Enhanced conformational space sampling improves the prediction of chemical shifts in proteins.

A biased-potential molecular dynamics simulation method, accelerated molecular dynamics (AMD), was combined with the chemical shift prediction algorithm SHIFTX to calculate (1)H(N), (15)N, (13)Calpha, (13)Cbeta, and (13)C' chemical shifts of the ankyrin repeat protein IkappaBalpha (residues 67-206), the primary inhibitor of nuclear factor kappa-B (NF-kappaB). Free-energy-weighted molecular ensembles were generated over a range of acceleration levels, affording systematic enhancement of the conformational space sampling of the protein. We have found that the predicted chemical shifts, particularly for the (15)N, (13)Calpha, and (13)Cbeta nuclei, improve substantially with enhanced conformational space sampling up to an optimal acceleration level. Significant improvement in the predicted chemical shift data coincides with those regions of the protein that exhibit backbone dynamics on longer time scales. Interestingly, the optimal acceleration level for reproduction of the chemical shift data has previously been shown to best reproduce the experimental residual dipolar coupling (RDC) data for this system, as both chemical shift data and RDCs report on an ensemble and time average in the millisecond range

Functional dynamics of the folded ankyrin repeats of I kappa B alpha revealed by nuclear magnetic resonance.

Inhibition of nuclear factor kappaB (NF-kappaB) is mainly accomplished by IkappaB alpha, which consists of a signal response sequence at the N-terminus, a six-ankyrin repeat domain (ARD) that binds NF-kappaB, and a C-terminal PEST sequence. Previous studies with the ARD revealed that the fifth and sixth repeats are only partially folded in the absence of NF-kappaB. Here we report NMR studies of a truncated version of IkappaB alpha, containing only the first four ankyrin repeats, IkappaB alpha(67-206). This four-repeat segment is well-structured in the free state, enabling full resonance assignments to be made. H-D exchange, backbone dynamics, and residual dipolar coupling (RDC) experiments reveal regions of flexibility. In addition, regions consistent with the presence of micro- to millisecond motions occur periodically throughout the repeat structure. Comparison of the RDCs with the crystal structure gave only moderate agreement, but an ensemble of structures generated by accelerated molecular dynamics gave much better agreement with the measured RDCs. The regions showing flexibility correspond to those implicated in entropic compensation for the loss of flexibility in ankyrin repeats 5 and 6 upon binding to NF-kappaB. The regions showing micro- to millisecond motions in the free protein are the ends of the beta-hairpins that directly interact with NF-kappaB in the complex

Mechanism of glycan receptor recognition and specificity switch for avian, swine, and human adapted influenza virus hemagglutinins: a molecular dynamics perspective.

Hemagglutinins (HA's) from duck, swine, and human influenza viruses have previously been shown to prefer avian and human glycan receptor analogues with distinct topological profiles, pentasaccharides LSTa (alpha-2,3 linkage) and LSTc (alpha-2,6 linkage), in comparative molecular dynamics studies. On the basis of detailed analyses of the dynamic motions of the receptor binding domains (RBDs) and interaction energy profiles with individual glycan residues, we have identified approximately 30 residue positions in the RBD that present distinct profiles with the receptor analogues. Glycan binding constrained the conformational space sampling by the HA. Electrostatic steering appeared to play a key role in glycan binding specificity. The complex dynamic behaviors of the major SSE and trimeric interfaces with or without bound glycans suggested that networks of interactions might account for species specificity in these low affinity and high avidity (multivalent) interactions between different HA and glycans. Contact frequency, energetic decomposition, and H-bond analyses revealed species-specific differences in HA-glycan interaction profiles, not readily discernible from crystal structures alone. Interaction energy profiles indicated that mutation events at the set of residues such as 145, 156, 158, and 222 would favor human or avian receptor analogues, often through interactions with distal asialo-residues. These results correlate well with existing experimental evidence, and suggest new opportunities for simulation-based vaccine and drug development

Integrin and cytoskeletal regulation of growth factor signaling to the MAP kinase pathway

Integrin-mediated anchorage of NIH3T3 fibroblasts to the extracellular matrix component fibronectin permits efficient growth factor signaling to the p42 and p44 forms of mitogen-activated protein kinase (MAPK). Since integrins bridge the extracellular matrix to focal adhesion sites and to the actin cytoskeleton, we analyzed the role of these integrin-associated structures in efficient growth factor activation of p42 and p44-MAPKs. Use of specific reagents that disrupt actin stress fiber and focal adhesion formation demonstrated that upon readhesion of NIH3T3 cells to fibronectin, cells that were poorly spread and lacked prominent focal adhesions but that formed cortical actin structures, efficiently signaled to p42 and p44-MAPKs upon EGF stimulation. In contrast, failure to form the cortical actin structures, despite attachment to fibronectin, precluded effective EGF signaling to p42 and p44-MAPKs. Actin cytoskeletal changes induced by expression of dominant-negative and constitutively active forms of Rho GTPases did not alter EGF activation of MAPK in adherent cells. However, active Cdc42, but not active Rac1 or RhoA, partially rescued EGF signaling to p44-MAPK in cells maintained in suspension. These data indicate that a limited degree of adhesion-mediated cytoskeletal organization and focal adhesion complex formation are required for efficient EGF activation of p42 and p44-MAPKs. Our studies exclude a major role for the GTPases RhoA and Rac1 in the formation of cytoskeletal structures relevant for signaling, but indicate that structures regulated by Cdc42 enhance the ability of suspension cells to activate MAPK in response to growth factors

Novel statistical approaches for non-normal censored immunological data: analysis of cytokine and gene expression data

Background: For several immune-mediated diseases, immunological analysis will become more complex in the future with datasets in which cytokine and gene expression data play a major role. These data have certain characteristics that require sophisticated statistical analysis such as strategies for non-normal distribution and censoring. Additionally, complex and multiple immunological relationships need to be adjusted for potential confounding and interaction effects. Objective: We aimed to introduce and apply different methods for statistical analysis of non-normal censored cytokine and gene expression data. Furthermore, we assessed the performance and accuracy of a novel regression approach in order to allow adjusting for covariates and potential confounding. Methods: For non-normally distributed censored data traditional means such as the Kaplan-Meier method or the generalized Wilcoxon test are described. In order to adjust for covariates the novel approach named Tobit regression on ranks was introduced. Its performance and accuracy for analysis of non-normal censored cytokine/gene expression data was evaluated by a simulation study and a statistical experiment applying permutation and bootstrapping. Results: If adjustment for covariates is not necessary traditional statistical methods are adequate for non-normal censored data. Comparable with these and appropriate if additional adjustment is required, Tobit regression on ranks is a valid method. Its power, type-I error rate and accuracy were comparable to the classical Tobit regression. Conclusion: Non-normally distributed censored immunological data require appropriate statistical methods. Tobit regression on ranks meets these requirements and can be used for adjustment for covariates and potential confounding in large and complex immunological datasets

Computing power of quantitative trait locus association mapping for haploid loci

<p>Abstract</p> <p>Background</p> <p>Statistical power calculations are a critical part of any study design for gene mapping. Most calculations assume that the locus of interest is biallelic. However, there are common situations in human genetics such as X-linked loci in males where the locus is haploid. The purpose of this work is to mathematically derive the biometric model for haploid loci, and to compute power for QTL mapping when the loci are haploid.</p> <p>Results</p> <p>We have derived the biometric model for power calculations for haploid loci and have developed software to perform these calculations. We have verified our calculations with independent mathematical methods.</p> <p>Conclusion</p> <p>Our results fill a need in power calculations for QTL mapping studies. Furthermore, failure to appropriately model haploid loci may cause underestimation of power.</p

Automatically extracting functionally equivalent proteins from SwissProt

In summary, FOSTA provides an automated analysis of annotations in UniProtKB/Swiss-Prot to enable groups of proteins already annotated as functionally equivalent, to be extracted. Our results demonstrate that the vast majority of UniProtKB/Swiss-Prot functional annotations are of high quality, and that FOSTA can interpret annotations successfully. Where FOSTA is not successful, we are able to highlight inconsistencies in UniProtKB/Swiss-Prot annotation. Most of these would have presented equal difficulties for manual interpretation of annotations. We discuss limitations and possible future extensions to FOSTA, and recommend changes to the UniProtKB/Swiss-Prot format, which would facilitate text-mining of UniProtKB/Swiss-Prot

Integrating personality research and animal contest theory: aggressiveness in the green swordtail <i>Xiphophorus helleri</i>

&lt;p&gt;Aggression occurs when individuals compete over limiting resources. While theoretical studies have long placed a strong emphasis on context-specificity of aggression, there is increasing recognition that consistent behavioural differences exist among individuals, and that aggressiveness may be an important component of individual personality. Though empirical studies tend to focus on one aspect or the other, we suggest there is merit in modelling both within-and among-individual variation in agonistic behaviour simultaneously. Here, we demonstrate how this can be achieved using multivariate linear mixed effect models. Using data from repeated mirror trials and dyadic interactions of male green swordtails, &lt;i&gt;Xiphophorus helleri&lt;/i&gt;, we show repeatable components of (co)variation in a suite of agonistic behaviour that is broadly consistent with a major axis of variation in aggressiveness. We also show that observed focal behaviour is dependent on opponent effects, which can themselves be repeatable but were more generally found to be context specific. In particular, our models show that within-individual variation in agonistic behaviour is explained, at least in part, by the relative size of a live opponent as predicted by contest theory. Finally, we suggest several additional applications of the multivariate models demonstrated here. These include testing the recently queried functional equivalence of alternative experimental approaches, (e. g., mirror trials, dyadic interaction tests) for assaying individual aggressiveness.&lt;/p&gt