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Related Experiment Videos

SESAM: a relational database for structure and sequence of macromolecules.

M Huysmans1, J Richelle, S J Wodak

  • 1BIM, Everberg, Belgium.

Proteins
|January 1, 1991
PubMed
Summary

The SESAM system integrates diverse protein data, including structure and sequence, into a unified relational database. This enables advanced computational analyses for protein modeling and design.

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Bioinformatics

Background:

  • Protein data is often fragmented across various databases.
  • Integrating structural, sequence, and survey data is crucial for advanced analysis.
  • Existing systems may lack comprehensive data integration and validation.

Purpose of the Study:

  • To describe the SESAM system for integrating diverse protein data.
  • To highlight SESAM's capabilities in combining structural and non-structural information.
  • To showcase SESAM's utility in computational protein research.

Main Methods:

  • Development of the SESAM relational database using SYBASE.
  • Integration of data from Brookhaven Protein Databank and SWISS-PROT.
  • Implementation of a molecular dictionary for data validation and parameterization.

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  • Creation of interfaces for molecular graphics and mechanics software.

    • Main Results:

    • SESAM successfully integrates raw protein structure, sequence, and survey data.
    • The system includes a molecular dictionary for validation, checking coordinates, symbols, and chirality.
    • Data validation ensures compatibility with molecular graphics and mechanics software.
    • Interactive data access is achieved through efficient interfaces.

    Conclusions:

    • SESAM provides a powerful, integrated platform for protein data management.
    • The system facilitates advanced applications like homology-based modeling and protein design.
    • SESAM's validation and integration capabilities enhance the reliability of computational protein studies.