Structure of Protein Interaction Networks and Their Implications on Drug Design
Publication Date
October 30, 2009
Journal
PLOS Computational Biology
Authors
Takeshi Hase, Hiroshi Tanaka, Yasuhiro Suzuki, So Nakagawa, et al
Volume
5
Issue
10
Pages
e1000550
DOI
https://dx.plos.org/10.1371/journal.pcbi.1000550
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1000550
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/19876376
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2760708
Europe PMC
http://europepmc.org/abstract/MED/19876376
Web of Science
000272033100030
Scopus
73549090972
Mendeley
http://www.mendeley.com/research/structure-protein-interaction-networks-implications-drug-design
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CiteULike | Further Information

Mendeley | Further Information

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CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/877329"], "description"=>"<p><i>P</i><sub>n</sub>(<i>k</i>) gives the probability that a link of a <i>k</i>-degree node is a link to a node in each sub-network of the yeast (left) and human (right) PINs. The value of <i>P</i><sub>n</sub>(<i>k</i>) is calculated for a sub-network consisting of high-degree nodes, that consisting of middle-degree nodes, and that consisting of low-degree nodes. (A) Distribution of <i>P</i><sub>n</sub>(<i>k</i>) for the high-degree sub-network. (B) Distribution of <i>P</i><sub>n</sub>(<i>k</i>) for the middle-degree sub-network. (C) Distribution of <i>P</i><sub>n</sub>(<i>k</i>) for the low-degree sub-network.</p>", "links"=>[], "tags"=>["connectivity"], "article_id"=>547789, "categories"=>["Genetics", "Biological Sciences"], "users"=>["Takeshi Hase", "Hiroshi Tanaka", "Yasuhiro Suzuki", "So Nakagawa", "Hiroaki Kitano"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000550.g001", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Degree_dependent_connectivity_chart_/547789", "title"=>"Degree dependent connectivity chart.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-10-30 02:09:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/435067", "https://ndownloader.figshare.com/files/435144", "https://ndownloader.figshare.com/files/435195", "https://ndownloader.figshare.com/files/435239", "https://ndownloader.figshare.com/files/435296", "https://ndownloader.figshare.com/files/435347", "https://ndownloader.figshare.com/files/435393", "https://ndownloader.figshare.com/files/435443", "https://ndownloader.figshare.com/files/435489", "https://ndownloader.figshare.com/files/435541", "https://ndownloader.figshare.com/files/435591", "https://ndownloader.figshare.com/files/435643"], "description"=>"<div><p>Protein-protein interaction networks (PINs) are rich sources of information that enable the network properties of biological systems to be understood. A study of the topological and statistical properties of budding yeast and human PINs revealed that they are scale-rich and configured as highly optimized tolerance (HOT) networks that are similar to the router-level topology of the Internet. This is different from claims that such networks are scale-free and configured through simple preferential-attachment processes. Further analysis revealed that there are extensive interconnections among middle-degree nodes that form the backbone of the networks. Degree distributions of essential genes, synthetic lethal genes, synthetic sick genes, and human drug-target genes indicate that there are advantageous drug targets among nodes with middle- to low-degree nodes. Such network properties provide the rationale for combinatorial drugs that target less prominent nodes to increase synergetic efficacy and create fewer side effects.</p></div>", "links"=>[], "tags"=>["networks", "implications"], "article_id"=>145822, "categories"=>["Genetics", "Biological Sciences"], "users"=>["Takeshi Hase", "Hiroshi Tanaka", "Yasuhiro Suzuki", "So Nakagawa", "Hiroaki Kitano"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1000550.s001", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s002", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s003", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s004", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s005", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s006", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s007", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s008", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s009", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s010", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s011", "https://dx.doi.org/10.1371/journal.pcbi.1000550.s012"], "stats"=>{"downloads"=>16, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Structure_of_Protein_Interaction_Networks_and_Their_Implications_on_Drug_Design/145822", "title"=>"Structure of Protein Interaction Networks and Their Implications on Drug Design", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2009-10-30 01:37:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/877635"], "description"=>"<p>Each diagram shows cumulative degree distributions of proteins in each functional group. The name above each diagram denotes the name of the functional category with which the cumulative degree distribution was examined.</p>", "links"=>[], "tags"=>["yeast"], "article_id"=>548091, "categories"=>["Genetics", "Biological Sciences"], "users"=>["Takeshi Hase", "Hiroshi Tanaka", "Yasuhiro Suzuki", "So Nakagawa", "Hiroaki Kitano"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000550.g004", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scale_richness_in_yeast_PIN_/548091", "title"=>"Scale-richness in yeast PIN.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-10-30 02:14:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/877892"], "description"=>"<p>Proteins were ranked in decreasing order of their degree <i>k</i>. (A) Rank of a protein with degree <i>k</i>. (B) Rank of a drug target with degree <i>k</i>. (C) Rank of a target for cancer diseases with degree <i>k</i>. (D) Rank of a target for non-cancerous diseases with degree <i>k</i>. Red, green, and blue lines represent fraction of drug targets, targets for cancer diseases, and those for non-cancerous diseases to all proteins with rank from rank−0.1<i>N</i> to rank+0.1<i>N</i> (<i>N</i> represents number of proteins in the human PIN). (E) Red, green, and blue lines represent fraction of drug targets, targets for cancer disease, and those for non-cancerous disease with rank from rank−0.1<i>N</i> to rank+0.1<i>N</i> to all drug targets, all targets for cancer diseases, and those for non-cancerous diseases, respectively.</p>", "links"=>[], "tags"=>["tails", "targets", "non-cancerous"], "article_id"=>548346, "categories"=>["Genetics", "Biological Sciences"], "users"=>["Takeshi Hase", "Hiroshi Tanaka", "Yasuhiro Suzuki", "So Nakagawa", "Hiroaki Kitano"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000550.g006", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_long_tails_in_degree_distribution_of_drug_targets_targets_for_cancer_and_those_for_non_cancerous_diseases_/548346", "title"=>"The long tails in degree distribution of drug targets, targets for cancer, and those for non-cancerous diseases.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-10-30 02:19:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/877453"], "description"=>"<p>Grey, red, and blue nodes correspond to low-, middle-, and high-degree nodes. Grey, red, green, and blue links correspond to links between low- and high-degree nodes, those between middle-degree nodes, those between middle- and high-degree nodes, and those between high-degree nodes. For clarity, low- and middle-degree nodes that have no links to high-degree nodes have been omitted. (A) Altocumulus and stratus structures in the yeast PIN. (B) Stratus structure in the yeast PIN. (C) Altocumulus structure in the yeast PIN. (D) Altocumulus and stratus structure in the human PIN. (E) Stratus structure in the human PIN. (F) Altocumulus structure in the human PIN.</p>", "links"=>[], "tags"=>["topology", "yeast"], "article_id"=>547912, "categories"=>["Genetics", "Biological Sciences"], "users"=>["Takeshi Hase", "Hiroshi Tanaka", "Yasuhiro Suzuki", "So Nakagawa", "Hiroaki Kitano"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000550.g002", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cloud_topology_in_yeast_and_human_PINs_/547912", "title"=>"Cloud topology in yeast and human PINs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-10-30 02:11:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/877790"], "description"=>"<p>(A) Degree distribution. Red triangles represent fraction of drug-target proteins to all proteins with degree <i>k</i>. The dashed line in black gives the probability that a randomly selected protein is a drug target. (B) Distribution on network topology. Drugs targets (yellow circles) are mapped on human PIN network topology shown in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000550#pcbi-1000550-g002\" target=\"_blank\">Figure 2D</a>.</p>", "links"=>[], "tags"=>["Computational biology", "genetics and genomics/bioinformatics"], "article_id"=>548245, "categories"=>["Genetics", "Biological Sciences"], "users"=>["Takeshi Hase", "Hiroshi Tanaka", "Yasuhiro Suzuki", "So Nakagawa", "Hiroaki Kitano"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000550.g005", "stats"=>{"downloads"=>4, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_drug_targets_/548245", "title"=>"Distribution of drug targets.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-10-30 02:17:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/877554"], "description"=>"<p>(A) Fraction of essential proteins to all proteins with degree <i>k</i> (red triangles). (B) Fraction of synthetic lethal proteins to all proteins with degree <i>k</i> (red triangles). (C) Fraction of synthetic sick proteins to all proteins with degree <i>k</i> (red triangles). (D) Fraction of normal proteins to all proteins with degree <i>k</i> (red triangles). Dashed lines in black give the probability that a randomly selected protein is essential, synthetic lethal, synthetic sick, or normal. Dashed lines in red represent fraction of essential, synthetic lethal, synthetic sick, or normal proteins to all proteins with degree from <i>k</i>−5 to <i>k</i>+5, when <i>k</i>≤38. When <i>k</i>>38, dashed lines in red represent fraction of essential, synthetic lethal, synthetic sick, or normal proteins to all proteins with degrees more than 38.</p>", "links"=>[], "tags"=>["synthetic", "lethal", "proteins"], "article_id"=>548015, "categories"=>["Genetics", "Biological Sciences"], "users"=>["Takeshi Hase", "Hiroshi Tanaka", "Yasuhiro Suzuki", "So Nakagawa", "Hiroaki Kitano"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000550.g003", "stats"=>{"downloads"=>3, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Degree_distribution_of_essential_proteins_synthetic_lethal_proteins_synthetic_sick_proteins_and_proteins_that_do_not_belong_to_any_of_these_normal_proteins_/548015", "title"=>"Degree distribution of essential proteins, synthetic lethal proteins, synthetic sick proteins, and proteins that do not belong to any of these (normal proteins).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2009-10-30 02:13:35"}

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