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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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Protein Networks02:26

Protein Networks

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Predator-Prey Interactions02:39

Predator-Prey Interactions

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Predators consume prey for energy. Predators that acquire prey and prey that avoid predation both increase their chances of survival and reproduction (i.e., fitness). Routine predator-prey interactions elicit mutual adaptations that improve predator offenses, such as claws, teeth, and speed, as well as prey defenses, including crypsis, aposematism, and mimicry. Thus, predator-prey interactions resemble an evolutionary arms race.
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Network Covalent Solids02:18

Network Covalent Solids

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Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
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Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Protein Kinases and Phosphatases02:54

Protein Kinases and Phosphatases

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Proteins undergo chemical modifications that trigger changes in the charge, structure, and conformation of the proteins. Phosphorylation, acetylation, glycosylation, nitrosylation, ubiquitination, lipidation, methylation, and proteolysis are various protein modifications that regulate protein activity. Such modifications are usually enzyme-driven.
Protein kinases
Many proteins in the cell are regulated by phosphorylation, the addition of a phosphate group. A family of enzymes called kinases...
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Updated: Jan 22, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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プロテオムの共進化によって明らかになったタンパク質の相互作用ネットワーク

Qian Cong1,2, Ivan Anishchenko1,2, Sergey Ovchinnikov3

  • 1Department of Biochemistry, University of Washington, Seattle, WA 98105, USA.

Science (New York, N.Y.)
|July 13, 2019
PubMed
まとめ

タンパク質同士の相互作用を 他の方法よりも正確に 予測するのに役立つことを発見しました この研究は,E. coliとM. tuberculosisにおける多くの新しいPPIを特定した.

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Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
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Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

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Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation
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Quantification of Protein Interaction Network Dynamics using Multiplexed Co-Immunoprecipitation

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科学分野:

  • プロテオミクス
  • バイオ情報学
  • コンピュータ生物学

背景:

  • タンパク質のインターフェイスでは,残留-残留の共進化が知られている.
  • プロテオーム全体における共進化の体系的な研究は欠けている.

研究 の 目的:

  • タンパク質の家族間のプロテオーム全体の共進化を調査する.
  • 精密なタンパク質相互作用 (PPI) の予測方法を開発する.
  • エシェリキア・コライとミコバクテリアの結核における新しいPPIを特定する.

主な方法:

  • 大腸菌の540万個のタンパク質ペアと, 結核菌の390万個のタンパク質ペアを分析した.
  • 複合的な大きさと機能との関係で考察した共進化パターン.
  • PPI予測のための構造モデリングと統合された共進化データ.

主要な成果:

  • バイナリ代謝複合体では強い共進化が観察され,より大きな遺伝子複合体では弱い.
  • プロテオーム幅の2ハイブリッドと質量スペクトロメトリよりも高い精度でPPIを予測した.
  • この2つの生物でこれまでに特徴づけられなかった PPIを数百個特定した.

結論:

  • タンパク質全体の共進化分析はPPI予測の強力なツールです.
  • このアプローチは,E. coliとM. tuberculosisの既知の相互作用を大幅に拡張します.
  • 新しいPPIは,既知の新しいタンパク質複合体やネットワークに寄与し,それを明らかにします.