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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 Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...

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Updated: Jun 20, 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

Scatter search algorithm for protein structure prediction.

Nashat Mansour1, Christine Kehyayan, Hassan Khachfe

  • 1Department of Computer Science and Mathematics, Lebanese American University, Lebanon. nmansour@lau.edu.lb

International Journal of Bioinformatics Research and Applications
|September 26, 2009
PubMed
Summary

We developed a Scatter Search (SS) algorithm to predict protein 3D structures using torsion angles. This method effectively generates low-energy protein conformations, crucial for understanding protein function and drug design.

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Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Biophysics

Background:

  • Predicting three-dimensional (3D) protein structures from amino acid sequences is a fundamental challenge in biology.
  • Accurate protein structure prediction is vital for understanding biological function, disease mechanisms, and drug discovery.
  • Existing methods often face challenges in efficiently exploring the vast conformational space of proteins.

Purpose of the Study:

  • To introduce a novel Scatter Search (SS) algorithm for predicting protein 3D structures.
  • To utilize a torsion angle representation for protein structure generation.
  • To minimize the energy function associated with the predicted protein structures.

Main Methods:

  • The study employs a Scatter Search (SS) algorithm, an evolutionary computation technique.
  • The algorithm operates on a population of candidate protein structures represented by torsion angles.
  • Evolutionary operations are applied to iteratively refine structures, balancing search intensification and diversification.

Main Results:

  • The SS algorithm was evaluated on three proteins from the Protein Data Bank (PDB).
  • The algorithm successfully generated 3D protein structures with favorable sub-optimal energy values.
  • Root Mean Square Deviation (RMSD) values indicated promising structural accuracy relative to reference structures.

Conclusions:

  • The proposed Scatter Search algorithm is effective for predicting protein 3D structures.
  • The torsion angle representation combined with SS provides a viable approach for energy minimization in protein folding.
  • The results demonstrate the potential of this method for advancing structural bioinformatics research.