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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 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 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...
Protein Folding01:22

Protein Folding

Overview

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Related Experiment Video

Updated: May 13, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Protein structure alignment beyond spatial proximity.

Sheng Wang1, Jianzhu Ma, Jian Peng

  • 1Toyota Technological Institute, Chicago, IL 60637, USA.

Scientific Reports
|March 15, 2013
PubMed
Summary
This summary is machine-generated.

DeepAlign improves protein structure alignment by integrating evolutionary and hydrogen-bonding data with geometric similarity. This novel method yields more biologically meaningful alignments, especially for distantly related proteins.

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Last Updated: May 13, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Published on: July 14, 2015

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

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Area of Science:

  • Computational structural biology
  • Bioinformatics
  • Protein structure analysis

Background:

  • Protein structure alignment is crucial in computational biology.
  • Existing methods often rely solely on geometric similarity, neglecting evolutionary and functional insights.
  • This can lead to biologically less meaningful alignments, particularly for remote homologs.

Purpose of the Study:

  • To introduce DeepAlign, a novel method for automatic pairwise protein structure alignment.
  • To enhance alignment accuracy by incorporating evolutionary relationships and hydrogen-bonding patterns alongside geometric similarity.

Main Methods:

  • DeepAlign utilizes spatial proximity of residues after rigid-body superposition.
  • It integrates evolutionary information and hydrogen-bonding similarity into the alignment process.
  • The method performs automatic pairwise protein structure alignment.

Main Results:

  • DeepAlign generates structure alignments more consistent with manually curated alignments compared to existing tools.
  • The improvement is particularly notable when aligning remote protein homologs.
  • Experimental results validate the effectiveness of incorporating evolutionary and hydrogen-bonding data.

Conclusions:

  • Evolutionary information and hydrogen-bonding similarity are essential components for accurate protein structure alignment.
  • DeepAlign offers a more biologically relevant approach to protein structure comparison.
  • The method advances the field of computational structural biology by providing more meaningful alignments.