Nitric oxide-A novel therapeutic for cancer.

Much research over the past two decades has focussed on understanding the complex interactions of nitric oxide (NO()) in both physiological and pathological processes. As with many other aspects of NO() biology, its precise role in tumour pathophysiology has been the cause of intense debate and we now know that it participates in numerous signalling pathways that are crucial to the malignant character of cancer. The available experimental evidence highlights contrasting pro- and anti-tumour effects of NO() expression, which appear to be reconciled by consideration of the concentrations involved. This review addresses the complexities of the role of NO() in cancer, whilst evaluating various experimental approaches to NO()-based cancer therapies, including both inhibition of nitric oxide synthases, and overexpression of NO() using donor drugs or nitric oxide synthase gene transfer. The evidence provided strongly supports a role for manipulation of tumour NO() either as a stand-alone therapy or in combination with conventional treatments to achieve a significant therapeutic gain.

Molecular subtyping of breast cancer: Opportunities for new therapeutic approaches

Evidence is accumulating that breast cancer is not one disease but many separate diseases. DNA microarray-based gene expression profiling has demonstrated subtypes with distinct phenotypic features and clinical responses. Prominent among the new subtypes is 'basal-like' breast cancer, one of the 'intrinsic' subtypes defined by negativity for the estrogen, progesterone, and HER2/neu receptors and positivity for cytokeratins-5/6. Focusing on basal-like breast cancer, we discuss how molecular technologies provide new chemotherapy targets, optimising treatment whilst sparing patients from un-necessary toxicity. Clinical trials are needed that incorporate long-term follow-up of patients with well-characterised tumour markers. Whilst the absence of an obvious dominant oncogene driving basallike breast cancer and the lack of specific therapeutic agents are serious stumbling blocks, this review will highlight several promising therapeutic candidates currently under evaluation. Thus, new molecular technologies should provide a fundamental foundation for better understanding breast and other cancers which may be exploited to save lives.

Molecular dynamics studies of trinucleotide repeat DNA involved in neurodegenerative disorders.

Expansion of trinucleotide repeat DNA of the classes CAG�·CTG, CGG�·CCG and GAA�·TTC are found to be associated with several neurodegenerative disorders. Different mechanisms have been attributed to the expansion of triplets, mainly involving the formation of alternate secondary structures by such repeats. This paper reports the molecular dynamics simulation of triplet repeat DNA sequences to study the basic structural features of DNA that are responsible for the formation of structures such as hairpins and slip-strand DNA leading to expansion. All the triplet repeat sequences studied were found to be more flexible compared to the control sequence unassociated with disease. Moreover, flexibility was found to be in the order CAG�·CTG > CGG�·CCG = GAA�·TTC, the highly flexible CAG�·CTG repeat being the most common cause of neurodegenerative disorders. In another simulation, a single G�·C to T�·A mutation at the 9th position of the CAG�·CTG repeat exhibited a reduction in bending compared to the pure 15-mer CAGâ�¢CTG repeat. EPM1 dodecamer repeat associated with the pathogenesis of progressive myoclonus epilepsy was also simulated and showed flexible nature suggesting a similar expansion mechanism.

Stochastic protein folding simulation in the three-dimensional HP-model

We present results from three-dimensional protein folding simulations in the HP-model on ten benchmark problems. The simulations are executed by a simulated annealing-based algorithm with a time-dependent cooling schedule. The neighbourhood relation is determined by the pull-move set. The results provide experimental evidence that the maximum depth D of local minima of the underlying energy landscape can be upper bounded by D < n(2/3). The local search procedure employs the stopping criterion (In/delta)(D/gamma) where m is an estimation of the average number of neighbouring conformations, gamma relates to the mean of non-zero differences of the objective function for neighbouring conformations, and 1-delta is the confidence that a minimum conformation has been found. The bound complies with the results obtained for the ten benchmark problems. (c) 2008 Elsevier Ltd. All rights reserved.

Population-based local search for protein folding simulation in the MJ energy model and cubic lattices

We present experimental results on benchmark problems in 3D cubic lattice structures with the Miyazawa-Jernigan energy function for two local search procedures that utilise the pull-move set: (i) population-based local search (PLS) that traverses the energy landscape with greedy steps towards (potential) local minima followed by upward steps up to a certain level of the objective function; (ii) simulated annealing with a logarithmic cooling schedule (LSA). The parameter settings for PLS are derived from short LSA-runs executed in pre-processing and the procedure utilises tabu lists generated for each member of the population. In terms of the total number of energy function evaluations both methods perform equally well, however. PLS has the potential of being parallelised with an expected speed-up in the region of the population size. Furthermore, both methods require a significant smaller number of function evaluations when compared to Monte Carlo simulations with kink-jump moves. (C) 2009 Elsevier Ltd. All rights reserved.

Ranking of microRNA target prediction scores by Pareto front analysis

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure. which encourages further research towards a higher-dimensional analysis of Pareto fronts. (C) 2010 Elsevier Ltd. All rights reserved.

Structural information content of networks: Graph entropy based on local vertex functionals

In this paper we define the structural information content of graphs as their corresponding graph entropy. This definition is based on local vertex functionals obtained by calculating-spheres via the algorithm of Dijkstra. We prove that the graph entropy and, hence, the local vertex functionals can be computed with polynomial time complexity enabling the application of our measure for large graphs. In this paper we present numerical results for the graph entropy of chemical graphs and discuss resulting properties. (C) 2007 Elsevier Ltd. All rights reserved.

Molecular Modeling on Inhibitor Complexes and Active-Site Dynamics of Cytochrome P450 C17, a Target for Prostate Cancer Therapy

A molecular model for the P450 enzyme cytochrome P450 C17 (CYP17) is presented based on sequence alignments of multiple template structures and homology modeling. This enzyme plays a central role in the biosynthesis of testosterone and is emerging as a major target in prostate cancer, with the recently developed inhibitor abiraterone currently in advanced clinical trials. The model is described in detail, together with its validation, by providing structural explanations to available site-directed mutagenesis data. The CYP17 molecule in this model is in the form of a triangular prism, with an edge of similar to 55 angstrom and a thickness of similar to 37 angstrom. It is predominantly helical, comprising 13 alpha helices interspersed by six 3(10) helices and 11 beta-sheets. Multinanosecond molecular dynamics simulations in explicit solvent have been carried out, and principal components analysis has been used to reveal the details of dynamics around the active site. Coarse-grained methods have also been used to verify low-frequency motions, which have been correlated with active-site gating. The work also describes the results of docking synthetic inhibitors, including the drug abiraterone and the natural substrate pregnenolone, in the CYP17 active site together with molecular dynamics simulations on the complexes. (C) 2010 Elsevier Ltd. All rights reserved.

Molecular Dynamics of HIV1-Integrase in Complex with 93del - A Structural Perspective on the Mechanism of Inhibition

HIV1 integrase is an important target for the antiviral therapy. Guanine-rich quadruplex, such as 93del, have been shown to be potent inhibitors of this enzyme and thus representing a new class of antiviral agents. Although X-ray and NMR structures of HIV1 integrase and 93del have been reported, there is no structural information of the complex and the mechanism of inhibition still remains unexplored. A number of computational methods including automated protein-DNA docking and molecular dynamics simulation in explicit solvent were used to model the binding of 93del to HIV1 integrase. Analysis of the dynamic behaviour of the complex using principal components analysis and elastic network modelling techniques allow us to understand how the binding of 93del aptamer and its interactions with key residues affect the intrinsic motions of the catalytic loops by stabilising them in catalytically inactive conformations. Such insights into the structural mechanism of inhibition can aid in improving the design of anti-HIV aptamers.

Molecular basis of Yersinia enterocolitica temperature-dependent resistance to antimicrobial peptides

Antimicrobial peptides (APs) belong to the arsenal of weapons of the innate immune system against infections. In the case of gram-negative bacteria, APs interact with the anionic lipid A moiety of the lipopolysaccharide (LPS). In yersiniae most virulence factors are temperature regulated. Studies from our laboratory demonstrated that Yersinia enterocolitica is more susceptible to polymyxin B, a model AP, when grown at 37°C than at 22°C (J. A. Bengoechea, R. Díaz, and I. Moriyón, Infect. Immun. 64:4891-4899, 1996), and here we have extended this observation to other APs, not structurally related to polymyxin B. Mechanistically, we demonstrate that the lipid A modifications with aminoarabinose and palmitate are downregulated at 37°C and that they contribute to AP resistance together with the LPS O-polysaccharide. Bacterial loads of lipid A mutants in Peyer's patches, liver, and spleen of orogastrically infected mice were lower than those of the wild-type strain at 3 and 7 days postinfection. PhoPQ and PmrAB two-component systems govern the expression of the loci required to modify lipid A with aminoarabinose and palmitate, and their expressions are also temperature regulated. Our findings support the notion that the temperature-dependent regulation of loci controlling lipid A modifications could be explained by H-NS-dependent negative regulation alleviated by RovA. In turn, our data also demonstrate that PhoPQ and PmrAB regulate positively the expression of rovA, the effect of PhoPQ being more important. However, rovA expression reached wild-type levels in the phoPQ pmrAB mutant background, hence indicating the existence of an unknown regulatory network controlling rovA expression in this background.

Simulations of Biased Agonists in the β2 Adrenergic Receptor with Accelerated Molecular Dynamics

The biased agonism of the G protein-coupled receptors (GPCRs), where in addition to a traditional G protein-signalling pathway a GPCR promotes intracellular signals though ß-arrestin, is a novel paradigm in pharmacology. Biochemical and biophysical studies have suggested that a GPCR forms a distinct ensemble of conformations signalling through the G protein and ß-arrestin. Here we report on the dynamics of the ß2 adrenergic receptor bound to the ß-arrestin and G protein biased agonists and the empty receptor to further characterize the receptor conformational changes caused by biased agonists. We use conventional and accelerated molecular dynamics (aMD) simulations to explore the conformational transitions of the GPCR from the active state to the inactive state. We found that aMD simulations enable monitoring the transition within the nanosecond timescale while capturing the known microscopic characteristics of the inactive states, such as the ionic lock, the inward position of F6.44, and water clusters. Distinct conformational states are shown to be stabilized by each biased agonist. In particular, in simulations of the receptor with the ß-arrestin biased agonist, N-cyclopentylbutanepherine we observe a different pattern of motions in helix 7 when compared to simulations with the G protein biased agonist, Salbutamol that involves perturbations of the network of interactions within the NPxxY motif. Understanding the network of interactions induced by biased ligands and the subsequent receptor conformational shifts will lead to development of more efficient drugs. © 2013 American Chemical Society

Genetics of Healthy Aging in Europe.The EU-Integrated Project GEHA (GEnetics of Healthy Aging)

The aim of the 5-year European Union (EU)-Integrated Project GEnetics of Healthy Aging (GEHA), constituted by 25 partners (24 from Europe plus the Beijing Genomics Institute from China), is to identify genes involved in healthy aging and longevity, which allow individuals to survive to advanced old age in good cognitive and physical function and in the absence of major age-related diseases. To achieve this aim a coherent, tightly integrated program of research that unites demographers, geriatricians, geneticists, genetic epidemiologists, molecular biologists, bioinfomaticians, and statisticians has been set up. The working plan is to: (a) collect DNA and information on the health status from an unprecedented number of long-lived 90+ sibpairs (n = 2650) and of younger ethnically matched controls (n = 2650) from 11 European countries; (b) perform a genome-wide linkage scannning in all the sibpairs (a total of 5300 individuals); this investigation will be followed by linkage disequilibrium mapping (LD mapping) of the candidate chromosomal regions; (c) study in cases (i.e., the 2650 probands of the sibpairs) and controls (2650 younger people), genomic regions (chromosome 4, D4S1564, chromosome 11, 11.p15.5) which were identified in previous studies as possible candidates to harbor longevity genes; (d) genotype all recruited subjects for apoE polymorphisms; and (e) genotype all recruited subjects for inherited as well as epigenetic variability of the mitochondrial DNA (mtDNA). The genetic analysis will be performed by 9 high-throughput platforms, within the framework of centralized databases for phenotypic, genetic, and mtDNA data. Additional advanced approaches (bioinformatics, advanced statistics, mathematical modeling, functional genomics and proteomics, molecular biology, molecular genetics) are envisaged to identify the gene variant(s) of interest. The experimental design will also allow (a) to identify gender-specific genes involved in healthy aging and longevity in women and men stratified for ethnic and geographic origin and apoE genotype; (b) to perform a longitudinal survival study to assess the impact of the identified genetic loci on 90+ people mortality; and (c) to develop mathematical and statistical models capable of combining genetic data with demographic characteristics, health status, socioeconomic factors, lifestyle habits.

Reactivity of the 4d transition metals toward N hydrogenation and NH dissociation: A DFT-based HSAB analysis

The density functional theory (DFT) based hard-soft acid-base (HSAB) reactivity indices, including the electrophilicity index, have been successfully applied to many areas of molecular chemistry. In this work we test the applicability of such an approach to fundamental surface chemistry. We have considered, as prototypical surface reactions, both the hydrogenation of atomic nitrogen and the dissociative adsorption of the NH molecular radical. By use of a DFT methodology, the minimum energy reaction pathways, and corresponding reaction barriers, of the above reactions over Zr(001), Nb(110), Mo(110), Tc(001), Ru(001), Rh(111), and Pd(111) have been determined. By consideration of the chemical potential and chemical hardness of the surface metal atoms, and the principle of electronegativity equalization, it is found that the charge transferred to the NH radical during the process of dissociative adsorption correlates very well with that determined by Mulliken population analysis. Furthermore, it is found that the stability of the NH/surface transition state complex relates directly to this charge transfer and that the trend in transition state stability predicted by a HSAB; treatment correlates very strongly with that determined by DFT calculations. With regards to N hydrogenation, we find that during the course of the reaction, H loses cohesion to the surface, as it must migrate from a 3-fold hollow site to either a bridge or top site, to react with N. Partial density of states (PDOS) and Mulliken population analysis reveal that this loss of bonding is accompanied by charge transfer from H to the surface metal atoms. Moreover, by simple modeling, we show that the reaction barriers are directly proportional to this mandatory charge transfer. Indeed, it is found that the reaction barriers correlate very well with the electrophilicity index of the metal atoms.