Abstract

BackgroundProtein-DNA interactions play an important role in many fundamental biological activities such as DNA replication, transcription and repair. Identification of amino acid residues involved in DNA binding site is critical for understanding of the mechanism of gene regulations. In the last decade, there have been a number of computational approaches developed to predict protein-DNA binding sites based on protein sequence and/or structural information.ResultsIn this article, we present metaDBSite, a meta web server to predict DNA-binding residues for DNA-binding proteins. MetaDBSite integrates the prediction results from six available online web servers: DISIS, DNABindR, BindN, BindN-rf, DP-Bind and DBS-PRED and it solely uses sequence information of proteins. A large dataset of DNA-binding proteins is constructed from the Protein Data Bank and it serves as a gold-standard benchmark to evaluate the metaDBSite approach and the other six predictors.ConclusionsThe comparison results show that metaDBSite outperforms single individual approach. We believe that metaDBSite will become a useful and integrative tool for protein DNA-binding residues prediction. The MetaDBSite web-server is freely available at http://projects.biotec.tu-dresden.de/metadbsite/ and http://sysbio.zju.edu.cn/metadbsite.

Highlights

  • Protein-DNA interactions play an important role in many fundamental biological activities such as DNA replication, transcription and repair

  • The comparison results show that metaDBSite outperforms single individual approach

  • We believe that metaDBSite will become a useful tool for predicting protein-DNA binding residues for relevant researchers

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Summary

Introduction

Protein-DNA interactions play an important role in many fundamental biological activities such as DNA replication, transcription and repair. Identification of amino acid residues involved in DNA binding site is critical for understanding of the mechanism of gene regulations. There have been a number of computational approaches developed to predict protein-DNA binding sites based on protein sequence and/or structural information. Transcription factors bind to specific DNA sequences in promoters to activate gene expression [1]. Protein-DNA interactions play important roles in many other biological processes, including DNA replication, DNA repairing, viral infection, DNA packing and DNA modifications [2]. Predicting the DNA binding properties of these DNA binding proteins will be very useful in helping understanding their biological functions

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