Journal of
Computational Biology and Bioinformatics Research

  • Abbreviation: J. Comput. Biol. Bioinform. Res
  • Language: English
  • ISSN: 2141-2227
  • DOI: 10.5897/JCBBR
  • Start Year: 2009
  • Published Articles: 39

Full Length Research Paper

Bind-Predict: An algorithm for identifying zinc finger binding motifs in DNA sequences

Jayaraman Muthukumaran, Mannu Jayakanthan, Sanniyasi Chandrasekar and Premendu P. Mathur*
Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Pondicherry 605 014, India.
Email: [email protected], [email protected]

  •  Accepted: 24 August 2011
  •  Published: 31 December 2011


Zinc fingers are the most abundant eukaryotic DNA-binding motifs, which recognize DNA triplets with high efficacy and are used to develop chimeric enzymes for genome modification and site specific gene therapy. Considering the importance of zinc finger motifs and their recognition patterns we have developed a web interface with the incorporation of sequence based search algorithm named as Bind-Predict. This algorithm facilitates the identification of target sites of zinc finger proteins (ZFPs) in the given DNA sequences. This paper describes the concepts of the developed algorithm (scoring system) and its applications in predicting ZFP binding sites. Bind-Predict web interface contains dual applications such as a web server (Bind-Predict tool) and a database (Bind-PredictdB). In order to enhance its utility and to validate the prediction results, Bind-Predicttool is interconnected with Bind-PredictdB. The combination of sequence based pattern recognition followed by computing Bind-Predict scores is used to identify the ZFP binding sites in the direct (5′→3′), complementary (3′→5′), double strand DNA (5′→3′ and 3′→5′) and user-defined binding sites of the input sequence. Currently Bind-PredictdB contains 374 entries of zinc finger motifs comprising 91 engineered constructs, 250 naturally occurring and 33 zinc binuclear clusters. Bind-Predict web interface is freely accessible at


Key words: Engineered construct, site specific gene correction, targeted genome engineering, zinc binuclear cluster, zinc finger.