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Related Concept Videos

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...
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...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...

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Related Experiment Video

Updated: May 16, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Effect of conformation sampling strategies in genetic algorithm for multiple protein docking.

Juan Esquivel-Rodríguez1, Daisuke Kihara

  • 1Department of Computer Science, College of Science, Purdue University, West Lafayette, IN 47907, USA. dkihara@purdue.edu.

BMC Proceedings
|November 24, 2012
PubMed
Summary

Optimizing the Multi-LZerD algorithm for protein complex structure prediction shows that excessive sampling is unnecessary for small complexes. Structural clustering effectively reduces redundant predictions, improving accuracy and computational efficiency.

Related Experiment Videos

Last Updated: May 16, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
08:49

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis

Published on: June 20, 2025

Area of Science:

  • Computational Biology
  • Structural Biology
  • Bioinformatics

Background:

  • Macromolecular protein complexes are vital for cellular functions, and understanding their structure aids in elucidating biological processes.
  • Multiple protein docking is a computational method for determining the structure of multimeric protein complexes.
  • The Multi-LZerD algorithm was previously developed to model protein complexes as graphs, using genetic algorithms for conformational sampling.

Purpose of the Study:

  • To investigate optimal configurations for the Multi-LZerD genetic algorithm.
  • To evaluate the impact of population size, crossover operations, and structural clustering thresholds on prediction accuracy and computational time.

Main Methods:

  • The Multi-LZerD algorithm was applied to predict the structures of three multimeric protein complexes.
  • Variations in population size, clustering thresholds, and genetic algorithm operations (mutation, crossover) were tested.
  • Computational time and prediction accuracy were analyzed for each configuration.

Main Results:

  • Increasing population size or including crossover operations did not significantly improve prediction accuracy for small complexes.
  • Structural clustering proved effective in minimizing redundant pairwise predictions.
  • Optimized parameter settings are crucial for efficient conformational space sampling.

Conclusions:

  • Excessive sampling is not required for accurate structure prediction of small protein complexes.
  • Structural clustering is a key strategy for enhancing the efficiency and success rate of near-native conformation identification.
  • Proper parameter tuning of genetic algorithms is essential for computational efficiency in large-scale structural studies.