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Journal ArticleDOI

Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review

TL;DR: It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates and an optimized protocol of network-aided drug development is suggested, and a list of systems-level hallmarks of drug quality is provided.
About: This article is published in Pharmacology & Therapeutics.The article was published on 2013-06-01 and is currently open access. It has received 806 citations till now. The article focuses on the topics: Drug development & Drug discovery.

Summary (1 min read)

Introduction

  • Bu koruma, teknik/ bilimsel veriler ışığında ve uzmanlık bilgiyle bir alanın niteliklerinin belirlenmesini sağlamaktadır.
  • Sit alanlarının, niteliği gereği tüm insanlık için ve hatta bugünün insanları kadar gelecek kuşaklar için de önemli değer olarak kabul edilmesi, insanlığın ortak mirası kavramı kapsamında korunmasını gündeme getirmiştir.
  • Buna göre, hak ehliyetine sahip her gerçek ve tüzelkişi idari yargıda taraf olabilir.
  • GÖZÜBÜYÜK, bu noktada davalı idarenin tüzel kişiliğinin bulunmasının zorunlu olmadığına ve hatta davalı idarenin dava dilekçesinde gösterilmesinin dahi gerekli olmadığına 5 dair.

2 ONAR, age, (C.III), s.1783.

  • Bilindiği gibi, 4001 sayılı yasa ile İYUK'ta yapılan değişiklik, iptal davalarında ehliyet hususuna ilişkin yapılan incelemelerde milat kabul edilmekte; bu nedenle de dava ehliyetinin 4001 sayılı yasa öncesi17, 4001 sayılı yasa sonrası18, Anayasa Mahkemesi kararı sonrası 2000 yılına kadar 16 YALTI'nın ifadeleriyle "ülkemizdeki hukuk yapıcı ve uygulayıcıların, yargılama konusundaki kadim mottosu, “yargının iş yükünün azaltılması” üzerine kuruludur.”.
  • GÜNDÜZ'ün haklılıkla ifade ettiği üzere derneklerin dava açma ehliyetini, derneğin tüzel kişiliğini ilgilendiren işlemlere karşı, derneğin üyelerinin genelini ilgilendiren işlemlere karşı, dernek üyelerinin bir kısmını ilgilendiren işlemlere karşı, derneği ve üyelerini ilgilendirmeyen işlemlere karşı ayrı ayrı ele alarak değerlendirmek gereklidir.
  • Diğer yandan kararlardaki farklılıklar nedeniyle dernek tüzüğünün yeterli olmadığı ve dava konusunun dernek üyelerinin genelini ilgilendirmesinin de arandığı kararlar da bulunmaktadır.
  • 60 Paralel bir hüküm, 58 Taraflar, bilirkişiye veya raporuna itiraz edebilirler.

70 Atalay, age, s.1924.

  • Buna göre Mahkeme, "kamu yararının gerektirmesi, hukuk devleti kavramıyla bağdaşmayacak sonuçlara yol açma olasılığının bulunup bulunmaması, adalet duygusunu rencide edip etmemesi, hak arama özgürlüğünü kısıtlayıp kısıtlamaması, davaların hızlandırılması, mahkemelerin iş yükünün azaltılması" gerekçelerinin kümülatif olarak yer aldığı durumlarda, mahkemelerin verdiği kararlara karşı yasa koyucunun kanun yollarını kapatabileceğine hükmetmiştir.
  • Bunlardan ilki, sit kararları hakkında verilen yargı kararlarının kanun yollarından istinaf müessesesi aracılığıyla maddi ve hukuki olgular yönünden yeniden incelenecek olmasıdır.

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Citations
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Journal ArticleDOI
TL;DR: In this paper, the state-of-the-art algorithms for vital node identification in real networks are reviewed and compared, and extensive empirical analyses are provided to compare well-known methods on disparate real networks.

919 citations

Journal ArticleDOI
TL;DR: This review clarifies the concepts and metrics, classify the problems and methods, as well as review the important progresses and describe the state of the art, and provides extensive empirical analyses to compare well-known methods on disparate real networks and highlight the future directions.
Abstract: Real networks exhibit heterogeneous nature with nodes playing far different roles in structure and function. To identify vital nodes is thus very significant, allowing us to control the outbreak of epidemics, to conduct advertisements for e-commercial products, to predict popular scientific publications, and so on. The vital nodes identification attracts increasing attentions from both computer science and physical societies, with algorithms ranging from simply counting the immediate neighbors to complicated machine learning and message passing approaches. In this review, we clarify the concepts and metrics, classify the problems and methods, as well as review the important progresses and describe the state of the art. Furthermore, we provide extensive empirical analyses to compare well-known methods on disparate real networks, and highlight the future directions. In despite of the emphasis on physics-rooted approaches, the unification of the language and comparison with cross-domain methods would trigger interdisciplinary solutions in the near future.

542 citations


Cites background from "Structure and dynamics of molecular..."

  • ...Additionally, previously known results suggest that essential proteins have correlations with human disease genes [339], and thus the identification of essential proteins is helpful to find drug target candidates in anti-infectious and anti-cancer therapies [21]....

    [...]

  • ...Indeed, to identify vital nodes associated with some certain structural or functional objectives is very significant, which allows us to better control the outbreak of epidemics [13,14], conduct successful advertisements for e-commercial products [15,16], prevent catastrophic outages in power grids or the Internet [17–19], optimize the use of limited resources to facilitate information propagation [20], discover drug target candidates and essential proteins [21], maintain the connectivity or design strategies for connectivity breakdowns in communication networks [22–24], identify the best player from the records of professional sport competitions [25], and predict successful scientists as well as popular scientific publications based on co-authorship and citation networks [26–28] (to name just a few, see more examples in Section 10)....

    [...]

Journal ArticleDOI
TL;DR: All these approaches to genetic analysis using networks are variations of a unifying mathematical machinery — network propagation — suggesting that it is a powerful data transformation method of broad utility in genetic research.
Abstract: Biological networks are powerful resources for the discovery of genes and genetic modules that drive disease. Fundamental to network analysis is the concept that genes underlying the same phenotype tend to interact; this principle can be used to combine and to amplify signals from individual genes. Recently, numerous bioinformatic techniques have been proposed for genetic analysis using networks, based on random walks, information diffusion and electrical resistance. These approaches have been applied successfully to identify disease genes, genetic modules and drug targets. In fact, all these approaches are variations of a unifying mathematical machinery - network propagation - suggesting that it is a powerful data transformation method of broad utility in genetic research.

502 citations

Journal ArticleDOI
TL;DR: A family of H-indices are obtained that can be used to measure a node's importance and it is proved that the convergence to coreness can be guaranteed even under an asynchronous updating process, allowing a decentralized local method of calculating a nodes' coreness in large-scale evolving networks.
Abstract: Identifying influential nodes in dynamical processes is crucial in understanding network structure and function. Degree, H-index and coreness are widely used metrics, but previously treated as unrelated. Here we show their relation by constructing an operator , in terms of which degree, H-index and coreness are the initial, intermediate and steady states of the sequences, respectively. We obtain a family of H-indices that can be used to measure a node's importance. We also prove that the convergence to coreness can be guaranteed even under an asynchronous updating process, allowing a decentralized local method of calculating a node's coreness in large-scale evolving networks. Numerical analyses of the susceptible-infected-removed spreading dynamics on disparate real networks suggest that the H-index is a good tradeoff that in many cases can better quantify node influence than either degree or coreness.

486 citations

Journal ArticleDOI
TL;DR: The results show consistency among literature curated resources, biological properties of the proteins and interactions covered, and the combined network: Omnipath and pypath.
Abstract: Supplementary Results • S13 Sup. Results 1 • Classification of the resources • S13 Sup. Results 2 • Literature curated signaling resources • S13 Sup. Results 3 • Uses of the different pathway resources • S17 Sup. Results 4 • Benchmarking pathway resources • S18 Sup. Results 4.1 • Consistency among literature curated resources • S18 Sup. Results 4.2 • Analysing occurrence of high-throughput interactions • S18 Sup. Results 4.3 • What do the PubMed IDs tell us? • S20 Sup. Results 4.4 • Biological properties of the proteins and interactions covered • S20 Sup. Results 5 • The combined network: Omnipath and pypath • S25

413 citations

References
More filters
Journal ArticleDOI
04 Mar 2011-Cell
TL;DR: Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.

51,099 citations

Journal ArticleDOI
04 Jun 1998-Nature
TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Abstract: Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.

39,297 citations


"Structure and dynamics of molecular..." refers background in this paper

  • ...The global topology of most real world networks is characterized by the small world property first generalized in the landmark paper of Watts and Strogatz (1998)....

    [...]

Journal ArticleDOI
15 Oct 1999-Science
TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Abstract: Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

33,771 citations


"Structure and dynamics of molecular..." refers background in this paper

  • ...Real world networks often have a scale-free degree distribution providing a non-negligible probability for the occurrence of hubs, as it was first generalized to real world networks by the seminal paper of Barabási and Albert (1999)....

    [...]

Journal ArticleDOI
07 Jan 2000-Cell
TL;DR: This work has been supported by the Department of the Army and the National Institutes of Health, and the author acknowledges the support and encouragement of the National Cancer Institute.

28,811 citations

Journal ArticleDOI
TL;DR: In this article, three distinct intuitive notions of centrality are uncovered and existing measures are refined to embody these conceptions, and the implications of these measures for the experimental study of small groups are examined.

14,757 citations


"Structure and dynamics of molecular..." refers background in this paper

  • ...Recently a number of centralitymeasures have beendefined based on network dynamics (Freeman, 1978; Estrada & Rodríguez-Velázquez, 2005; Estrada, 2006; Hwang et al., 2008; Kovács et al., 2010; Du et al., 2012; Ghosh & Lerman, 2012; Grady et al., 2012; Grassler et al., 2012; Joseph&Chen,…...

    [...]

Frequently Asked Questions (18)
Q1. What are the contributions in "Structure and dynamics of molecular networks: a novel paradigm of drug discovery" ?

In this paper, the authors highlight the promises and perspectives of network-aided drug development and highlight the promising and perspectives. 

Sampling bias, missing interactions and false positives are all important factors influencing the robustness of interactome results. 

designing drugs for a group of targets with similar binding sites is challenging due to low specificity as exemplified by the drug design efforts against the ATP binding sites of protein kinases. 

Improving the quality of target selection is widely considered as the single most important factor to improve the productivity of the pharmaceutical industry. 

mRNA expression patterns, genome-wide association studies (GWAS) of disease-associated single-nucleotide polymorphisms (SNPs) and disease-related changes in posttranslational modifications (such as the phospho-proteome) are just three of the most widely used datasets, which may also include system-wide changes of subcellular localization. 

The identification of polar ‘emphatic’ fragments anchoring chemicals to serum albumin and hydrophobic fragments determining albumin binding was an important step in network-related prediction of bioavailability. 

Proteins are the major targets of drug action, and therefore the description of their structure and dynamics has a crucial importance in the determination of drug binding sites, as well as in prediction of drug effects at the sub-molecular level. 

The number of neighbors in protein–protein interaction networks is an important network measure of essentiality (Jeong et al., 2001). 

Some of the major health challenges, such as many types of cancers and infectious diseases, diabetes and neurodegenerative diseases are in desperate need of innovative medicines. 

Another important application of QSAR-related similarity networks is the molecular fragment network of human serum albumin binding defined by Estrada et al. (2006). 

when inhibitors of a specific cancer hallmark are used separately, they may even strengthen another hallmark, like certain types of angiogenesis inhibitors increased the rate of metastasis. 

• Protein binding site similarity networks may be constructed using a simplified representation of binding sites as geometric patterns, or numerical fingerprints. 

Tuske et al. (2004) defined the substrate-envelope for HIV reverse transcriptase as the space occupied by various conformations of naturally occurring ligands and their targets. 

The applicability of network analysis in drug design is determined by the following major factors: 1.) proper definition of network nodes, edges and edge weights; 2.) data quality and carefully defined, uniformly applied data inclusion criteria; 3.) data refinement by genetic variability, aging, environmental effects and compounding pathologies such as bacterial or viral infections (Arrell & Terzic, 2010; Kolodkin et al., 2012). 

Target sets, which are highly relevant at the systems-level, but have diverse binding site structures may require the identification of a set of indirect targets selectively influencing the desired target set, but posing a more feasible lead development task. 

Suthram et al. (2010) identified 59 core modules out of the 4620 modules of the human interactome, which were affected by mRNA changes in more than half of the 54 diseases examined. 

Suthram et al. (2010) identified 59 modules out of the 4620 modules of the human interactome, which are dysregulated in at least half of the 54 diseases tested, and were enriched in known drug targets. 

As the pharmacologist and Nobel Laureate James Black said: “themost fruitful basis for the discovery of a new drug is to start with an old drug” (Chong & Sullivan,2007).