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Related Concept Videos

Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...

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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

High-throughput modeling and analysis of protein structural dynamics.

Xiong Liu1, Hassan A Karimi

  • 1Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. xliu33@jhmi.edu

Briefings in Bioinformatics
|May 9, 2007
PubMed
Summary

Understanding protein function requires analyzing dynamic structural changes. This review covers computational methods and introduces iGNM, a web system for predicting protein conformational dynamics and exploring sequence-structure-dynamics-function relationships.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Structural Biology

Background:

  • Protein function is intrinsically linked to its dynamic structural changes in a physiological context.
  • Predicting these molecular-level motions is crucial for understanding and controlling protein behavior.

Purpose of the Study:

  • To review computational methods for predicting protein conformational dynamics.
  • To discuss available software tools for analyzing this dynamic data.
  • To highlight the iGNM web-based system for high-throughput analysis of protein structural dynamics.

Main Methods:

  • Review of computational approaches for predicting collective protein motions.
  • Discussion of data analysis software for molecular dynamics.
  • Description of the iGNM system, including its database and online calculation capabilities.

Main Results:

  • iGNM provides a database of protein motions for over 20,000 Protein Data Bank (PDB) structures.
  • The system supports online calculations for new or modified PDB structures.
  • iGNM facilitates the analysis of dynamics across various protein scales, from enzymes to large assemblies.

Conclusions:

  • Computational methods and tools like iGNM are essential for predicting and analyzing protein conformational dynamics.
  • iGNM enables comprehensive exploration of the complex relationships between protein sequence, structure, dynamics, and function.
  • This approach aids in understanding and potentially manipulating protein behavior for various applications.