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Protein Networks02:26

Protein Networks

3.9K
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,...
3.9K
Protein-protein Interfaces02:04

Protein-protein Interfaces

12.4K
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...
12.4K
Conserved Binding Sites01:49

Conserved Binding Sites

4.1K
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
4.1K
Protein Organization01:24

Protein Organization

6.2K
Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
6.2K
Ligand Binding Sites02:40

Ligand Binding Sites

12.7K
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.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...
12.7K
Covalently Linked Protein Regulators02:04

Covalently Linked Protein Regulators

6.8K
Proteins can undergo many types of post-translational modifications, often in response to changes in their environment. These modifications play an important role in the function and stability of these proteins. Covalently linked molecules include functional groups, such as methyl, acetyl, and phosphate groups, and also small proteins, such as ubiquitin. There are around 200 different types of covalent regulators that have been identified.
These groups modify specific amino acids in a protein....
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Related Experiment Video

Updated: May 27, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
06:50

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

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RNA-protein interaction prediction using network-guided deep learning.

Haoquan Liu1, Yiren Jian2, Chen Zeng3

  • 1Institute of Biophysics and Department of Physics, Central China Normal University, Wuhan, 430079, China.

Communications Biology
|February 16, 2025
PubMed
Summary
This summary is machine-generated.

ZHMolGraph, a new computational tool, accurately predicts RNA-protein interactions using graph neural networks and language models. It significantly outperforms existing methods, especially for unknown RNA and protein pairs.

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Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling
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Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Structural Biology

Background:

  • Predicting RNA-protein interactions (RPI) computationally is difficult, especially with novel RNAs and proteins.
  • Existing deep learning models struggle due to the limited number and flexibility of known RNAs.

Purpose of the Study:

  • To develop ZHMolGraph, an advanced computational method for predicting RNA-protein interactions.
  • To improve the accuracy and reliability of RPI prediction, particularly for novel molecular entities.

Main Methods:

  • Integration of graph neural networks (GNNs) and unsupervised large language models (LLMs).
  • Validation on benchmark datasets and application to SARS-CoV-2 RPI and unbound complex prediction.

Main Results:

  • ZHMolGraph significantly outperforms current state-of-the-art methods on benchmark datasets.
  • Achieved high AUROC (79.8%) and AUPRC (82.0%) on a dataset of entirely unknown RNAs and proteins, showing substantial improvements.
  • Demonstrated enhanced prediction accuracy for SARS-CoV-2 RPI and unbound RNA-protein complexes.

Conclusions:

  • ZHMolGraph offers a reliable and accurate approach for genome-wide RNA-protein interaction prediction.
  • The method shows significant potential for modeling and designing novel RNA-protein complexes.