How strong is the edge effect in the adsorption of anticancer drugs on a graphene cluster?

The adsorption of nucleobase-analog anticancer drugs (fluorouracil, thioguanine, and mercaptopurine) on a graphene flake (C₅₄H₁₈) was investigated by shifting the site at which adsorption occurs from one end of the sheet to the other end. The counterpoise-corrected M06-2X/cc-pVDZ binding energies revealed that the binding stability decreases in the sequence thioguanine?>?mercaptopurine?>?fluorouracil. We found that adsorption near the middle of the sheet is more favorable than adsorption near the edge due to the edge effect. This edge effect is stronger for the adsorption of thioguanine or mercaptopurine than for fluorouracil adsorption. However, the edge effect reduces the binding energy of the drug to the flake by only a small amount, <5 kcal/mol, depending on the adsorption site and the alignment of the drug at this site.     

Theoretical studies of the role of C-terminal cysteines in the process of <Emphasis Type="Italic">S</Emphasis>-nitrosylation of human Src kinases

Src tyrosine kinases are a family of non-receptor proteins that are responsible for the growth process, cellular proliferation, differentiation and survival. Lack of Src kinase control has been associated with the development of certain human cancers. This family of proteins is constituted of four domains, with SH1 being the kinase or catalytic domain. SH1 also presents three important regulatory sites. Two residues, Tyr416 and Tyr527, are responsible for important phosphorylation processes that lead to, respectively, activation and deactivation of these kinases. More recently, however, a set of four cysteine residues located near the C-terminus-Cys483, Cys487, Cys496 and Cys498-has been associated with the activation of the Src kinases through S-nitrosylation reactions. Particularly, the Cys498 has been specified as a fundamental residue when considering this regulatory mechanism. Aiming to understand the role of these four cysteines in S-nitrosylation, theoretical studies of electrostatic, steric and hydrophobic properties were performed with a sequence of 20 amino acids, enclosing the four cysteine residues under study, extracted from the PDB coordinates of the crystal obtained from the inactive state of Src kinase. Results indicate that Cys498 is buried deeply in the protein, in hydrophobic surroundings in which NO is more likely to suffer decomposition into the electrophilic intermediates known to be responsible for S-nitrosylation reactions. Electronic calculated properties, such as punctual atomic charges, electrostatic potentials and molecular orbital energy, also demonstrated the good nucleophilic potential of Cys498.

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Graphical Abstract Structure of Src kinase with zoomed area representing the 20 amino acids comprising the CC motif extracted from the whole protein structure. Right upper panel Electrostatic potential map, right lower panel hydrophilic map in anterior view

     

Molecular dynamics simulations of a lithium/sodium carbonate mixture

The diffusion and ionic conductivity of Li _x Na_1?x CO₃ salt mixtures were studied by means of Molecular Dynamics (MD) simulations, using the Janssen and Tissen model (Janssen and Tissen, Mol Simul 5:83–98; 1990). These salts have received particular attention due to their central role in fuel cells technology, and reliable numerical methods that could perform as important interpretative tool of experimental data are thus required but still lacking. The chosen computational model nicely reproduces the main structural behaviour of the pure Li₂CO₃, Na₂CO₃ and K₂CO₃ carbonates, but also of their Li/K and Li/Na mixtures. However, it fails to accurately describe dynamic properties such as activation energies of diffusion and conduction processes, outlining the need to develop more accurate models for the simulation of molten salt carbonates.     

DFT investigation on the decarboxylation mechanism of <Emphasis Type="Italic">ortho</Emphasis> hydroxy benzoic acids with acid catalysis

A density functional theory (DFT) study was performed to explore the mechanisms of the acid-catalyzed decarboxylation reaction of salicylic acids using the B3LYP method with 6-31++G(d,p) basis set in both gas phase and aqueous environment. The α-protonated cation of carboxylate acid was formed during the decarboxylation process in acidic conditions, and the presence of hydrogen ions promotes decarboxylation greatly by significantly decreasing the overall reaction energy barriers to 20.98 kcal mol^?1 in gas phase and 20.93 kcal mol^?1 in water, respectively. The hydrogen in the α-carbon came directly from the acid rather than from the carboxyl group in neutral state. Compared with the reaction in gas phase, water in aqueous state causes the reaction to occur more easily. Substituents of methyl group, chlorine and fluorine at the ortho-position to the carboxyl of salicylic acid could further lower the decarboxylation energy barriers and facilitate the reaction.     

Computational prediction of CRISPR cassettes in gut metagenome samples from Chinese type-2 diabetic patients and healthy controls

Background

CRISPR has been becoming a hot topic as a powerful technique for genome editing for human and other higher organisms. The original CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats coupled with CRISPR-associated proteins) is an important adaptive defence system for prokaryotes that provides resistance against invading elements such as viruses and plasmids. A CRISPR cassette contains short nucleotide sequences called spacers. These unique regions retain a history of the interactions between prokaryotes and their invaders in individual strains and ecosystems. One important ecosystem in the human body is the human gut, a rich habitat populated by a great diversity of microorganisms. Gut microbiomes are important for human physiology and health. Metagenome sequencing has been widely applied for studying the gut microbiomes. Most efforts in metagenome study has been focused on profiling taxa compositions and gene catalogues and identifying their associations with human health. Less attention has been paid to the analysis of the ecosystems of microbiomes themselves especially their CRISPR composition.

Results

We conducted a preliminary analysis of CRISPR sequences in a human gut metagenomic data set of Chinese individuals of type-2 diabetes patients and healthy controls. Applying an available CRISPR-identification algorithm, PILER-CR, we identified 3169 CRISPR cassettes in the data, from which we constructed a set of 1302 unique repeat sequences and 36,709 spacers. A more extensive analysis was made for the CRISPR repeats: these repeats were submitted to a more comprehensive clustering and classification using the web server tool CRISPRmap. All repeats were compared with known CRISPRs in the database CRISPRdb. A total of 784 repeats had matches in the database, and the remaining 518 repeats from our set are potentially novel ones.

Conclusions

The computational analysis of CRISPR composition based contigs of metagenome sequencing data is feasible. It provides an efficient approach for finding potential novel CRISPR arrays and for analysing the ecosystem and history of human microbiomes.

     

Generalized logical model based on network topology to capture the dynamical trends of cellular signaling pathways

Background

Cellular responses to extracellular perturbations require signaling pathways to capture and transmit the signals. However, the underlying molecular mechanisms of signal transduction are not yet fully understood, thus detailed and comprehensive models may not be available for all the signaling pathways. In particular, insufficient knowledge of parameters, which is a long-standing hindrance for quantitative kinetic modeling necessitates the use of parameter-free methods for modeling and simulation to capture dynamic properties of signaling pathways.

Results

We present a computational model that is able to simulate the graded responses to degradations, the sigmoidal biological relationships between signaling molecules and the effects of scheduled perturbations to the cells. The simulation results are validated using experimental data of protein phosphorylation, demonstrating that the proposed model is capable of capturing the main trend of protein activities during the process of signal transduction. Compared with existing simulators, our model has better performance on predicting the state transitions of signaling networks.

Conclusion

The proposed simulation tool provides a valuable resource for modeling cellular signaling pathways using a knowledge-based method.

     

Prediction of drugs having opposite effects on disease genes in a directed network

Background

Developing novel uses of approved drugs, called drug repositioning, can reduce costs and times in traditional drug development. Network-based approaches have presented promising results in this field. However, even though various types of interactions such as activation or inhibition exist in drug-target interactions and molecular pathways, most of previous network-based studies disregarded this information.

Methods

We developed a novel computational method, Prediction of Drugs having Opposite effects on Disease genes (PDOD), for identifying drugs having opposite effects on altered states of disease genes. PDOD utilized drug-drug target interactions with ‘effect type’, an integrated directed molecular network with ‘effect type’ and ‘effect direction’, and disease genes with regulated states in disease patients. With this information, we proposed a scoring function to discover drugs likely to restore altered states of disease genes using the path from a drug to a disease through the drug-drug target interactions, shortest paths from drug targets to disease genes in molecular pathways, and disease gene-disease associations.

Results

We collected drug-drug target interactions, molecular pathways, and disease genes with their regulated states in the diseases. PDOD is applied to 898 drugs with known drug-drug target interactions and nine diseases. We compared performance of PDOD for predicting known therapeutic drug-disease associations with the previous methods. PDOD outperformed other previous approaches which do not exploit directional information in molecular network. In addition, we provide a simple web service that researchers can submit genes of interest with their altered states and will obtain drugs seeming to have opposite effects on altered states of input genes at http://gto.kaist.ac.kr/pdod/index.php/main.

Conclusions

Our results showed that ‘effect type’ and ‘effect direction’ information in the network based approaches can be utilized to identify drugs having opposite effects on diseases. Our study can offer a novel insight into the field of network-based drug repositioning.

     

Seasonal change in xylem growth of <Emphasis Type="Italic">Pinus densiflora</Emphasis> in central Japan

This study investigated the seasonal change in xylem growth of Japanese red pine (Pinus densiflora). Wood cores were sampled at 2-week intervals from April to November in 2012 using the microcoring method. Daily increment rates of tracheid number and tree-ring width were compared with seasonal changes in daily mean temperature and photoperiod. Xylem growth started in early to late May and stopped in late October to early November. The maximum daily increment rates of tracheid number and tree-ring width were in early July. The 95 % confidence intervals of the timing of the maximum daily increment rates included the summer solstice (23 June) with the longest photoperiod, but not the warmest day (30 July). The maximum daily increment rate of xylem growth is thought to be controlled by the photoperiod rather than by temperature. The daily mean temperature exceeded 20 °C after the summer solstice, indicating that temperature is not a limiting factor for xylem growth. This study suggests that the timing of maximum daily increment rates of xylem growth of P. densiflora is controlled by the photoperiod.     

Establishment of laurel forest vegetation in adjacent secondary forest in central Japan

Distributions of lucidophyllous species are limited due to the fragmentation of laurel forest. On Komayama Hill in central Japan, we evaluated the colonization of typical lucidophyllous vascular plants from a 350-year-old laurel forest into adjacent abandoned secondary forest for conservation and restoration purposes. A total of 14 consecutive subplots were established along the vegetation border between the two forests (length, 30 m; width, 5 m), extending 70 m into the secondary forest; 18 quadrats of old-growth forest were surveyed. Edge effects of old-growth forest were found to play an important role in re-establishing lucidophyllous saplings and seedlings in the secondary forest. In particular, the abundances of the four dominant canopy species of the old-growth forest significantly decreased with increasing distance. Hence, they are expected to colonize further into the secondary forest and, ultimately, to dominate the canopy. However, the number of lucidophyllous species did not change with distance. Species such as Ficus nipponica, Damnacanthus indicus, Ilex integra, and Lemmaphyllum microphyllum were near-completely or completely limited to the old-growth forest. They are known to be negatively affected by forest fragmentation and were observed to be struggling to colonize the exterior of the old-growth forest even after 60 years of abandonment. Their absence highlighted the limited colonization capacities of some old-growth forest species and underlined the time required for habitat restoration following human disturbance. We conclude that it is important to consider the population dynamics of dominant canopy species and the colonization of these interior species when assessing the habitat expansion of lucidophyllous species and hence the restoration of degraded lands.     

Multiple Hypotheses in the Analysis of a Crossover Trial

Crossover trials are used in a variety of fields, such as medicine, biology, psychology, and some commercial goods investigations. The aim of this paper is to extend a methodology for multiple comparisons to the problem of testing in crossover trials with two treatments. These two treatments are given in two orderings, treatment A first or treatment B first. We perform inference on the effect of one treatment relative to the effect of the other, without assuming that these effects are independent of treatment ordering, using techniques from order-restricted inference and multiple comparisons, and compare to some existing multiple comparison tests.