ArticleBMC structural biology2011
Benchmarks for flexible and rigid transcription factor-DNA docking.
Article in BMC structural biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Dockground: Expanding the Resource to Protein-DNA Complexes.Journal of molecular biology · 2026Article
- Insights into protein-DNA interactions from hydrogen bond energy-based comparative protein-ligand analyses.Proteins · 2022Article
- A comparative study of protein-ssDNA interactions.NAR genomics and bioinformatics · 2021Article
- An SVM-based method for assessment of transcription factor-DNA complex models.BMC bioinformatics · 2018Article
- Article
- Structural Insights into the Assembly of the Adeno-associated Virus Type 2 Rep68 Protein on the Integration Site AAVS1.The Journal of biological chemistry · 2015Article
- TFinDit: transcription factor-DNA interaction data depository.BMC bioinformatics · 2012Article
- High performance transcription factor-DNA docking with GPU computing.Proteome science · 2012Article
- DNA structural properties in the classification of genomic transcription regulation elements.Bioinformatics and biology insights · 2012Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStructural insight from transcription factor-DNA (TF-DNA) complexes is of paramount importance to our understanding of the affinity and specificity of TF-DNA interaction, and to the development of structure-based prediction of TF binding sites. Yet the majority of the TF-DNA complexes remain unsolved despite the considerable experimental efforts being made. Computational docking represents a promising alternative to bridge the gap. To facilitate the study of TF-DNA docking, carefully designed benchmarks are needed for performance evaluation and identification of the strengths and weaknesses of docking algorithms.
resultsWe constructed two benchmarks for flexible and rigid TF-DNA docking respectively using a unified non-redundant set of 38 test cases. The test cases encompass diverse fold families and are classified into easy and hard groups with respect to the degrees of difficulty in TF-DNA docking. The major parameters used to classify expected docking difficulty in flexible docking are the conformational differences between bound and unbound TFs and the interaction strength between TFs and DNA. For rigid docking in which the starting structure is a bound TF conformation, only interaction strength is considered.
conclusionsWe believe these benchmarks are important for the development of better interaction potentials and TF-DNA docking algorithms, which bears important implications to structure-based prediction of transcription factor binding sites and drug design.
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