TBI Server: A Web Server for Predicting Ion Effects in RNA Folding

Background

Metal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects.

Results

The TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects.

Conclusions

By accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.     

Down‐regulation of mitogen‐activated protein kinases and nuclear factor‐κB signaling is involved in rapamycin suppression of TLR2‐induced inflammatory response in monocytic THP‐1 cells

Tripalmitoyl‐S‐glycero‐Cys‐(Lys) 4 (Pam3CSK4) interacted with TLR2 induces inflammatory responses through the mitogen‐activated protein kinases (MAPKs) and nuclear factor‐κB (NF‐κB) signal pathway. Rapamycin can suppress TLR‐induced inflammatory responses; however, the detailed molecular mechanism is not fully understood. Here, the mechanism by which rapamycin suppresses TLR2‐induced inflammatory responses was investigated. It was found that Pam3CSK4‐induced pro‐inflammatory cytokines were significantly down‐regulated at both the mRNA and protein levels in THP‐1 cells pre‐treated with various concentrations of rapamycin. Inhibition of phosphatidylinositol 3‐kinase/protein kinase‐B (PI3K/AKT) signaling did not suppress the expression of pro‐inflammatory cytokines, indicating that the immunosuppression mediated by rapamycin in THP1 cells is independent of the PI3K/AKT pathway. RT‐PCR showed that Erk and NF‐κB signal pathways are related to the production of pro‐inflammatory cytokines. Inhibition of Erk or NF‐κB signaling significantly down‐regulated production of pro‐inflammatory cytokines. Additionally, western blot showed that pre‐treatment of THP‐1 cells with rapamycin down‐regulates MAPKs and NF‐κB signaling induced by Pam3CSK4 stimulation, suggesting that rapamycin suppresses Pam3CSK4‐induced pro‐inflammatory cytokines via inhibition of TLR2 signaling. It was concluded that rapamycin suppresses TLR2‐induced inflammatory responses by down‐regulation of Erk and NF‐κB signaling.     

Sparse networks of directly coupled,polymorphic, and functional side chains in allosteric proteins

Recent studies have highlighted the role of coupled side‐chain fluctuations alone in the allosteric behavior of proteins. Moreover, examination of X‐ray crystallography data has recently revealed new information about the prevalence of alternate side‐chain conformations (conformational polymorphism), and attempts have been made to uncover the hidden alternate conformations from X‐ray data. Hence, new computational approaches are required that consider the polymorphic nature of the side chains, and incorporate the effects of this phenomenon in the study of information transmission and functional interactions of residues in a molecule. These studies can provide a more accurate understanding of the allosteric behavior. In this article, we first present a novel approach to generate an ensemble of conformations and an efficient computational method to extract direct couplings of side chains in allosteric proteins, and provide sparse network representations of the couplings. We take the side‐chain conformational polymorphism into account, and show that by studying the intrinsic dynamics of an inactive structure, we are able to construct a network of functionally crucial residues. Second, we show that the proposed method is capable of providing a magnified view of the coupled and conformationally polymorphic residues. This model reveals couplings between the alternate conformations of a coupled residue pair. To the best of our knowledge, this is the first computational method for extracting networks of side chains' alternate conformations. Such networks help in providing a detailed image of side‐chain dynamics in functionally important and conformationally polymorphic sites, such as binding and/or allosteric sites. Proteins 2015; 83:497–516. © 2014 Wiley Periodicals, Inc.