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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.
Protein Organization01:13

Protein Organization

Overview
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

Overview
Protein and Protein Structure02:15

Protein and Protein Structure

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 can...

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Related Experiment Video

Updated: Jul 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 structure prediction by all-atom free-energy refinement.

Abhinav Verma1, Wolfgang Wenzel

  • 1Institute for Scientific Computing, Forschungszentrum Karlsruhe, Karlsruhe, Germany. verma@int.fzk.de <verma@int.fzk.de>

BMC Structural Biology
|March 21, 2007
PubMed
Summary

A new low-cost protocol using the all-atom free-energy protein forcefield (PFF01) effectively predicts protein tertiary structures. This method successfully identifies near-native protein conformations from large datasets, offering a powerful tool for de-novo protein structure prediction.

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Area of Science:

  • Computational Biology
  • Structural Biology
  • Biophysics

Background:

  • Protein tertiary structure prediction from amino acid sequences is a significant challenge.
  • An all-atom free-energy protein forcefield (PFF01) was developed, capable of folding small proteins.
  • High computational costs limit de-novo folding studies for larger proteins.

Purpose of the Study:

  • To investigate a low-cost free-energy relaxation protocol for protein structure prediction.
  • To combine heuristic methods with PFF01 for efficient structure prediction.
  • To assess the effectiveness of PFF01 in identifying near-native protein conformations.

Main Methods:

  • Development of an all-atom free-energy protein forcefield (PFF01).
  • Implementation of a low-cost free-energy relaxation protocol.
  • Utilizing heuristic methods for model generation combined with PFF01 relaxation.
  • Ranking and clustering protein conformations generated by ROSETTA.

Main Results:

  • PFF01 successfully ranked and clustered conformations for 32 proteins.
  • Near-native conformations were selected with an average Calpha root mean square deviation of 3.03 Å for high-quality decoys and 6.04 Å for low-quality decoys.
  • The protocol's reliability indicator succeeded for 78% of decoy sets, selecting near-native conformations in over 90% of these cases.

Conclusions:

  • All-atom free-energy relaxation with PFF01 is a powerful, low-cost approach for de-novo protein structure prediction.
  • The protocol is applicable to large, diverse all-atom decoy sets without prior structural information.
  • Evidence suggests PFF01 can fold a broad range of proteins.