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Protein structure computing in the genomic era.

T Schwede1, A Diemand, N Guex

  • 1Glaxo Wellcome Experimental Research, Swiss Institute for Bioinformatics, Plan-Les-Ouates.

Research in Microbiology
|June 24, 2000
PubMed
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Computational protein modeling aids life science research by predicting protein structures. This study introduces an integrated environment, Swiss-PdbViewer, SWISS-MODEL, and 3DCrunch, to advance 3-D model utilization in functional analysis and mutagenesis experiments.

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Genomics

Background:

  • Functional analysis of proteins from sequenced genomes is a key challenge in life sciences.
  • Computational methods, particularly comparative protein modeling, are vital for understanding protein function and designing experiments.
  • 3-D protein model structures offer significant assistance in rational mutagenesis experiment design.

Purpose of the Study:

  • To advance the application of 3-D model structures in functional protein analysis.
  • To develop an integrated computational environment for comparative protein modeling.

Main Methods:

  • Development of a comparative protein modeling environment.
  • Integration of Swiss-PdbViewer (sequence-to-structure workbench and viewing program).

Related Experiment Videos

  • Utilization of SWISS-MODEL (internet-based server for model generation).
  • Inclusion of a database of models generated with 3DCrunch.
  • Main Results:

    • An integrated environment for comparative protein modeling has been established.
    • The developed system facilitates the use of 3-D protein models in research.
    • The tools support the sequence-to-structure workflow and model generation.

    Conclusions:

    • The developed comparative protein modeling environment enhances the utility of 3-D structures in life science research.
    • This integrated approach supports functional analysis and the rational design of mutagenesis experiments.
    • Furthering the use of computational tools is crucial for advancing protein research.