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Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.2K
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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Protein Folding01:22

Protein Folding

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Overview
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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.0K
Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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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...
11.0K
Mechanical Protein Functions01:58

Mechanical Protein Functions

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Proteins perform many mechanical functions in a cell. These proteins can be classified into two general categories- proteins that generate mechanical forces and proteins that are subjected to mechanical forces. Proteins providing mechanical support to the structure of the cell, such as keratin, are subjected to mechanical force, whereas proteins involved in cell movement and transport of molecules across cell membranes, such as an ion pump, are examples of generating mechanical force. 
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Protein and Protein Structure02:15

Protein and Protein Structure

80.0K
Proteins are one of the most abundant organic molecules in living systems and have the most diverse range of functions of all macromolecules. Proteins may be structural, regulatory, contractile, or protective. They may serve in transport, storage, or membranes; or they may be toxins or enzymes. Their structures, like their functions, vary greatly. They are all, however, amino acid polymers arranged in a linear sequence.
A protein's shape is critical to its function. For example, an enzyme...
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Related Experiment Video

Updated: Aug 8, 2025

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

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Functional Protein Dynamics Directly from Sequences.

Kejue Jia1, Mesih Kilinc1, Robert L Jernigan1

  • 1Bioinformatics and Computational Biology Program and Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology Iowa State University, Ames, Iowa 50011, United States.

The Journal of Physical Chemistry. B
|February 27, 2023
PubMed
Summary
This summary is machine-generated.

Protein sequence correlations can directly predict protein dynamics, bypassing the need for structural information. This approach utilizes elastic network models and coarse-graining for efficient analysis of protein motion.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Structural Biology

Background:

  • Protein sequence correlations from multiple sequence alignments are commonly used for predicting structural contacts.
  • Elastic network models (ENMs) are established methods for analyzing protein dynamics, relying on contact information.

Purpose of the Study:

  • To demonstrate that protein sequence correlations can directly predict protein dynamics.
  • To establish a direct link between sequence information and protein dynamics without requiring prior structural knowledge.

Main Methods:

  • Application of coarse-graining to protein structures at one point per amino acid.
  • Utilizing elastic network models and normal mode analysis on contact maps derived from sequence data.

Main Results:

  • Sequence correlations can be directly used to predict protein dynamics.
  • Coarse-grained ENMs successfully represent large-scale protein motions relevant to function.

Conclusions:

  • Protein structure is not required to determine protein dynamics.
  • Sequence information alone is sufficient for predicting protein dynamics using this approach.