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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...
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.
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Conservation of Protein Domains Over Different Proteins02:26

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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

Protein structure prediction using basin-hopping.

Michael C Prentiss1, David J Wales, Peter G Wolynes

  • 1Center for Theoretical Biological Physics, University of California at San Diego, La Jolla, California 92093, USA. mcprentiss@gmail.com

The Journal of Chemical Physics
|June 17, 2008
PubMed
Summary
This summary is machine-generated.

Basin-hopping global optimization effectively identifies low-energy structures in protein energy landscapes, outperforming molecular dynamics for small systems. This method offers a novel optimization scheme for energy function development.

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Area of Science:

  • Computational chemistry
  • Biophysics
  • Protein structure prediction

Background:

  • Protein energy landscapes can be complex and rugged.
  • Associative memory Hamiltonian potentials exhibit mildly frustrated landscapes, similar to real proteins.

Purpose of the Study:

  • To evaluate basin-hopping global optimization for identifying low-lying minima in mildly frustrated energy landscapes.
  • To compare basin-hopping with molecular dynamics for protein structure prediction.

Main Methods:

  • Basin-hopping global optimization with random Cartesian coordinate perturbations.
  • Umbrella sampling to confirm global minima.
  • Bioinformatic techniques to reduce energy surface roughness.
  • Hamiltonian improvements focusing on excluded volume.

Main Results:

  • Basin-hopping successfully located lower energy minima and structures closer to experimental data for small systems compared to simulated annealing molecular dynamics.
  • The efficiency of the initial basin-hopping implementation decreased for larger systems.
  • Umbrella sampling confirmed the attainment of global minima.
  • Improvements to the energy surface and Hamiltonian resulted in better predicted structures.

Conclusions:

  • Basin-hopping is a promising optimization method for protein structure prediction on mildly frustrated energy landscapes.
  • The approach offers a novel and transferable scheme for future energy function development.
  • Further optimization of basin-hopping algorithms is needed for large systems.