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Related Concept Videos

Conserved Binding Sites01:49

Conserved Binding Sites

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 analyses the...
Protein Organization01:24

Protein Organization

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.
Protein-protein Interfaces02:04

Protein-protein Interfaces

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 polypeptide...

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Related Experiment Video

Updated: May 17, 2026

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

A nonredundant structure dataset for benchmarking protein-RNA computational docking.

Sheng-You Huang1, Xiaoqin Zou

  • 1Department of Physics and Astronomy, University of Missouri, Columbia, Missouri 65211, USA.

Journal of Computational Chemistry
|October 11, 2012
PubMed
Summary

A new benchmark dataset for protein-RNA docking and scoring has been developed. This resource aids in improving computational methods for predicting protein-RNA complex structures, crucial for understanding biological mechanisms.

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

Published on: July 25, 2013

Related Experiment Videos

Last Updated: May 17, 2026

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

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

Area of Science:

  • Computational Biology
  • Structural Biology
  • Biochemistry

Background:

  • Protein-RNA interactions are fundamental to numerous biological processes.
  • Predicting the molecular structures of protein-RNA complexes is vital for elucidating underlying chemical mechanisms.
  • Accurate structural prediction aids in understanding molecular recognition and function.

Purpose of the Study:

  • To develop and present a novel, nonredundant benchmark dataset for protein-RNA docking and scoring.
  • To provide a diverse set of targets for evaluating and advancing docking algorithms.
  • To facilitate the development of improved computational tools for structural prediction.

Main Methods:

  • Compilation of a benchmark dataset comprising 72 protein-RNA targets.
  • Classification of targets into unbound-unbound (52 cases) and unbound-bound (20 cases) categories.
  • Categorization of targets into easy (49), medium (16), and difficult (7) based on interface RMSD and native contact percentage.

Main Results:

  • A comprehensive dataset of 72 protein-RNA docking targets is now available.
  • The dataset includes varying degrees of difficulty, catering to diverse algorithm testing needs.
  • Structures are accessible for public use, promoting community-driven advancements.

Conclusions:

  • The developed benchmark dataset will significantly benefit the protein-RNA docking and scoring algorithm development community.
  • This resource is expected to drive improvements in the accuracy and efficiency of computational structure prediction methods.
  • The availability of this dataset promotes reproducibility and accelerates research in the field.