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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.
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...
¹H NMR of Conformationally Flexible Molecules: Temporal Resolution00:52

¹H NMR of Conformationally Flexible Molecules: Temporal Resolution

At room temperature, the chair conformer of cyclohexane undergoes rapid ring flipping between two equivalent chair conformers at a rate of approximately 105 times per second. These two chair conformers are in equilibrium. The rapid ring flipping results in the interconversion of the axial proton to an equatorial proton and an equatorial to the axial proton. Such interconversions are too rapid and cannot be detected on the NMR timescale. Hence, the NMR spectrometer cannot distinguish between the...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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...

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Updated: Jun 16, 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

Feature space resampling for protein conformational search.

Ben Blum1, Michael I Jordan, David Baker

  • 1Department of Electrical Engineering and Computer Science, University of California, Berkeley, 94720, USA. benblum@gmail.com

Proteins
|February 5, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for de novo protein structure prediction by combining conformational space annealing and genetic algorithms. The approach improves accuracy by predicting and utilizing native structural features to guide protein folding simulations.

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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

Related Experiment Videos

Last Updated: Jun 16, 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

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
  • Biophysics

Background:

  • De novo protein structure prediction is crucial for understanding protein function and designing new proteins.
  • Existing methods like conformational space annealing and genetic algorithms have limitations in exploring vast conformational spaces.
  • Accurate prediction of the lowest energy state of a polypeptide chain remains a significant challenge.

Purpose of the Study:

  • To develop a hybrid approach combining conformational space annealing and genetic algorithms for enhanced de novo protein structure prediction.
  • To improve the accuracy and efficiency of protein structure prediction by leveraging predicted native structural features.
  • To address the limitations of current methods in exploring conformational space and recombining structural elements.

Main Methods:

  • Protein conformations were projected onto a discrete feature space including backbone torsion angles, secondary structure, and beta pairings.
  • Native feature values were predicted from frequencies and energy distributions in initial Monte Carlo simulations (Rosetta).
  • A second round of structure prediction trajectories was guided by these predicted native feature distributions.

Main Results:

  • Native features were predicted at significantly higher than background rates.
  • The use of predicted feature distributions demonstrably improved protein structure prediction accuracy across a benchmark of 28 proteins.
  • The method successfully combined features from multiple structures without generating physically inviable models.

Conclusions:

  • The hybrid approach effectively integrates strengths of existing methods for de novo protein structure prediction.
  • Predicting and utilizing native feature distributions offers a powerful strategy to enhance the accuracy of protein folding simulations.
  • This method provides a robust framework for combining diverse structural information while maintaining physical realism.