Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Protein factors that bind to the murine 2',5'-oligoadenylate synthetase ME-12 gene 5' upstream regulatory region

The murine 2',5'-oligoadenylate synthetase ME-12 gene regulatory region AB forms six complexes with protein factors in murine BALB/c 3T3 cells as demonstrated by the mobility shift electrophoresis assay under the reaction conditions used. The complexes, designated C1-C6 in order of their decreasing electrophoretic mobility, showed three distinctive specificities with regulatory region AB, element A, and element B as probes or competing DNA: 1) C1 is region AB-specific (this complex did not form with either element A or B used alone or as a mixture); 2) C5 formed both with element A and element B; 3) C2, C3, C4, and C6 formed with element B, but not A. The protein factors that give rise to these complexes show differential DNA binding activities in various buffer solutions at different pH values. The C4-forming protein factor is the interferon (IFN)-alpha/beta-stimulated response factor (ISRF) which shows element B specificity. It preexists in the cytoplasm. ISRF appears to be complexed to an inhibitor (ISRFI) in the cytoplasm and to dissociate from the inhibitor and to translocate into the nucleus upon treatment of cells with IFN-alpha/beta. We propose that IFN-alpha/beta treatment of BALB/c 3T3 can trigger at least two events: 1) loosening of a tight inhibitor-ISRF complex with the release of free ISRF; this may be mediated via phosphorylation of ISRF or ISRFI; 2) translocation of ISRF into the nucleus and binding to the enhancer element B, which results in the activation of 2',5'-oligoadenylate synthetase gene expression.     

Growth form and distribution of introduced plants in their native and non-native ranges in Eastern Asia and North America

There is a growing interest in understanding the influence of plant traits on their ability to spread in non-native regions. Many studies addressing this issue have been based on relatively small areas or restricted taxonomic groups. Here, we analyse a large data base involving 1567 plant species introduced between Eastern Asia and North America or from elsewhere to both regions. We related the extent of species distributions in each region to growth form and the distinction between upland and wetland habitats. We identified significant relationships between geographical distribution and plant traits in both native and exotic ranges as well as regional differences in the relationships. Range size was larger for herbaceous graminoids and forbs, especially annuals compared to perennials, than for woody species, and range size also was larger for plants of wetland compared to upland habitats. Distributions were more extensive in North America than in Eastern Asia, although native plants from both regions had broader distributions than non-natives, with exotics from elsewhere intermediate. Growth form and environment explained more of the variance in distribution of plants in North America than in Eastern Asia. The influence of growth form and habitat on distribution suggests that these traits might be related to tolerance of ecological conditions. In addition, the smaller extents of species in non-native compared to native areas suggest roles for dispersal limitation and adaptation to region-specific ecological conditions in determining distribution.     

Screening of significant biomarkers related with prognosis of liver cancer by lncRNA-associated ceRNAs analysis

This study aimed to identify significant biomarkers related to the prognosis of liver cancer using long noncoding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) analysis. Differentially expressed mRNA and lncRNAs between liver cancer and paracancerous tissues were screened, and the functions of these mRNAs were predicted by gene ontology and pathway enrichment analyses. A ceRNA network consisting of differentially expressed mRNAs and lncRNAs was constructed. LncRNA FENDRR and lncRNA HAND2-AS1 were hub nodes in the ceRNA network. A risk score assessment model consisting of eight genes (PDE2A, ESR1, FBLN5, ALDH8A1, AKR1D1, EHHADH, ADRA1A, and GNE) associated with prognosis were developed. Multivariate Cox regression suggested that both pathologic_T and risk group could be regarded as independent prognostic factors. Furthermore, a nomogram model consisting of pathologic_T and risk group showed a good prediction ability for predicting the survival rate of liver cancer patients. The nomogram model consisting of pathologic_T and a risk score assessment model could be regarded as an independent factor for predicting prognosis of liver cancer.