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Macromolecular query language (MMQL): prototype data model and implementation

I N Shindyalov1, W Chang, C Pu

  • 1Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032.

Protein Engineering
|November 1, 1994
PubMed
Summary
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Macromolecular Query Language (MMQL) simplifies complex biological structure queries. This extensible language uses filters and patterns for intuitive data retrieval from macromolecular structures.

Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Analyzing 3-D structures of biological macromolecules requires specialized tools.
  • Existing methods may lack intuitive query capabilities for complex structural features.

Purpose of the Study:

  • To introduce the Macromolecular Query Language (MMQL) as an intuitive and extensible interpretive language.
  • To demonstrate MMQL's capability in posing queries about experimental or derived features of macromolecular 3-D structures.

Main Methods:

  • MMQL utilizes a combination of filter and pattern grammar for query expression.
  • Filters select object attributes (e.g., compound name, resolution).
  • Patterns query primary sequence, contacts, hydrogen bonding, secondary structure, and amino acid properties.

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Main Results:

  • MMQL allows for the expression of a wide range of biological queries, including complex motif identification.
  • Performance metrics compare MMQL queries on PDB files with and without a prototype object-oriented database (OOPDB).
  • MMQLlib (C++ library) and PDBlib (C++ library for PDB data) facilitate query processing and data representation.

Conclusions:

  • MMQL offers an intuitive syntax for complex queries on macromolecular structures.
  • The MMQL system, built upon MMQLlib and PDBlib, is extensible and can query data from various sources including PDB files and databases.
  • MMQL provides a powerful approach for exploring structural biology data.