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Protein and Protein Structure02:15

Protein and Protein Structure

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 can...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order to...
Protein and Protein Structures02:15

Protein and Protein Structures

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 can...

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Erratum: "Edge expansion parallel cascade selection molecular dynamics simulation for investigating large-amplitude collective motions of proteins" [J. Chem. Phys. 152, 225101 (2020)].

The Journal of chemical physics·2020
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Edge expansion parallel cascade selection molecular dynamics simulation for investigating large-amplitude collective motions of proteins.

The Journal of chemical physics·2020
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Refining evERdock: Improved selection of good protein-protein complex models achieved by MD optimization and use of multiple conformations.

The Journal of chemical physics·2018
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Structure prediction of boron-doped graphene by machine learning.

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Binding free energy analysis of protein-protein docking model structures by evERdock.

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Updated: Jul 9, 2026

Detection of RNA-binding Proteins by In Vitro RNA Pull-down in Adipocyte Culture
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evERdock BAI: Machine-learning-guided selection of protein-protein complex structure.

Kei Terayama1, Ai Shinobu2, Koji Tsuda1

  • 1RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.

The Journal of Chemical Physics
|December 12, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient method for protein-protein complex structure prediction using evERdock and reinforcement learning. The approach significantly reduces computational costs while maintaining prediction accuracy.

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Biophysics

Background:

  • Protein-protein interactions are crucial in biological systems.
  • Accurate prediction of protein-protein complex structures aids in understanding these interactions.
  • Existing methods like evERdock, while effective, are computationally expensive.

Purpose of the Study:

  • To develop a more computationally efficient method for selecting accurate protein-protein complex structures.
  • To reduce the computational cost associated with high-accuracy decoy selection.

Main Methods:

  • Integration of the evERdock method with the best arm identification (BAI) framework from reinforcement learning.
  • BAI framework optimizes calculations by prioritizing promising decoys and reducing computations for non-promising ones.
  • Evaluation on three protein-protein complex systems.

Main Results:

  • The proposed method successfully reduced computational costs compared to standard approaches.
  • Computational cost reduction achieved up to a factor of 4.05 in the best case.
  • Prediction accuracy was maintained without sacrifice.

Conclusions:

  • The combination of evERdock and BAI offers a significant improvement in computational efficiency for protein-protein complex structure prediction.
  • This approach provides a viable solution for reducing the computational burden in structural bioinformatics.
  • The method demonstrates the potential of reinforcement learning in optimizing complex biological simulations.