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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 Folding01:22

Protein Folding

Overview
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

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Protein Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...

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Related Experiment Video

Updated: May 20, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Structure-based mutant stability predictions on proteins of unknown structure.

Giulia Gonnelli1, Marianne Rooman, Yves Dehouck

  • 1Department of BioModelling, BioInformatics and BioProcesses, Université Libre de Bruxelles, CP165/61, Av. Fr. Roosevelt 50, 1050 Brussels, Belgium.

Journal of Biotechnology
|July 12, 2012
PubMed
Summary

Predicting protein mutation effects is vital for drug design and disease research. Combining structural models with stability predictions maintains high accuracy, even with lower-quality models, outperforming sequence-only methods.

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Area of Science:

  • Protein engineering
  • Computational biology
  • Structural bioinformatics

Background:

  • Predicting mutation effects on protein properties is crucial for rational protein design and understanding disease.
  • Lack of experimental structures hinders many predictive software tools.
  • Existing methods often rely heavily on experimentally resolved protein structures.

Purpose of the Study:

  • To assess the utility of combining coarse-grained structure-based stability predictions with comparative modeling.
  • To evaluate if this combined approach can overcome the limitations posed by the absence of experimental structures.
  • To compare the predictive power of this method against sequence-feature-based approaches.

Main Methods:

  • Utilized coarse-grained structure-based stability predictions.
  • Integrated a simple comparative modeling procedure.
  • Assessed predictive performance using varying quality structural models (experimental, average, high, low).

Main Results:

  • Combining structural models with stability predictions showed minimal loss in predictive power compared to experimental structures.
  • Even low-quality structural models yielded a limited decrease in performance.
  • The combined approach significantly outperformed methods relying solely on sequence features.

Conclusions:

  • Coarse-grained structure-based stability predictions coupled with comparative modeling offer a robust alternative when experimental structures are unavailable.
  • This integrated approach maintains high predictive accuracy for mutation effects.
  • The method provides a valuable tool for protein design and disease research, broadening accessibility beyond structure-dependent software.