify the AS specific proteome in a high throughput manner and provide a simple and robust method to systematically analyze cell-biomaterial interactions at a molecular level.     

A Universal Trend of Reduced mRNA Stability near the Translation-Initiation Site in Prokaryotes and Eukaryotes

Recent studies have suggested that the thermodynamic stability of mRNA secondary structure near the start codon can regulate translation efficiency in Escherichia coli, and that translation is more efficient the less stable the secondary structure. We survey the complete genomes of 340 species for signals of reduced mRNA secondary structure near the start codon. Our analysis includes bacteria, archaea, fungi, plants, insects, fishes, birds, and mammals. We find that nearly all species show evidence for reduced mRNA stability near the start codon. The reduction in stability generally increases with increasing genomic GC content. In prokaryotes, the reduction also increases with decreasing optimal growth temperature. Within genomes, there is variation in the stability among genes, and this variation correlates with gene GC content, codon bias, and gene expression level. For birds and mammals, however, we do not find a genome-wide trend of reduced mRNA stability near the start codon. Yet the most GC rich genes in these organisms do show such a signal. We conclude that reduced stability of the mRNA secondary structure near the start codon is a universal feature of all cellular life. We suggest that the origin of this reduction is selection for efficient recognition of the start codon by initiator-tRNA.     

A computational framework for influenza antigenic cartography

Influenza viruses have been responsible for large losses of lives around the world and continue to present a great public health challenge. Antigenic characterization based on hemagglutination inhibition (HI) assay is one of the routine procedures for influenza vaccine strain selection. However, HI assay is only a crude experiment reflecting the antigenic correlations among testing antigens (viruses) and reference antisera (antibodies). Moreover, antigenic characterization is usually based on more than one HI dataset. The combination of multiple datasets results in an incomplete HI matrix with many unobserved entries. This paper proposes a new computational framework for constructing an influenza antigenic cartography from this incomplete matrix, which we refer to as Matrix Completion-Multidimensional Scaling (MC-MDS). In this approach, we first reconstruct the HI matrices with viruses and antibodies using low-rank matrix completion, and then generate the two-dimensional antigenic cartography using multidimensional scaling. Moreover, for influenza HI tables with herd immunity effect (such as those from Human influenza viruses), we propose a temporal model to reduce the inherent temporal bias of HI tables caused by herd immunity. By applying our method in HI datasets containing H3N2 influenza A viruses isolated from 1968 to 2003, we identified eleven clusters of antigenic variants, representing all major antigenic drift events in these 36 years. Our results showed that both the completed HI matrix and the antigenic cartography obtained via MC-MDS are useful in identifying influenza antigenic variants and thus can be used to facilitate influenza vaccine strain selection. The webserver is available at http://sysbio.cvm.msstate.edu/AntigenMap.