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Related Concept Videos

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...
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...
Noncovalent Attractions in Biomolecules02:35

Noncovalent Attractions in Biomolecules

Noncovalent attractions are associations within and between molecules that influence the shape and structural stability of complexes. These interactions differ from covalent bonding in that they do not involve sharing of electrons.
Four types of noncovalent interactions are hydrogen bonds, van der Waals forces, ionic bonds, and hydrophobic interactions.
Hydrogen bonding results from the electrostatic attraction of a hydrogen atom covalently bonded to a strong-electronegative atom like oxygen,...
Noncovalent Attractions in Biomolecules02:35

Noncovalent Attractions in Biomolecules

Noncovalent attractions are associations within and between molecules that influence the shape and structural stability of complexes. These interactions differ from covalent bonding in that they do not involve sharing of electrons.
Four types of noncovalent interactions are hydrogen bonds, van der Waals forces, ionic bonds, and hydrophobic interactions.
Hydrogen bonding results from the electrostatic attraction of a hydrogen atom covalently bonded to a strong-electronegative atom like oxygen,...
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,...

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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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A generalized knowledge-based discriminatory function for biomolecular interactions.

Brady Bernard1, Ram Samudrala

  • 1Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.

Proteins
|January 8, 2009
PubMed
Summary
This summary is machine-generated.

A new r.m.r function accurately distinguishes native biomolecular interactions. This atomic-level radial distribution function shows superior performance for protein-small molecule and protein-DNA interactions.

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Area of Science:

  • Computational Biology
  • Structural Biology
  • Bioinformatics

Background:

  • Knowledge-based functions are crucial for distinguishing native biomolecular interactions from non-native ones.
  • Existing methods require robust parameter sets for accurate discrimination.

Purpose of the Study:

  • To develop and evaluate novel discriminatory functions for biomolecular interactions.
  • To identify parameter sets with high accuracy in distinguishing native from incorrect interactions.

Main Methods:

  • Developed the r.m.r (radial distribution function with mean reference state) function, an atomic-level approach.
  • Averaged pairwise atom types from a reduced composition using data from the Cambridge Structural Database (CSD) and Protein Data Bank (PDB).

Main Results:

  • The r.m.r function demonstrated superior discriminatory accuracy and power for protein-small molecule and protein-DNA interactions.
  • Performance remained high whether native complexes were included or excluded in the test set.
  • Outperformed seventeen alternative functions on publicly available datasets, indicating robustness.

Conclusions:

  • The r.m.r function offers a significant advancement in identifying correct biomolecular interactions.
  • Further improvements are possible by refining probability derivations from specific subsets of the CSD.
  • The method is accessible via a web server module.