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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...
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...
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
Protein Folding01:25

Protein Folding

Proteins are chains of amino acids linked together by peptide bonds. Upon synthesis, a protein folds into a three-dimensional conformation, critical to its biological function. Interactions between its constituent amino acids guide protein folding, and hence the protein structure is primarily dependent on its amino acid sequence.
Protein Structure Is Critical to Its Biological Function
Proteins perform a wide range of biological functions such as catalyzing chemical reactions, providing...
Protein Folding01:22

Protein Folding

Overview

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Related Experiment Video

Updated: May 15, 2026

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

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Published on: July 14, 2015

Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure.

Nikolas S Burkoff1, Csilla Várnai, David L Wild

  • 1Systems Biology Centre, Senate House, University of Warwick, Coventry, CV4 7AL, UK.

Bioinformatics (Oxford, England)
|January 15, 2013
PubMed
Summary

This study predicts protein residue contacts in β-sheets using a novel maximum entropy-based correlated mutation measure (CMM). The new method improves accuracy, especially with small multiple sequence alignments (MSAs), outperforming existing models for protein structure prediction.

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Single-Molecule Measurement of Protein Interaction Dynamics Within Biomolecular Condensates
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Single-Molecule Measurement of Protein Interaction Dynamics Within Biomolecular Condensates

Published on: January 5, 2024

Area of Science:

  • Computational Biology
  • Structural Biology
  • Bioinformatics

Background:

  • Predicting protein residue contacts is crucial for understanding protein folding.
  • Maximum entropy-based correlated mutation measures (CMMs) are effective but typically require large multiple sequence alignments (MSAs).
  • This study addresses the challenge of predicting contacts using CMMs with small or noisy MSAs, focusing on β-sheet contacts.

Purpose of the Study:

  • To develop a novel method for predicting residue contacts specifically within protein β-sheets.
  • To leverage maximum entropy-based CMMs effectively even with limited or noisy multiple sequence alignment data.
  • To improve the accuracy and efficiency of protein structure prediction, particularly for β-sheet interactions.

Main Methods:

  • Calculated a maximum entropy-based CMM using contrastive divergence, a statistical machine learning technique.
  • Developed a new probabilistic model for predicting β-contacts at both residue and strand levels.
  • Integrated the CMM with the probabilistic model for enhanced prediction accuracy.

Main Results:

  • The novel model significantly outperforms a 2D recurrent neural network, achieving a 5% improvement in true positives at a 5% false-positive rate for residue-level contacts.
  • At the strand level, the approach demonstrates competitive performance with state-of-the-art methods, achieving 61.0% precision and 55.4% recall.
  • The method does not require residue solvent accessibility as an input, simplifying the prediction process.

Conclusions:

  • The developed method effectively predicts β-sheet contacts using maximum entropy-based CMMs, even with small MSAs.
  • This approach offers a significant improvement over existing methods for residue-level contact prediction and is competitive at the strand level.
  • The findings contribute to more accurate and efficient protein structure prediction in computational biology.