Exploring the Viral Channel KcvPBCV-1 Function via Computation.
Ontology highlight
ABSTRACT:
SUBMITTER: Andersson AEV
PROVIDER: S-EPMC6028866 | biostudies-literature | 2018 Jun
REPOSITORIES: biostudies-literature
Publications
Exploring the Viral Channel Kcv<sub>PBCV-1</sub> Function via Computation.
Andersson Alma E V AEV Kasimova Marina A MA Delemotte Lucie L
The Journal of membrane biology 20180223 3
Viral potassium channels (Kcv) are homologous to the pore module of complex [Formula: see text]-selective ion channels of cellular organisms. Due to their relative simplicity, they have attracted interest towards understanding the principles of [Formula: see text] conduction and channel gating. In this work, we construct a homology model of the [Formula: see text] open state, which we validate by studying the binding of known blockers and by monitoring ion conduction through the channel. Molecul ...[more]
Similar Datasets
Project description:Despite the clinical ubiquity of anesthesia, the molecular basis of anesthetic action is poorly understood. Amongst the many molecular targets proposed to contribute to anesthetic effects, the voltage gated sodium channels (VGSCs) should also be considered relevant, as they have been shown to be sensitive to all general anesthetics tested thus far. However, binding sites for VGSCs have not been identified. Moreover, the mechanism of inhibition is still largely unknown. The recently reported atomic structures of several members of the bacterial VGSC family offer the opportunity to shed light on the mechanism of action of anesthetics on these important ion channels. To this end, we have performed a molecular dynamics "flooding" simulation on a membrane-bound structural model of the archetypal bacterial VGSC, NaChBac in a closed pore conformation. This computation allowed us to identify binding sites and access pathways for the commonly used volatile general anesthetic, isoflurane. Three sites have been characterized with binding affinities in a physiologically relevant range. Interestingly, one of the most favorable sites is in the pore of the channel, suggesting that the binding sites of local and general anesthetics may overlap. Surprisingly, even though the activation gate of the channel is closed, and therefore the pore and the aqueous compartment at the intracellular side are disconnected, we observe binding of isoflurane in the central cavity. Several sampled association and dissociation events in the central cavity provide consistent support to the hypothesis that the "fenestrations" present in the membrane-embedded region of the channel act as the long-hypothesized hydrophobic drug access pathway.
| S-EPMC3681623 | biostudies-literature
Project description:Although the number of available protein sequences is growing exponentially, functional protein annotations lag far behind. Therefore, accurate identification of protein functions remains one of the major challenges in molecular biology. In this study, we presented a novel approach to predict mouse protein functions. The approach was a sequential combination of a similarity-based approach, an interaction-based approach and a pseudo amino acid composition-based approach. The method achieved an accuracy of about 0.8450 for the 1st-order predictions in the leave-one-out and ten-fold cross-validations. For the results yielded by the leave-one-out cross-validation, although the similarity-based approach alone achieved an accuracy of 0.8756, it was unable to predict the functions of proteins with no homologues. Comparatively, the pseudo amino acid composition-based approach alone reached an accuracy of 0.6786. Although the accuracy was lower than that of the previous approach, it could predict the functions of almost all proteins, even proteins with no homologues. Therefore, the combined method balanced the advantages and disadvantages of both approaches to achieve efficient performance. Furthermore, the results yielded by the ten-fold cross-validation indicate that the combined method is still effective and stable when there are no close homologs are available. However, the accuracy of the predicted functions can only be determined according to known protein functions based on current knowledge. Many protein functions remain unknown. By exploring the functions of proteins for which the 1st-order predicted functions are wrong but the 2nd-order predicted functions are correct, the 1st-order wrongly predicted functions were shown to be closely associated with the genes encoding the proteins. The so-called wrongly predicted functions could also potentially be correct upon future experimental verification. Therefore, the accuracy of the presented method may be much higher in reality.
| S-EPMC5112993 | biostudies-literature
Project description:Approximate Bayesian computation has become an essential tool for the analysis of complex stochastic models when the likelihood function is numerically unavailable. However, the well-established statistical method of empirical likelihood provides another route to such settings that bypasses simulations from the model and the choices of the approximate Bayesian computation parameters (summary statistics, distance, tolerance), while being convergent in the number of observations. Furthermore, bypassing model simulations may lead to significant time savings in complex models, for instance those found in population genetics. The Bayesian computation with empirical likelihood algorithm we develop in this paper also provides an evaluation of its own performance through an associated effective sample size. The method is illustrated using several examples, including estimation of standard distributions, time series, and population genetics models.
| S-EPMC3557074 | biostudies-literature
Project description:Viral channel-forming proteins comprise a class of viral proteins which, similar to their host companions, are made to alter electrochemical or substrate gradients across lipid membranes. These proteins are active during all stages of the cellular life cycle of viruses. An increasing number of proteins are identified as channel proteins, but the precise role in the viral life cycle is yet unknown for the majority of them. This review presents an overview about these proteins with an emphasis on those with available structural information. A concept is introduced which aligns the transmembrane domains of viral channel proteins with those of host channels and toxins to give insights into the mechanism of function of the viral proteins from potential sequence identities. A summary of to date investigations on drugs targeting these proteins is given and discussed in respect of their mode of action in vivo.
| S-EPMC7149447 | biostudies-literature
Project description:Exploring the dynamic variations of viral genomes utilizing with a phylogenetic analysis is vital to control the pandemic and stop its waves. Genetic network can be applied to depict the complicated evolution relationships of viral genomes. However, current phylogenetic methods cannot handle the cases with deletions effectively. Therefore, the k-mer natural vector is employed to characterize the compositions and distribution features of k-mers occurring in a viral genome, and construct a one-to-one relationship between a viral genome and its k-mer natural vector. Utilizing the k-mer natural vector, we proposed a novel genetic network to investigate the variations of viral genomes in transmission among humans. With the assistance of genetic network, we identified the super-spreaders that were responsible for the pandemic outbreaks all over the world and chose the parental strains to evaluate the effectiveness of diagnostics, therapeutics, and vaccines. The obtaining results fully demonstrated that our genetic network can truly describe the relationships of viral genomes, effectively simulate virus spread tendency, and trace the transmission routes precisely. In addition, this work indicated that the k-mer natural vector has the ability to capture established hotspots of diversities existing in the viral genomes and understand how genomic contents change over time.
| S-EPMC9262653 | biostudies-literature
Project description:Complex networks have recently become the focus of research in many fields. Their structure reveals crucial information for the nodes, how they connect and share information. In our work we analyze protein interaction networks as complex networks for their functional modular structure and later use that information in the functional annotation of proteins within the network. We propose several graph representations for the protein interaction network, each having different level of complexity and inclusion of the annotation information within the graph. We aim to explore what the benefits and the drawbacks of these proposed graphs are, when they are used in the function prediction process via clustering methods. For making this cluster based prediction, we adopt well established approaches for cluster detection in complex networks using most recent representative algorithms that have been proven as efficient in the task at hand. The experiments are performed using a purified and reliable Saccharomyces cerevisiae protein interaction network, which is then used to generate the different graph representations. Each of the graph representations is later analysed in combination with each of the clustering algorithms, which have been possibly modified and implemented to fit the specific graph. We evaluate results in regards of biological validity and function prediction performance. Our results indicate that the novel ways of presenting the complex graph improve the prediction process, although the computational complexity should be taken into account when deciding on a particular approach.
| S-EPMC4074043 | biostudies-literature
Project description:Nested sampling is a Bayesian sampling technique developed to explore probability distributions localized in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence (marginal likelihood) of the model. The nested sampling algorithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering. In this article, we describe a parallel implementation of the nested sampling algorithm and its application to the problem of protein folding in a Gō-like force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations. We demonstrate the method by conducting folding simulations on a number of small proteins that are commonly used for testing protein-folding procedures. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high-level description of the potential energy surface for the protein folding simulations. These charts provide qualitative insights into both the folding process and the nature of the model and force field used.
| S-EPMC3283771 | biostudies-literature
Project description:Despite an increasingly vast literature on cophylogenetic reconstructions for studying host-parasite associations, understanding the common evolutionary history of such systems remains a problem that is far from being solved. Most algorithms for host-parasite reconciliation use an event-based model, where the events include in general (a subset of) cospeciation, duplication, loss, and host switch. All known parsimonious event-based methods then assign a cost to each type of event in order to find a reconstruction of minimum cost. The main problem with this approach is that the cost of the events strongly influences the reconciliation obtained. Some earlier approaches attempt to avoid this problem by finding a Pareto set of solutions and hence by considering event costs under some minimization constraints. To deal with this problem, we developed an algorithm, called Coala, for estimating the frequency of the events based on an approximate Bayesian computation approach. The benefits of this method are 2-fold: (i) it provides more confidence in the set of costs to be used in a reconciliation, and (ii) it allows estimation of the frequency of the events in cases where the data set consists of trees with a large number of taxa. We evaluate our method on simulated and on biological data sets. We show that in both cases, for the same pair of host and parasite trees, different sets of frequencies for the events lead to equally probable solutions. Moreover, often these solutions differ greatly in terms of the number of inferred events. It appears crucial to take this into account before attempting any further biological interpretation of such reconciliations. More generally, we also show that the set of frequencies can vary widely depending on the input host and parasite trees. Indiscriminately applying a standard vector of costs may thus not be a good strategy.
| S-EPMC4395844 | biostudies-literature
Project description:UnlabelledNonprimate hepacivirus (NPHV), the closest homolog of hepatitis C virus (HCV) described to date, has recently been discovered in horses. Even though the two viruses share a similar genomic organization, conservation of the encoded hepaciviral proteins remains undetermined. The HCV p7 protein is localized within endoplasmic reticulum (ER) membranes and is important for the production of infectious particles. In this study, we analyzed the structural and functional features of NPHV p7 in addition to its role during virus assembly. Three-dimensional homology models for NPHV p7 using various nuclear magnetic resonance spectroscopy (NMR) structures were generated, highlighting the conserved residues important for ion channel function. By applying a liposome permeability assay, we observed that NPHV p7 exhibited liposome permeability features similar to those of HCV p7, indicative of similar ion channel activity. Next, we characterized the viral protein using a p7-based trans-complementation approach. A similar subcellular localization pattern at the ER membrane was observed, although production of infectious particles was likely hindered by genetic incompatibilities with HCV proteins. To further characterize these cross-species constraints, chimeric viruses were constructed by substituting different regions of HCV p7 with NPHV p7. The N terminus and transmembrane domains were nonexchangeable and therefore constitute a cross-species barrier in hepaciviral assembly. In contrast, the basic loop and the C terminus of NPHV p7 were readily exchangeable, allowing production of infectious trans-complemented viral particles. In conclusion, comparison of NPHV and HCV p7 revealed structural and functional homology of these proteins, including liposome permeability, and broadly acting determinants that modulate hepaciviral virion assembly and contribute to the host-species barrier were identified.ImportanceThe recent discovery of new relatives of hepatitis C virus (HCV) enables for the first time the study of cross-species determinants shaping hepaciviral pathogenesis. Nonprimate hepacivirus (NPHV) was described to infect horses and represents so far the closest homolog of HCV. Both viruses encode the same viral proteins; however, NPHV protein functions remain poorly understood. In this study, we aimed to dissect NPHV p7 on a structural and functional level. By using various NMR structures of HCV p7 as templates, three-dimensional homology models for NPHV p7 were generated, highlighting conserved residues that are important for ion channel function. A p7-based trans-complementation approach and the construction of NPHV/HCV p7 chimeric viruses showed that the N terminus and transmembrane domains were nonexchangeable. In contrast, the basic loop and the C terminus of NPHV p7 were readily exchangeable, allowing production of infectious viral particles. These results identify species-specific constraints as well as exchangeable determinants in hepaciviral assembly.
| S-EPMC4859704 | biostudies-literature
Project description:BackgroundProtein interactions between voltage-gated sodium (Nav) channels and accessory proteins play an essential role in neuronal firing and plasticity. However, a surprisingly limited number of kinases have been identified as regulators of these molecular complexes. We hypothesized that numerous as-of-yet unidentified kinases indirectly regulate the Nav channel via modulation of the intracellular fibroblast growth factor 14 (FGF14), an accessory protein with numerous unexplored phosphomotifs and required for channel function in neurons.MethodsHere we present results from an in-cell high-throughput screening (HTS) against the FGF14: Nav1.6 complex using >3000 diverse compounds targeting an extensive range of signaling pathways. Regulation by top kinase targets was then explored using in vitro phosphorylation, biophysics, mass-spectrometry and patch-clamp electrophysiology.ResultsCompounds targeting Janus kinase 2 (JAK2) were over-represented among HTS hits. Phosphomotif scans supported by mass spectrometry revealed FGF14Y158, a site previously shown to mediate both FGF14 homodimerization and interactions with Nav1.6, as a JAK2 phosphorylation site. Following inhibition of JAK2, FGF14 homodimerization increased in a manner directly inverse to FGF14:Nav1.6 complex formation, but not in the presence of the FGF14Y158A mutant. Patch-clamp electrophysiology revealed that through Y158, JAK2 controls FGF14-dependent modulation of Nav1.6 channels. In hippocampal CA1 pyramidal neurons, the JAK2 inhibitor Fedratinib reduced firing by a mechanism that is dependent upon expression of FGF14.ConclusionsThese studies point toward a novel mechanism by which levels of JAK2 in neurons could directly influence firing and plasticity by controlling the FGF14 dimerization equilibrium, and thereby the availability of monomeric species for interaction with Nav1.6.
| S-EPMC7984254 | biostudies-literature