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Related Concept Videos

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 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 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...

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Related Experiment Video

Updated: Jun 21, 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

Iterative non-sequential protein structural alignment.

Saeed Salem1, Mohammed J Zaki

  • 1Computer Science Department, Rensselaer Polytechnic Institute, 110 8th St. Troy, NY 12180, USA. salems@cs.rpi.edu

Computational Systems Bioinformatics. Computational Systems Bioinformatics Conference
|August 1, 2009
PubMed
Summary
This summary is machine-generated.

Structural similarity in proteins reveals evolutionary links, even with low sequence similarity. A new method, STSA, achieves accurate non-sequential protein structural alignment, outperforming existing approaches.

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Last Updated: Jun 21, 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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09:51

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Published on: July 16, 2017

Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein structure analysis

Background:

  • Protein structural similarity offers insights into evolutionary relationships, particularly when sequence similarity is low.
  • Accurate structural alignment is crucial for understanding protein function and evolution.

Purpose of the Study:

  • To introduce a novel approach, STSA (Structural Threading Sequence Alignment), for non-sequential pair-wise protein structural alignment.
  • To evaluate the performance of STSA against established methods on challenging datasets.

Main Methods:

  • STSA employs an iterative two-step process: superposition and alignment, until convergence.
  • A novel greedy algorithm is utilized for constructing both sequential and non-sequential alignments from superposed structures.

Main Results:

  • STSA demonstrates high agreement with reference alignments on the RPIC dataset, indicating its effectiveness in challenging cases.
  • On a large CATH database dataset, STSA achieved high sensitivity and specificity, outperforming state-of-the-art methods.
  • STSA produced longer alignments with lower root-mean-square deviation (rmsd).

Conclusions:

  • STSA is a robust and effective method for non-sequential protein structural alignment.
  • The approach provides competitive or superior performance compared to existing methods.
  • The STSA software and datasets are publicly available for research use.