An electrostatic mechanism for Ca(2+)-mediated regulation of gap junction channels.

Gap junction channels mediate intercellular signalling that is crucial in tissue development, homeostasis and pathologic states such as cardiac arrhythmias, cancer and trauma. To explore the mechanism by which Ca(2+) blocks intercellular communication during tissue injury, we determined the X-ray crystal structures of the human Cx26 gap junction channel with and without bound Ca(2+). The two structures were nearly identical, ruling out both a large-scale structural change and a local steric constriction of the pore. Ca(2+) coordination sites reside at the interfaces between adjacent subunits, near the entrance to the extracellular gap, where local, side chain conformational rearrangements enable Ca(2+)chelation. Computational analysis revealed that Ca(2+)-binding generates a positive electrostatic barrier that substantially inhibits permeation of cations such as K(+) into the pore. Our results provide structural evidence for a unique mechanism of channel regulation: ionic conduction block via an electrostatic barrier rather than steric occlusion of the channel pore

Multiple generation of Bengali static signatures

Handwritten signature datasets are really necessary for the purpose of developing and training automatic signature verification systems. It is desired that all samples in a signature dataset should exhibit both inter-personal and intra-personal variability. A possibility to model this reality seems to be obtained through the synthesis of signatures. In this paper we propose a method based on motor equivalence model theory to generate static Bengali signatures. This theory divides the human action to write mainly into cognitive and motor levels. Due to difference between scripts, we have redesigned our previous synthesizer [1,2], which generates static Western signatures. The experiments assess whether this method can approach the intra and inter-personal variability of the Bengali-100 Static Signature DB from a performance-based validation. The similarities reported in the experimental results proof the ability of the synthesizer to generate signature images in this script

A small molecule agonist of EphA2 receptor tyrosine kinase inhibits tumor cell migration in vitro and prostate cancer metastasis in vivo

10.1371/journal.pone.0042120PLoS ONE78

PeptiSite: A structural database of peptide binding sites in 4D

We developed PeptiSite, a comprehensive and reliable database of biologically and structurally characterized peptide-binding sites, in which each site is represented by an ensemble of its complexes with protein, peptide and small molecule partners. The unique features of the database include: (1) the ensemble site representation that provides a fourth dimension to the otherwise three dimensional data, (2) comprehensive characterization of the binding site architecture that may consist of a multimeric protein assembly with cofactors and metal ions and (3) analysis of consensus interaction motifs within the ensembles and identification of conserved determinants of these interactions. Currently the database contains 585 proteins with 650 peptide-binding sites. http://peptisite.ucsd.edu/ link allows searching for the sites of interest and interactive visualization of the ensembles using the ActiveICM web-browser plugin. This structural database for protein-peptide interactions enables understanding of structural principles of these interactions and may assist the development of an efficient peptide docking benchmark

A diagnostic tool for population models using non-compartmental analysis : The ncappc package for R

Background and objective: Non-compartmental analysis (NCA) calculates pharmacokinetic (PK) metrics related to the systemic exposure to a drug following administration, e.g. area under the concentration time curve and peak concentration. We developed a new package in R, called ncappc, to perform (i) a NCA and (ii) simulation-based posterior predictive checks (ppc) for a population PK (PopPK) model using NCA metrics. Methods: The nca feature of ncappc package estimates the NCA metrics by NCA. The ppc feature of ncappc estimates the NCA metrics from multiple sets of simulated concentration time data and compares them with those estimated from the observed data. The diagnostic analysis is performed at the population as well as the individual level. The distribution of the simulated population means of each NCA metric is compared with the corresponding observed population mean. The individual level comparison is performed based on the deviation of the mean of any NCA metric based on simulations for an individual from the corresponding NCA metric obtained from the observed data. The ncappc package also reports the normalized prediction distribution error (NPDE) of the simulated NCA metrics for each individual and their distribution within a population. Results: The ncappc produces two default outputs depending on the type of analysis performed, i.e., NCA and PopPK diagnosis. The PopPK diagnosis feature of ncappc produces 8 sets of graphical outputs to assess the ability of a population model to simulate the concentration time profile of a drug and thereby evaluate model adequacy. In addition, tabular outputs are generated showing the values of the NCA metrics estimated from the observed and the simulated data, along with the deviation, NPDE, regression parameters used to estimate the elimination rate constant and the related population statistics. Conclusions: The ncappc package is a versatile and flexible tool-set written in R that successfully estimates NCA metrics from concentration time data and produces a comprehensive set of graphical and tabular output to summarize the diagnostic results including the model specific outliers. The output is easy to interpret and to use in evaluation of a population PK model. ncappc is freely available on CRAN (http://crantoprojectorg/web/packages/ncappc/index.html/) and GitHub (https://github.comicacha0227/ncappc/).

A Population Pharmacokinetic-Pharmacodynamic Model of Pegfilgrastim

Neutropenia and febrile neutropenia (FN) are serious side effects of cytotoxic chemotherapy which may be alleviated with the administration of recombinant granulocyte colony-stimulating factor (GCSF) derivatives, such as pegfilgrastim (PG) which increases absolute neutrophil count (ANC). In this work, a population pharmacokinetic-pharmacodynamic (PKPD) model was developed based on data obtained from healthy volunteers receiving multiple administrations of PG. The developed model was a bidirectional PKPD model, where PG stimulated the proliferation, maturation, and margination of neutrophils and where circulating neutrophils in turn increased the elimination of PG. Simulations from the developed model show disproportionate changes in response with changes in dose. A dose increase of 10% from the 6 mg therapeutic dose taken as a reference leads to area under the curve (AUC) increases of similar to 50 and similar to 5% for PK and PD, respectively. A full random effects covariate model showed that little of the parameter variability could be explained by sex, age, body size, and race. As a consequence, little of the secondary parameter variability (C-max and AUC of PG and ANC) could be explained by these covariates