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Related Concept Videos

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...
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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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Toward high-throughput, multicriteria protein-structure comparison and analysis.

Azhar Ali Shah1, Gianluigi Folino, Natalio Krasnogor

  • 1School of Computer Science, University of Nottingham, Nottingham NG81BB, U.K. psxaass@nottingham.ac.uk

IEEE Transactions on Nanobioscience
|July 24, 2010
PubMed
Summary

We developed a high-throughput distributed algorithm for multicriteria protein-structure comparison (MC-PSC) to accelerate biomedical research. This new method achieves high-quality similarity assessments for large datasets significantly faster than previous approaches.

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Area of Science:

  • Biomedical research
  • Structural bioinformatics
  • Computational biology

Background:

  • Protein-structure comparison (PSC) is crucial for drug design, protein folding, and structure prediction.
  • The multicriteria PSC (MC-PSC) problem requires diverse similarity notions for various applications.
  • Current MC-PSC methods are time-consuming for large-scale datasets.

Purpose of the Study:

  • To develop a high-throughput distributed reimplementation of ProCKSI for MC-PSC on very large datasets.
  • To enable real-time or near real-time protein structure comparisons for dedicated users.
  • To significantly reduce the time required for large-scale protein structure comparisons.

Main Methods:

  • Designed an innovative distributed algorithm for cluster/grid environments.
  • Implemented multiple popular PSC methods (USM, MaxCMO, FAST, DaliLite, CE, TMAlign).
  • Incorporated a distributed consensus-building procedure for similarity assessment.

Main Results:

  • Achieved ProCKSI's similarity assessment quality with a fraction of the original time.
  • Demonstrated efficient target-against-all comparisons for large protein structure datasets.
  • Showcased efficient all-against-all comparisons for very large-scale datasets.

Conclusions:

  • The proposed distributed method significantly accelerates MC-PSC for large datasets.
  • This advancement is key for enabling real-time structural bioinformatics applications.
  • Further challenges remain in achieving true real-time MC-PSC.