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NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode
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Generalized fragment picking in Rosetta: design, protocols and applications.

Dominik Gront1, Daniel W Kulp, Robert M Vernon

  • 1Faculty of Chemistry, University of Warsaw, Warsaw, Poland. dgront@chem.uw.edu.pl

Plos One
|September 3, 2011
PubMed
Summary

A new fragment picking program enhances protein structure prediction by offering greater control and flexibility. This tool provides reliable building blocks for de novo structure prediction, improving upon previous methods.

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Last Updated: May 29, 2026

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Biochemistry

Background:

  • Protein structure prediction is crucial for understanding biological function.
  • Existing methods like Rosetta rely on fragment assembly from known structures.
  • The nnmake program was a precursor for fragment selection in these protocols.

Purpose of the Study:

  • To introduce a novel, object-oriented program for fragment picking.
  • To enhance the functionality and flexibility of fragment selection in protein structure modeling.
  • To enable new approaches in de novo structure prediction and loop modeling.

Main Methods:

  • Developed an object-oriented program for fragment selection from structural databases.
  • Implemented features for modularity, extensibility, and workflow customization.
  • Designed a customizable scoring system for fragment evaluation.

Main Results:

  • The new program offers extended functionality compared to nnmake.
  • It provides comparable or superior building blocks for ab initio structure prediction.
  • Demonstrated diverse applications now accessible through the new program.

Conclusions:

  • The developed fragment picking program represents a significant advancement in computational structural biology.
  • Its design facilitates greater control and customization in protein structure modeling.
  • The tool is expected to broaden the scope of de novo structure prediction and related applications.