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Related Experiment Video

Updated: May 10, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

A sampling approach for protein backbone fragment conformations.

J Y Yu1, W Zhang

  • 1Department of Automation, Shanghai Jiaotong University, Shanghai 200240, China. yujyong@sjtu.edu.cn

International Journal of Data Mining and Bioinformatics
|June 20, 2013
PubMed
Summary

This study introduces a novel probabilistic method for protein structure prediction. It effectively samples protein backbone conformations, aiding in the generation of native-like structures.

Related Concept Videos

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.

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Biophysics

Background:

  • Protein structure prediction is crucial for understanding protein function.
  • Existing methods often rely on fragment assembly, which can be limited.
  • Backbone torsion angle correlations are key to conformational sampling.

Purpose of the Study:

  • To develop a probabilistic sampling approach for protein backbone torsion angles.
  • To model angular correlations using directional statistics for improved conformational sampling.
  • To enhance protein structure prediction accuracy by generating native-like backbone fragments.

Main Methods:

  • Utilized a probabilistic sampling approach for protein backbone torsion angles (phi, psi).
  • Employed directional statistics to model angular correlations.

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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

Related Experiment Videos

Last Updated: May 10, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

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

  • Applied a backtrack sampling algorithm for a hidden Markov model (HMM) with multiple inputs and a single output.
  • Integrated secondary structure information with protein sequence data.

    • Main Results:

    • The method successfully sampled conformations of well-known structural motifs within a fragment library.
    • Demonstrated effective sampling along the optimal path for these motifs.
    • Computational results indicated the ability to obtain native-like backbone fragment conformations.

    Conclusions:

    • The proposed probabilistic sampling method offers a promising alternative to traditional fragment-based approaches.
    • This technique can significantly narrow down the conformational space for protein structure prediction.
    • The approach facilitates the generation of accurate, native-like protein backbone structures.