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Protein-protein Interfaces

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Docking-calculation-based method for predicting protein-RNA interactions.

Masahito Ohue1, Yuri Matsuzaki, Yutaka Akiyama

  • 1Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Meguro-ku, Tokyo, Japan. ohue@bi.cs.titech.ac.jp

Genome Informatics. International Conference on Genome Informatics
|January 11, 2012
PubMed
Summary
This summary is machine-generated.

Predicting protein-RNA interactions (PRIs) is crucial for cell biology. A new rigid-body docking method using tertiary structures achieved an F-measure of 0.465 in predicting these vital molecular interactions.

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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

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Published on: July 25, 2013

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

Area of Science:

  • Molecular Biology
  • Structural Biology
  • Bioinformatics

Background:

  • Protein-RNA interactions (PRIs) are fundamental to numerous cellular processes.
  • Understanding these interactions is key to deciphering complex biological systems.

Purpose of the Study:

  • To develop and evaluate a novel computational method for predicting protein-RNA interactions.
  • To utilize tertiary structure data and rigid-body docking for PRI prediction.

Main Methods:

  • A rigid-body protein-RNA docking approach was employed.
  • Tertiary structure data from the Protein Data Bank (PDB) was utilized.
  • The method was validated using 78 known protein-RNA complex structures.

Main Results:

  • The prediction system was tested on 78 positive (known complexes) and 6,006 negative (non-complexes) pairs.
  • An F-measure of 0.465 was achieved, indicating the system's predictive performance.
  • The study systematically evaluated prediction accuracy across numerous combinations.

Conclusions:

  • The developed rigid-body docking method shows potential for predicting protein-RNA interactions.
  • Tertiary structure information is a valuable component in computational PRI prediction.
  • Further refinement of the method could enhance its accuracy in structural biology and drug discovery.