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Related Experiment Videos

MONSTER: inferring non-covalent interactions in macromolecular structures from atomic coordinate data.

William J Salerno1, Samuel M Seaver, Brian R Armstrong

  • 1Department of Biochemistry, Molecular Biology and Cell Biology, Northwestern University, Evanston, IL 60208-3500, USA.

Nucleic Acids Research
|June 25, 2004
PubMed
Summary

Monster is a web application that identifies stabilizing non-bonding interactions in macromolecular structures. This tool helps validate structures and guide functional analysis for researchers.

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Macromolecular structures contain complex non-bonding interactions that influence stability and function.
  • Accurate identification and analysis of these interactions are crucial for understanding biological processes.
  • Existing methods may lack comprehensive analysis or user-friendly interfaces for interaction inference.

Purpose of the Study:

  • To describe a novel web application, Monster, for inferring potentially stabilizing non-bonding interactions in macromolecular structures.
  • To provide a user-friendly platform for analyzing atomic coordinate data.
  • To facilitate the validation of experimentally determined structures and guide functional analysis.

Main Methods:

  • Development of a PERL wrapper (Monster) integrating in-house and public domain scripts.

Related Experiment Videos

  • Validation of atomic coordinate files.
  • Identification of interacting residues and assignment of interaction types.
  • Presentation of results in an interactive graphical format.

    • Main Results:

    • Monster successfully infers potentially stabilizing non-bonding interactions from atomic coordinate data.
    • The application provides an intuitive and interactive graphical output for visualized analysis.
    • The software integrates various scripts for comprehensive validation and interaction assignment.

    Conclusions:

    • Monster offers a valuable tool for researchers studying macromolecular structures.
    • It aids in mining and validating experimental structures.
    • The application can guide functional analysis by revealing key interactions.