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Related Concept Videos

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...
Protein Folding01:22

Protein Folding

Overview
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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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

An adaptive bin framework search method for a beta-sheet protein homopolymer model.

Alena Shmygelska1, Holger H Hoos

  • 1Department of Structural Biology, Stanford University, Stanford, CA 94305, USA. alenas@stanford.edu

BMC Bioinformatics
|April 25, 2007
PubMed
Summary

This study introduces a novel bin framework for efficient protein structure prediction by adaptively storing and retrieving optimal protein conformations. This method significantly improves search efficiency for complex systems, outperforming existing generalized ensemble techniques.

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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:

  • Biomolecular Physics
  • Computational Biology
  • Algorithm Design

Background:

  • Protein structure prediction is crucial for understanding protein function, with growing sequence data outpacing structure determination.
  • The challenge lies in efficiently searching vast conformational spaces to find the native protein structure.
  • This is particularly relevant for ab initio protein structure prediction and complex search landscapes.

Purpose of the Study:

  • To develop a novel approach for efficiently searching protein conformational space.
  • To address the challenge of finding global optima in complex energy landscapes.
  • To improve the efficiency of ab initio protein structure prediction.

Main Methods:

  • Introduction of a novel bin framework for adaptive storage and retrieval of locally optimal protein conformations.
  • Development of adaptive mechanisms for selecting conformations to store based on existing memory.
  • Implementation of biased retrieval strategies to mitigate search stagnation.

Main Results:

  • The proposed bin framework enables adaptive and reactive search strategies.
  • Adaptive mechanisms enhance the management of stored conformations.
  • Biased retrieval from memory helps overcome search stagnation.

Conclusions:

  • The bin framework, coupled with Monte Carlo search, demonstrates superior performance.
  • Achieves significantly better results compared to state-of-the-art generalized ensemble methods.
  • Validated on a protein-like homopolymer model within a face-centered cubic lattice.