Structural basis for the membrane association of ankyrinG via palmitoylation

Fujiwara, Y., Kondo, H., Shirota, M. et al. Structural basis for the membrane association of ankyrinG via palmitoylation. Sci Rep 6, 23981 (2016) doi:10.1038/srep2398

SAHG, a comprehensive database of predicted structures of all human proteins

Most proteins from higher organisms are known to be multi-domain proteins and contain substantial numbers of intrinsically disordered (ID) regions. To analyse such protein sequences, those from human for instance, we developed a special protein-structure-prediction pipeline and accumulated the products in the Structure Atlas of Human Genome (SAHG) database at http://bird.cbrc.jp/sahg. With the pipeline, human proteins were examined by local alignment methods (BLAST, PSI-BLAST and Smith–Waterman profile–profile alignment), global–local alignment methods (FORTE) and prediction tools for ID regions (POODLE-S) and homology modeling (MODELLER). Conformational changes of protein models upon ligand-binding were predicted by simultaneous modeling using templates of apo and holo forms. When there were no suitable templates for holo forms and the apo models were accurate, we prepared holo models using prediction methods for ligand-binding (eF-seek) and conformational change (the elastic network model and the linear response theory). Models are displayed as animated images. As of July 2010, SAHG contains 42 581 protein-domain models in approximately 24 900 unique human protein sequences from the RefSeq database. Annotation of models with functional information and links to other databases such as EzCatDB, InterPro or HPRD are also provided to facilitate understanding the protein structure-function relationships

Lack of Transcription Triggers H3K27me3 Accumulation in the Gene Body

Trimethylated H3K27 (H3K27me3) is associated with transcriptional repression, and its abundance in chromatin is frequently altered in cancer. However, it has remained unclear how genomic regions modified by H3K27me3 are specified and formed. We previously showed that downregulation of transcription by oncogenic Ras signaling precedes upregulation of H3K27me3 level. Here, we show that lack of transcription as a result of deletion of the transcription start site of a gene is sufficient to increase H3K27me3 content in the gene body. We further found that histone deacetylation mediates Ras-induced gene silencing and subsequent H3K27me3 accumulation. The H3K27me3 level increased gradually after Ras activation, requiring at least 35 days to achieve saturation. Such maximal accumulation of H3K27me3 was reversed by forced induction of transcription with the dCas9-activator system. Thus, our results indicate that changes in H3K27me3 level, especially in the body of a subset of genes, are triggered by changes in transcriptional activity itself

Ion Concentration- and Voltage-Dependent Push and Pull Mechanisms of Potassium Channel Ion Conduction

<div><p>The mechanism of ion conduction by potassium channels is one of the central issues in physiology. In particular, it is still unclear how the ion concentration and the membrane voltage drive ion conduction. We have investigated the dynamics of the ion conduction processes in the Kv1.2 pore domain, by molecular dynamics (MD) simulations with several different voltages and ion concentrations. By focusing on the detailed ion movements through the pore including selectivity filter (SF) and cavity, we found two major conduction mechanisms, called the III-IV-III and III-II-III mechanisms, and the balance between the ion concentration and the voltage determines the mechanism preference. In the III-IV-III mechanism, the outermost ion in the pore is pushed out by a new ion coming from the intracellular fluid, and four-ion states were transiently observed. In the III-II-III mechanism, the outermost ion is pulled out first, without pushing by incoming ions. Increases in the ion concentration and voltage accelerated ion conductions, but their mechanisms were different. The increase in the ion concentrations facilitated the III-IV-III conductions, while the higher voltages increased the III-II-III conductions, indicating that the pore domain of potassium channels permeates ions by using two different driving forces: a push by intracellular ions and a pull by voltage.</p></div

Ion Concentration-Dependent Ion Conduction Mechanism of a Voltage-Sensitive Potassium Channel

<div><p>Voltage-sensitive potassium ion channels are essential for life, but the molecular basis of their ion conduction is not well understood. In particular, the impact of ion concentration on ion conduction has not been fully studied. We performed several micro-second molecular dynamics simulations of the pore domain of the Kv1.2 potassium channel in KCl solution at four different ion concentrations, and scrutinized each of the conduction events, based on graphical representations of the simulation trajectories. As a result, we observed that the conduction mechanism switched with different ion concentrations: at high ion concentrations, potassium conduction occurred by Hodgkin and Keynes' knock-on mechanism, where the association of an incoming ion with the channel is tightly coupled with the dissociation of an outgoing ion, in a one-step manner. On the other hand, at low ion concentrations, ions mainly permeated by a two-step association/dissociation mechanism, in which the association and dissociation of ions were not coupled, and occurred in two distinct steps. We also found that this switch was triggered by the facilitated association of an ion from the intracellular side within the channel pore and by the delayed dissociation of the outermost ion, as the ion concentration increased.</p> </div

Ion conduction processes under negative (-1,380 mV) voltage.

<p>(A) Ion-binding state graph. (B and C) Snapshots of the K:0:2:4 and K:0:2:5 states, respectively. (D) The trajectory of K⁺ ions in the pore axis.</p

Ion-binding state graph.

<p>The ion-binding state graph for the simulation at 150 mM ion concentration. A node and an edge indicate the state of the binding ions in the pore, and the transition between two states, respectively. The size and color of each node mean log existence probability of the state during the simulation. The red edges mean that a new K⁺ ion is entering from the intracellular side, and the blue ones indicate that an ion in S0 is exiting to the extracellular side. The nodes are classified into the four groups: II, IIIr, IIIe, and IV, for the following discussion. The two major ways to conduct K⁺ are shown as cyan and pink bold arrows (see the main text for details). The graph was drawn with Cytoscape 2.8 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056342#pone.0056342-Smoot1" target="_blank">[42]</a>.</p