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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-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 23, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Reduced false positives in PDZ binding prediction using sequence and structural descriptors.

John C Hawkins1, Hongbo Zhu, Joan Teyra

  • 1Structural Bioinformatics, BIOTEC TU Dresden, Dresden, Germany. john.hawkins@biotec.tu-dresden.de

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|April 18, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel computational method for predicting protein binding partners, significantly improving accuracy for PDZ domains. The new approach enhances prediction capabilities and reduces false positives compared to existing methods.

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A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

  • Computational Biology
  • Structural Biology
  • Bioinformatics

Background:

  • Identifying protein binding partners is crucial in computational biology.
  • PDZ domains are common protein binding domains, serving as a model for predictive studies.
  • Current methods often rely on sequence alignments to infer contact residues.

Purpose of the Study:

  • To develop an improved computational model for predicting PDZ domain binding partners.
  • To integrate structural information into predictive models for enhanced accuracy.
  • To generate a real-value score for binary predictions using probability distribution models.

Main Methods:

  • Incorporating structural information to describe binding site geometry.
  • Developing a filter based on predicted probability distributions of contact residues.
  • Utilizing canonical PDZ ligand binding positions for prediction refinement.

Main Results:

  • The model produced an order of magnitude more predictions at a 10% false positive proportion (FPP) during training cross-validation.
  • Independent cross-validation with predicted structures showed five times more predictions than the benchmark.
  • The model achieved a Matthews' correlation coefficient (MCC) of 0.33 and a 0.14 FPP, outperforming the benchmark's 0.25 FPP.

Conclusions:

  • The developed model significantly enhances the prediction of PDZ domain binding partners.
  • Integrating structural data improves prediction performance and reduces false positives.
  • This approach offers a more effective tool for identifying protein-protein interactions.