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Related Concept Videos

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.
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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 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.
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Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key...
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Proteomics01:33

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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.
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A Protocol for Computer-Based Protein Structure and Function Prediction
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PRONTO-TK: a user-friendly PROtein Neural neTwOrk tool-kit for accessible protein function prediction.

Gianfranco Politano1, Alfredo Benso1, Hafeez Ur Rehman2

  • 1Department of Control and Computer Engineering, Politecnico di Torino, Torino, 10129, Italy.

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Summary

PRONTO-TK simplifies protein function prediction using Gene Ontology (GO) terms with deep learning. This Python toolkit offers a user-friendly interface for researchers to access complex neural network workflows without extensive coding knowledge.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Associating Gene Ontology (GO) terms with proteins defines their functional characteristics and biological context.
  • Complex protein function prediction often requires advanced computational expertise and deep learning knowledge.

Purpose of the Study:

  • To introduce PRONTO-TK, a Python-based software toolkit.
  • To democratize access to neural network-based protein function prediction workflows.
  • To empower researchers with varying programming experience to utilize advanced deep learning for GO term annotation.

Main Methods:

  • Development of PRONTO-TK, a Python toolkit with a graphical user interface (GUI).
  • Integration of state-of-the-art Deep Learning architectures for protein function prediction.
  • Demonstration of the toolkit's effectiveness through a running example and intuitive configuration.

Main Results:

  • PRONTO-TK provides accessible protein function annotation using GO terms.
  • The toolkit simplifies the generation of complex analyses via an intuitive GUI.
  • Researchers can leverage deep learning for protein function prediction without building pipelines from scratch.

Conclusions:

  • PRONTO-TK effectively democratizes access to advanced protein function prediction methods.
  • The toolkit lowers the barrier to entry for utilizing deep learning in bioinformatics.
  • It enables researchers to easily perform complex protein function annotation using GO terms.