Statistical models for discerning protein structures containing the DNA-binding helix-turn-helix motif |
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Authors: | McLaughlin William A Berman Helen M |
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Institution: | Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, 610 Taylor Road, Piscataway 08854-8087, USA. |
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Abstract: | A method for discerning protein structures containing the DNA-binding helix-turn-helix (HTH) motif has been developed. The method uses statistical models based on geometrical measurements of the motif. With a decision tree model, key structural features required for DNA binding were identified. These include a high average solvent-accessibility of residues within the recognition helix and a conserved hydrophobic interaction between the recognition helix and the second alpha helix preceding it. The Protein Data Bank was searched using a more accurate model of the motif created using the Adaboost algorithm to identify structures that have a high probability of containing the motif, including those that had not been reported previously. |
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Keywords: | helix-turn-helix motif DNA-binding machine learning structure classification |
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