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.     

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.     

Functional role of hedgehog pathway in osteoarthritis

The hedgehog signalling pathway is one of the key regulators of metazoan development, and it plays an important role in the regulation of a variety of developmental and physiological processes. But it is aberrantly activated in many human diseases, including osteoarthritis (OA). In this study, we have reviewed the association of hedgehog signalling pathway in the development and progression of OA and evaluated the efforts to target this pathway for the prevention of OA. Usually in OA, activation of hedgehog induces up-regulation of the expression of hypertrophic markers, including type X collagen, increases production of nitric oxide and prostaglandin E2, several matrix-degrading enzymes including matrix metalloproteinase and a disintegrin and metalloproteinase with thrombospondin motifs in human knee joint cartilage leading to cartilage degeneration, and thus contributes in OA. Targeting hedgehog signalling might be a viable strategy to prevent or treat OA. Chemical inhibitors of hedgehog signalling is promising, but they cause severe side effects. Knockdown of HH gene is not an option for OA treatment in humans because it is not possible to delete HH in larger animals. Efficient knockdown of HH achieved by local delivery of small interfering RNA in future studies utilizing large animal OA models might be a more efficient approach for the prevention of OA. However, it remains a major problem to develop one single scaffold due to the different physiological functions of cartilage and subchondral bones possess. More studies are necessary to identify selective inhibitors for efficiently targeting the hedgehog pathway in clinical conditions.