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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.
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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Golgi Matrix Proteins01:12

Golgi Matrix Proteins

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Golgi matrix proteins are a group of highly dynamic proteins that maintain the stacked structure of Golgi. These proteins adapt to rapid morphological changes of the Golgi during the cell cycle. During cell division, mild proteolysis removes these connections resulting in Golgi unstacking. In The daughter cells, these proteins help reassemble the unstacked Golgi.
One of the first identified Golgi matrix proteins was GM130, a rod-like protein located in the cis-Golgi. Subsequently, many Golgi...
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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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Protein-protein Interfaces02:04

Protein-protein Interfaces

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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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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...
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Conjugated Proteins02:50

Conjugated Proteins

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Simple proteins and protein complexes contain only amino acids. In contrast, many other proteins, called conjugated proteins, covalently bond with non-protein moieties.
Nucleoproteins are protein complexes that contain nucleic acids, categorized as deoxyribonucleoproteins (DNPs) or ribonucleoproteins (RNPs) respectively. The nucleosome is a typical example of a DNP where nuclear DNA is associated with histone proteins. The major antigen for the Covid-19 virus SARS-CoV is an RNP that is critical...
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A Protocol for Computer-Based Protein Structure and Function Prediction
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PCLPred: A Bioinformatics Method for Predicting Protein-Protein Interactions by Combining Relevance Vector Machine

Li-Ping Li1, Yan-Bin Wang2, Zhu-Hong You3

  • 1Department of Information Engineering, Xijing University, Xi'an 710123, China. cs2bioinformatics@gmail.com.

International Journal of Molecular Sciences
|March 30, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a new computational method to predict protein-protein interactions (PPIs) using evolutionary sequence features. The developed approach achieves high accuracy, offering a valuable tool for proteomics research.

Keywords:
evolutionary informationlow rankprotein sequenceprotein–protein interactions (PPI)relevance vector machine (RVM)

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Area of Science:

  • Computational biology
  • Proteomics
  • Bioinformatics

Background:

  • Protein-protein interactions (PPIs) are crucial for cellular processes like signaling and cell cycle regulation.
  • Accurate prediction of PPIs is vital for molecular biology research.
  • Existing computational methods for PPI prediction often fall short of user needs.

Purpose of the Study:

  • To develop a novel, efficient, and sequence-based computational method for predicting protein-protein interactions (PPIs).
  • To enhance the accuracy and reliability of computational PPI prediction tools.

Main Methods:

  • Extraction of evolutionary features from protein Position-Specific Scoring Matrices (PSSM).
  • Utilizing a Relevance Vector Machine (RVM) classifier to differentiate interacting and non-interacting protein pairs.
  • Validation using five-fold cross-validation on the Saccharomyces cerevisiae dataset.

Main Results:

  • The proposed method achieved a high accuracy of 94.56%.
  • Sensitivity reached 94.79% with a precision of 94.36%.
  • Demonstrated effective extraction of significant features from protein sequences.

Conclusions:

  • The novel sequence-based method provides an efficient and accurate approach for PPI prediction.
  • This tool holds significant potential for advancing proteomics research.
  • The method effectively identifies key features for distinguishing interacting protein pairs.