Deciphering structural stability and binding mechanisms of potential antagonists with smoothened protein

Identification of new potential inhibitors against Hedgehog pathway activator protein Smoothened (SMO) is considered to be of higher importance to improvise the future cancer therapeutics. Different SMO inhibitors/drugs (e.g. Cyclopamine, Vismodegib, Taladegib) used till date are found to be associated with several drug-related resistivity and toxicity. To explore the ability of new drug/inhibitor molecules, which can show better/similar binding and dynamic stability as compared to known inhibitors, virtual screening against SMO is performed followed by the comparative docking and molecular dynamic studies. ‘ZINC12368305’ is found to be the best molecule among the entire data-set, as it shows the highest binding affinity and stable conformations. Here, an integrative approach using Dynamic Graph Theory is introduced to gain the molecular insights of the structural integrity of these protein complexes at the residue level by analyzing the corresponding Protein Contact Networks along the Molecular Dynamics trajectories. The study further focuses to understand the detailed binding mechanisms of available inhibitor/drug molecules along with the newly predicted molecule. It is observed that a unique big cluster of low fluctuating residues at the vicinity of the drug binding pocket of the SMO in ZINC12368305-bound complex is present and driving it toward a more stable region. A close inspection on this site reveals the presence of a stable Pi–Pi interaction between the pyrazole group-associated phenanthrene ring of ZINC12368305 and aromatic ring of Phe484 of SMO, which could be the potential factor of ZINC12368305 to create a more stable complex with SMO as compared to the other inhibitors.     

一个基于基因表达谱的基因逻辑网络模型的建立与应用

基因之间除了线性关联作用关系外,还存在着非线性的逻辑关系.用这种逻辑关系构建的生物系统网络模型对研究细胞内的各种生物通路和细胞分子网络非常重要.首先,根据图着色原理确定了基因的低阶和高阶逻辑关系,然后应用结肠癌基因表达谱数据分析了51个癌基因和抑癌基因的逻辑关系,在此基础上构建了结肠癌基因表达的逻辑网络.通过这个网络模型发现了与KEGG数据库中结肠癌通路一致的转化生长因子信号通路,并分析了各生物通路成员之间错综复杂的关系.实验结果表明,基因逻辑网络模型在一定程度上揭示了结肠癌基因和抑癌基因之间并行、分叉等复杂的相互作用关系,反映了结肠癌发病的复杂分子机制,为分子生物医学家提供了一个参考模型.     

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure

Recent advances in sequencing allow population‐genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction‐site‐associated DNA sequence (RAD‐seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well‐characterized single nucleotide polymorphism (SNP) data set from 21 three‐spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single‐outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population‐genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population‐demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population‐genomic data set, making it especially valuable for nonmodel species.     

An edge-centric perspective on the human connectome: link communities in the brain

Brain function depends on efficient processing and integration of information within a complex network of neural interactions, known as the connectome. An important aspect of connectome architecture is the existence of community structure, providing an anatomical basis for the occurrence of functional specialization. Typically, communities are defined as groups of densely connected network nodes, representing clusters of brain regions. Looking at the connectome from a different perspective, instead focusing on the interconnecting links or edges, we find that the white matter pathways between brain regions also exhibit community structure. Eleven link communities were identified: five spanning through the midline fissure, three through the left hemisphere and three through the right hemisphere. We show that these link communities are consistently identifiable and investigate the network characteristics of their underlying white matter pathways. Furthermore, examination of the relationship between link communities and brain regions revealed that the majority of brain regions participate in multiple link communities. In particular, the highly connected and central hub regions showed a rich level of community participation, supporting the notion that these hubs play a pivotal role as confluence zones in which neural information from different domains merges.     

太白山针叶林的Fuzzy分类研究

应用模糊聚类分析法和模糊图论分析对太白山针叶林进行了数量分类比较研究。将２６个样地分为两大类共７个群落类型。研究结果表明,两种方法在植物群落分类研究中,不但是可行的,而且所分类的实际结果是等价的,与实际观测情况也是吻合的。其中的图论法直接依据模糊相似系数得到树状图,简便易行,显示出更大的适用性。     

ploidyfrost: Reference-free estimation of ploidy level from whole genome sequencing data based on de Bruijn graphs

Polyploidy is ubiquitous and its consequences are complex and variable. A change of ploidy level generally influences genetic diversity and results in morphological, physiological and ecological differences between cells or organisms with different ploidy levels. To avoid cumbersome experiments and take advantage of the less biased information provided by the vast amounts of genome sequencing data, computational tools for ploidy estimation are urgently needed. Until now, although a few such tools have been developed, many aspects of this estimation, such as the requirement of a reference genome, the lack of informative results and objective inferences, and the influence of false positives from errors and repeats, need further improvement. We have developed ploidyfrost , a de Bruijn graph-based method, to estimate ploidy levels from whole genome sequencing data sets without a reference genome. ploidyfrost provides a visual representation of allele frequency distribution generated using the ggplot2 package as well as quantitative results using the Gaussian mixture model. In addition, it takes advantage of colouring information encoded in coloured de Bruijn graphs to analyse multiple samples simultaneously and to flexibly filter putative false positives. We evaluated the performance of ploidyfrost by analysing highly heterozygous or repetitive samples of Cyclocarya paliurus and a complex allooctoploid sample of Fragaria × ananassa. Moreover, we demonstrated that the accuracy of analysis results can be improved by constraining a threshold such as Cramér's V coefficient on variant features, which may significantly reduce the side effects of sequencing errors and annoying repeats on the graphical structure constructed.     

High levels of arbuscular mycorrhizal fungus colonization on Medicago truncatula reduces plant suitability as a host for pea aphids (Acyrthosiphon pisum)

This study sheds light on a poorly understood area in insect-plant-microbe interactions,focusing on aphid probing and feeding behavior on plants with varying levels of arbuscular mycorrhizal(AM)fungus root colonization.It investigates a commonly occurring interaction of three species:pea aphid Acyrthosiphon pisum,barrel medic Medicago truncatula,and the AM fungus Rhizophagus irregularis,examining whether aphid-feeding behavior changes when insects feed on plants at different levels of AM fungus colonization(42% and 84% root length colonized).Aphid probing and feeding behavior was monitored throughout 8 h of recording using the electrical penetration graph(EPG)technique,also,foliar nutrient content and plant growth were measured.Summarizing,aphids took longer to reach their 1st sustained phloem ingestion on the 84% AM plants than on the 42% AM plants or on controls.Less aphids showed phloem ingestion on the 84% AM plants relative to the 42% AM plants.Shoots of the 84% AM plants had higher percent carbon(43.7%)relative to controls(40.5%),and the 84% AM plants had reduced percent nitrogen(5.3%)relative to the 42% AM plants(6%).In conclusion,EPG and foliar nutrient data support the hypothesis that modifications in plant anatomy(e.g.,thicker leaves),and poor food quality(reduced nitrogen)in the 84% AM plants contribute to reduced aphid success in locating phloem and ultimately to differences in phloem sap ingestion.This work suggests that M.truncatula plants benefit from AM symbiosis not only because of increased nutrient uptake but also because of reduced susceptibility to aphids.     

An Ancestral Recombination Graph for Diploid Populations with Skewed Offspring Distribution

A large offspring-number diploid biparental multilocus population model of Moran type is our object of study. At each time step, a pair of diploid individuals drawn uniformly at random contributes offspring to the population. The number of offspring can be large relative to the total population size. Similar “heavily skewed” reproduction mechanisms have been recently considered by various authors (cf. e.g., Eldon and Wakeley 2006, 2008) and reviewed by Hedgecock and Pudovkin (2011). Each diploid parental individual contributes exactly one chromosome to each diploid offspring, and hence ancestral lineages can coalesce only when in distinct individuals. A separation-of-timescales phenomenon is thus observed. A result of Möhle (1998) is extended to obtain convergence of the ancestral process to an ancestral recombination graph necessarily admitting simultaneous multiple mergers of ancestral lineages. The usual ancestral recombination graph is obtained as a special case of our model when the parents contribute only one offspring to the population each time. Due to diploidy and large offspring numbers, novel effects appear. For example, the marginal genealogy at each locus admits simultaneous multiple mergers in up to four groups, and different loci remain substantially correlated even as the recombination rate grows large. Thus, genealogies for loci far apart on the same chromosome remain correlated. Correlation in coalescence times for two loci is derived and shown to be a function of the coalescence parameters of our model. Extending the observations by Eldon and Wakeley (2008), predictions of linkage disequilibrium are shown to be functions of the reproduction parameters of our model, in addition to the recombination rate. Correlations in ratios of coalescence times between loci can be high, even when the recombination rate is high and sample size is large, in large offspring-number populations, as suggested by simulations, hinting at how to distinguish between different population models.