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Updated: Jun 12, 2026

Chemical Dimerization-Induced Protein Condensates on Telomeres
08:52

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Published on: April 12, 2021

DIBER: protein, DNA or both?

Grzegorz Chojnowski1, Matthias Bochtler

  • 1MPG-PAN Junior Research Group, International Institute of Molecular and Cell Biology, 4 Ks. Trojdena Street, 02-109 Warsaw, Poland. gchojnowski@iimcb.gov.pl

Acta Crystallographica. Section D, Biological Crystallography
|June 3, 2010
PubMed
Summary
This summary is machine-generated.

The DIBER program predicts crystal contents (protein, DNA, or both) using native diffraction data. It achieves high accuracy, especially when integrating Phaser rotation-function scores, aiding structural biology research.

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Last Updated: Jun 12, 2026

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Published on: April 12, 2021

Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library
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Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

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06:48

CD Spectroscopy to Study DNA-Protein Interactions

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Area of Science:

  • Crystallography
  • Structural Biology
  • Bioinformatics

Background:

  • Accurate identification of crystal contents (protein, DNA, or both) is crucial for structural biology.
  • Existing methods may require additional data or complex analysis.

Purpose of the Study:

  • To develop and evaluate the DIBER program for classifying crystal contents using only native diffraction data.
  • To assess the performance of DIBER in standalone and combined modes.

Main Methods:

  • DIBER utilizes the cube root of reciprocal unit-cell volume and diffraction intensities at 3.4 Å resolution.
  • In combined mode, the Phaser rotation-function score with a B-DNA model is incorporated.
  • Performance is evaluated based on correct classification rates for protein, protein-DNA, and DNA crystals.

Main Results:

  • DIBER achieves high classification accuracy: 87.4% (standalone) and 90.2% (combined) for protein crystals.
  • It correctly classifies 69.1% (standalone) and 78.8% (combined) of protein-DNA crystals.
  • Reliable predictions (>80% accuracy) are possible for a significant portion of structures, particularly DNA crystals (83.3% standalone, 82.6% combined).

Conclusions:

  • DIBER effectively predicts crystal composition using native diffraction data.
  • Integrating Phaser scores in combined mode enhances classification accuracy.
  • An open-source version of DIBER is available, facilitating its use in structural biology research.