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Pspace: a program that assesses protein space.

Mihaly Mezei1, Ming-Ming Zhou

  • 1Department of Structural and Chemical Biology, Mount Sinai School of Medicine, New York University, One Gustave L, Levy Place, New York, New York 10029, USA. Mihaly.Mezei@mssm.edu.

Source Code for Biology and Medicine
|October 25, 2007
PubMed
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Pspace is a new program for protein structure homology modeling and ortholog searching. It helps select key proteins for experimental structure determination and efficiently matches sequence sets.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Genomics

Background:

  • Developing computational tools for protein structure analysis is crucial for understanding biological function.
  • Homology modeling requires a representative subset of protein structures for accurate predictions.
  • Identifying orthologous sequences is essential for comparative genomics and evolutionary studies.

Purpose of the Study:

  • To introduce Pspace, a novel program for protein structure description and ortholog searching.
  • To facilitate homology modeling by selecting optimal protein subsets for experimental structure determination.
  • To enhance ortholog identification through versatile sequence matching algorithms.

Main Methods:

  • Pspace utilizes dynamic prioritization of proteins based on their value in providing structural information.

Related Experiment Videos

  • The program employs ranking strategies for selecting proteins crucial for family structure description.
  • Sequence matching is performed in three distinct ways to identify potential or optimal orthologs.

    • Main Results:

    • The effectiveness of Pspace's covering strategies and ortholog search methods was validated using the bromodomain protein family.
    • The study demonstrated the program's capability in selecting informative protein subsets for structural analysis.
    • Successful ortholog identification was achieved through the implemented matching algorithms.

    Conclusions:

    • The Pspace program offers a robust framework for homology modeling and ortholog discovery.
    • The developed methods show promise for improving the efficiency of structural genomics initiatives.
    • The potential for extending Pspace's approach to encompass the broader protein universe is discussed.