Modelling repressor proteins docking to DNA

Patrick Aloy, Gidon Moont, Henry A. Gabb, Enrique Querol, Francesc X. Aviles, Michael J.E. Sternberg

Research output: Contribution to journalArticleResearchpeer-review

48 Citations (Scopus)

Abstract

The docking of repressor proteins to DNA starting from the unbound protein and model-built DNA coordinates is modeled computationally. The approach was evaluated on eight repressor/DNA complexes that employed different modes for protein/DNA recognition. The global search is based on a protein-protein docking algorithm that evaluates shape and electrostatic complementarity, which was modified to consider the importance of electrostatic features in DNA-protein recognition. Complexes were then ranked by an empirical score for the observed amino acid/nucleotide pairings (i.e., protein-DNA pair potentials) derived from a database of 20 protein/DNA complexes. A good prediction had at least 65% of the correct contacts modeled. This approach was able to identify a good solution at rank four or better for three out of the eight complexes. Predicted complexes were filtered by a distance constraint based on experimental data defining the DNA footprint. This improved coverage to four out of eight complexes having a good model at rank four or better. The additional use of amino acid mutagenesis and phylogenetic data defining residues on the repressor resulted in between 2 and 27 models that would have to be examined to find a good solution for seven of the eight test systems. This study shows that starting with unbound coordinates one can predict three-dimensional models for protein/DNA complexes that do not involve gross conformational changes on association.
Original languageEnglish
Pages (from-to)535-549
JournalProteins: Structure, Function and Genetics
Volume33
Issue number4
DOIs
Publication statusPublished - 1 Dec 1998

Keywords

  • Base recognition
  • Docking
  • Prediction
  • Protein-DNA
  • Structure

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