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Related Concept Videos

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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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
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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.
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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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MetalPredator: a web server to predict iron-sulfur cluster binding proteomes.

Yana Valasatava1, Antonio Rosato2, Lucia Banci2

  • 1Magnetic Resonance Center (CERM).

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|June 9, 2016
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Summary

Researchers developed MetalPredator, a free web server for predicting iron-sulfur proteins from sequences. This tool rapidly analyzes proteomes with high accuracy, aiding biological and biomedical research.

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Proteomics

Background:

  • Iron-sulfur proteins are crucial in biological systems.
  • Accurate prediction of these proteins is vital for research.
  • A freely available predictive tool was lacking.

Purpose of the Study:

  • To develop a user-friendly web server for predicting iron-sulfur proteins.
  • To provide a tool for rapid and accurate analysis of protein sequences.

Main Methods:

  • Development of a web server named MetalPredator.
  • Utilizing protein sequences as input for prediction.
  • High-throughput processing of complete proteomes.

Main Results:

  • MetalPredator accurately predicts iron-sulfur proteins.
  • The tool demonstrates high recall and precision.
  • Complete proteomes can be processed rapidly.

Conclusions:

  • MetalPredator is a valuable, freely accessible resource.
  • The tool facilitates research in iron-sulfur protein identification.
  • It addresses the need for a dedicated predictive tool.