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Knowledge-based prediction of DNA atomic structure from nucleic sequence.

Marcos J Araúzo-Bravo1, Akinori Sarai

  • 1Department of Biosciences and Bioinformatics, Kyushu Institute of Technology, 1-1 Kawazu, Iizuka, Fukuoka 820-8502, Japan. marara@bse.kyutech.ac.jp

Genome Informatics. International Conference on Genome Informatics
|August 12, 2006
PubMed
Summary

This study presents a knowledge-based method for predicting DNA atomic structures from sequences. The approach accurately estimates 3D positions for B-DNA, outperforming genetic algorithms.

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Area of Science:

  • * Structural Biology
  • * Bioinformatics
  • * Computational Chemistry

Background:

  • * Predicting DNA's three-dimensional (3D) atomic structure from its nucleotide sequence is crucial for understanding genetic function and regulation.
  • * Existing methods may be computationally intensive or lack accuracy for specific DNA forms like B-DNA.
  • * Knowledge-based approaches offer a promising avenue for efficient and accurate structural predictions.

Purpose of the Study:

  • * To develop and validate a simple knowledge-based method for predicting the atomic structure of B-DNA from its sequence.
  • * To establish the accuracy of this method by comparing predicted structures to known B-DNA crystal structures.
  • * To assess the performance of the knowledge-based method against alternative computational techniques, such as genetic algorithms.

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Main Methods:

  • * Utilized existing B-DNA crystal structures to derive statistical distributions of conformational coordinates for trinucleotide base pairs and tetranucleotide steps.
  • * Employed these derived distributions to predict the 3D positions of non-hydrogen atoms in nucleic bases for arbitrary DNA sequences.
  • * Imposed constraints for Watson-Crick base pairing and adherence to the B-DNA conformation.

Main Results:

  • * The knowledge-based method successfully predicted B-DNA structures for sequences of varying lengths (6-12 base pairs).
  • * Achieved root-mean-square deviation (RMSE) of approximately 0.5 Å for translational and 5° for rotational conformational coordinates.
  • * Obtained an RMSE of around 1.1 Å for the non-hydrogen atom coordinates of nucleic bases.
  • * Demonstrated superior performance compared to a genetic algorithm-based method for B-DNA structure prediction.

Conclusions:

  • * The developed knowledge-based method provides an accurate and efficient means for predicting B-DNA atomic structures.
  • * This approach offers a valuable tool for structural biology and bioinformatics research, particularly for analyzing DNA sequences.
  • * The method's effectiveness highlights the utility of statistical distributions derived from known structures for computational modeling.