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Related Concept Videos

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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 form...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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 form...
Protein Networks02:26

Protein Networks

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,...
Protein Networks02:26

Protein Networks

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,...
Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
Protein Folding01:22

Protein Folding

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Related Experiment Video

Updated: Jul 9, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

OrgNet+: towards robust protein stability prediction with convolutional neural networks.

Anastasia Sarycheva1,2, Aleksandr Shumilov1,2, Petr Popov1,2

  • 1School of Science, Constructor University Bremen gGmbH, Bremen 28759, Germany.

Bioinformatics (Oxford, England)
|July 7, 2026
PubMed
Summary
This summary is machine-generated.

OrgNet+ improves protein stability prediction by accounting for protein flexibility using conformational ensembles. This novel approach reduces prediction variance and enhances accuracy, even without experimental structures.

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Related Experiment Videos

Last Updated: Jul 9, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

  • Molecular Biology
  • Protein Engineering
  • Computational Biology

Background:

  • Predicting protein stability changes from mutations is crucial for molecular biology and protein engineering.
  • Current deep learning models often use static protein structures, ignoring conformational flexibility.
  • This can lead to unstable or contradictory predictions for protein stability.

Purpose of the Study:

  • To develop a novel framework, OrgNet+, that incorporates protein conformational flexibility for improved stability prediction.
  • To address the limitations of existing models that do not account for protein dynamics.

Main Methods:

  • OrgNet+ is a conformational ensemble-aware and orientation-gnostic framework.
  • It was trained on diverse conformational ensembles generated via molecular dynamics, Monte Carlo simulations, and deep learning.
  • The framework explicitly incorporates protein structure flexibility during training.

Main Results:

  • OrgNet+ significantly reduces intra-ensemble prediction variance across various ensemble types.
  • The framework demonstrates improved predictive accuracy for protein stability.
  • OrgNet+ shows strong performance on standard benchmarks, despite being trained solely on ensembles.

Conclusions:

  • Accounting for protein conformational flexibility is essential for accurate stability prediction.
  • OrgNet+ offers a robust solution for structure-based stability prediction by integrating ensemble data.
  • The developed framework advances the field of protein engineering and molecular biology.