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Related Concept Videos

Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

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 form...
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...
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...
Protein and Protein Structures02:15

Protein and Protein Structures

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...
Conservation of Protein Domains02:26

Conservation of Protein Domains

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 form...
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.

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Related Experiment Video

Updated: Jun 26, 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

A multi-objective evolutionary algorithm for protein structure prediction with immune operators.

M V Judy1, K S Ravichandran, K Murugesan

  • 1School of Computing, SASTRA University, Thanjavur, India. judynair@mca.sastra.edu

Computer Methods in Biomechanics and Biomedical Engineering
|January 28, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a modified immune-inspired evolutionary algorithm (MI-PAES) for protein structure prediction. MI-PAES effectively utilizes hydrophobic interaction knowledge, outperforming canonical genetic algorithms in accuracy and speed.

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

Background:

  • Protein structure prediction is a complex multi-objective optimization problem.
  • Potential energy functions involve conflicting local and non-local atomic interactions.
  • Hydrophobic interactions are crucial driving forces in protein folding.

Purpose of the Study:

  • To develop a novel evolutionary algorithm, MI-PAES, for enhanced protein structure prediction.
  • To leverage prior knowledge of hydrophobic interactions within an evolutionary strategy.
  • To improve upon existing multi-objective optimization algorithms for this task.

Main Methods:

  • Modification of the immune-inspired Pareto archived evolutionary strategy (I-PAES).
  • Integration of hydrophobic interaction knowledge into the algorithm.
  • Comparative analysis against canonical genetic algorithms (GA) and other evolutionary approaches.

Main Results:

  • The proposed MI-PAES demonstrates superior search ability compared to canonical GA.
  • MI-PAES achieves comparable or better results in terms of solution quality and computational time.
  • Effective exploitation of hydrophobic interaction priors is confirmed.

Conclusions:

  • MI-PAES offers a promising approach for multi-objective protein structure prediction.
  • The algorithm shows significant potential for improving the accuracy and efficiency of predicting protein conformations.
  • This modified strategy advances the application of evolutionary computation in bioinformatics.