ArticleBMC bioinformatics2013
Automatic workflow for the classification of local DNA conformations.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Conformational analysis of nucleic acids for optimizing DNA and RNA topological models.Nucleic acids research · 2026Article
- 3dDNAscoreA: A scoring function for evaluation of DNA 3D structures.Biophysical journal · 2024Article
- Accurate prediction of B-form/A-form DNA conformation propensity from primary sequence: A machine learning and free energy handshake.Patterns (New York, N.Y.) · 2021Article
- Ion Binding Properties and Dynamics of theJournal of chemical information and modeling · 2020Article
- Biologically important conformational features of DNA as interpreted by quantum mechanics and molecular mechanics computations of its simple fragments.Journal of molecular modeling · 2018Article
- A DNA structural alphabet provides new insight into DNA flexibility.Acta crystallographica. Section D, Structural biology · 2018Article
- Article
- Polarizable Force Field for DNA Based on the Classical Drude Oscillator: I. Refinement Using Quantum Mechanical Base Stacking and Conformational Energetics.Journal of chemical theory and computation · 2017Article
- Assessing the Current State of Amber Force Field Modifications for DNA.Journal of chemical theory and computation · 2016Article
- DNATCO: assignment of DNA conformers at dnatco.org.Nucleic acids research · 2016Article
- Protein flexibility in the light of structural alphabets.Frontiers in molecular biosciences · 2015Review
- Bioinformatic analysis of the protein/DNA interface.Nucleic acids research · 2014Article
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5 authors.
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Abstract
backgroundA growing number of crystal and NMR structures reveals a considerable structural polymorphism of DNA architecture going well beyond the usual image of a double helical molecule. DNA is highly variable with dinucleotide steps exhibiting a substantial flexibility in a sequence-dependent manner. An analysis of the conformational space of the DNA backbone and the enhancement of our understanding of the conformational dependencies in DNA are therefore important for full comprehension of DNA structural polymorphism.
resultsA detailed classification of local DNA conformations based on the technique of Fourier averaging was published in our previous work. However, this procedure requires a considerable amount of manual work. To overcome this limitation we developed an automatic classification method consisting of the combination of supervised and unsupervised approaches. A proposed workflow is composed of k-NN method followed by a non-hierarchical single-pass clustering algorithm. We applied this workflow to analyze 816 X-ray and 664 NMR DNA structures released till February 2013. We identified and annotated six new conformers, and we assigned four of these conformers to two structurally important DNA families: guanine quadruplexes and Holliday (four-way) junctions. We also compared populations of the assigned conformers in the dataset of X-ray and NMR structures.
conclusionsIn the present work we developed a machine learning workflow for the automatic classification of dinucleotide conformations. Dinucleotides with unassigned conformations can be either classified into one of already known 24 classes or they can be flagged as unclassifiable. The proposed machine learning workflow permits identification of new classes among so far unclassifiable data, and we identified and annotated six new conformations in the X-ray structures released since our previous analysis. The results illustrate the utility of machine learning approaches in the classification of local DNA conformations.
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