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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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Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Protein and Protein Structure02:15

Protein and Protein Structure

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Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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メタゲノム配列データを用いてタンパク質構造の決定

Sergey Ovchinnikov1,2,3, Hahnbeom Park1,2, Neha Varghese4

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

Science (New York, N.Y.)
|January 21, 2017
PubMed
まとめ
この要約は機械生成です。

研究者は進化データとメタゲノム配列を用いて 未知のタンパク質構造を正確にモデル化しました この費用対効果の高いアプローチは,タンパク質データバンクを拡張し,タンパク質構造イニシアチブの目標を支援します.

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Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
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Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

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An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis
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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures
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An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis
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科学分野:

  • 構造生物学
  • バイオ情報学
  • 計算生物学

背景:

  • 何千ものタンパク質の 構造は知られず 生物学的研究を妨げています
  • 比較モデリングのような現在の方法は 多くのタンパク質では不十分です

研究 の 目的:

  • タンパク質の構造を予測するための計算手法を開発し,検証する.
  • タンパク質の種類を拡大し 構造モデルを用意する.

主な方法:

  • 進化的残留-残留の接触によって導かれたロゼッタ構造の予測を活用した.
  • 統合されたメタゲノム配列データは,モデル化可能なタンパク質ファミリーのプールを増やすため.
  • 接触ベースの構造のマッチングとモデルの生成のためのロゼッタ計算を使用した.

主要な成果:

  • 進化の情報を用いて タンパク質を正確にモデル化します
  • メタゲノムデータは 精密なモデリングに適した タンパク質ファミリーの数を3倍にしました
  • 膜タンパク質と新しい折りたたみを含む,以前に特徴づけられていない614のタンパク質のモデルを生成した.

結論:

  • タンパク質の構造を予測する能力を大幅に向上させる.
  • この方法は,大きなタンパク質ファミリーの費用対効果の高い代表的なモデルを提供します.
  • この研究は,代表が不足しているタンパク質ファミリーの構造に関する貴重なデータを提供している.