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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

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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

Evolutionary Relationships through Genome Comparisons

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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 Organization01:13

Protein Organization

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Overview
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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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Determinación de la estructura proteica utilizando datos de la secuencia del metagenoma

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
Resumen
Este resumen es generado por máquina.

Los investigadores modelaron con precisión estructuras de proteínas desconocidas utilizando datos evolutivos y secuencias de metagenoma. Este enfoque rentable amplía el Banco de Datos de Proteínas y ayuda a alcanzar los objetivos de la Iniciativa de Estructura de Proteínas.

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Área de la Ciencia:

  • Biología estructural
  • La bioinformática
  • Biología computacional

Sus antecedentes:

  • Miles de familias de proteínas carecen de estructuras conocidas, lo que dificulta la investigación biológica.
  • Los métodos actuales como el modelado comparativo son insuficientes para muchas proteínas.

Objetivo del estudio:

  • Desarrollar y validar un enfoque computacional para predecir las estructuras de las proteínas.
  • Ampliar el número de familias de proteínas con modelos estructurales disponibles.

Principales métodos:

  • Utilizó la predicción de la estructura de Rosetta guiada por los contactos entre residuos evolutivos.
  • Datos integrados de la secuencia del metagenoma para aumentar el grupo de familias de proteínas modelables.
  • Utilizó el emparejamiento de estructuras basado en el contacto y los cálculos de Rosetta para la generación de modelos.

Principales resultados:

  • Modelado con precisión las proteínas dentro de las grandes familias utilizando información evolutiva.
  • Los datos del metagenoma triplicaron el número de familias de proteínas adecuadas para un modelado preciso.
  • Modelos generados para 614 familias de proteínas no caracterizadas anteriormente, incluidas las proteínas de membrana y los pliegues nuevos.

Conclusiones:

  • El enfoque combinado avanza significativamente las capacidades de predicción de la estructura de las proteínas.
  • Este método proporciona modelos representativos rentables para las grandes familias de proteínas.
  • El estudio aporta datos estructurales valiosos para las familias de proteínas subrepresentadas.