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      Onco-Regulon: an integrated database and software suite for site specific targeting of transcription factors of cancer genes

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          Abstract

          Transcription factors (TFs) bind at multiple sites in the genome and regulate expression of many genes. Regulating TF binding in a gene specific manner remains a formidable challenge in drug discovery because the same binding motif may be present at multiple locations in the genome. Here, we present Onco-Regulon ( http://www.scfbio-iitd.res.in/software/onco/NavSite/index.htm), an integrated database of regulatory motifs of cancer genes clubbed with Unique Sequence-Predictor (USP) a software suite that identifies unique sequences for each of these regulatory DNA motifs at the specified position in the genome. USP works by extending a given DNA motif, in 5′→3′, 3′ →5′ or both directions by adding one nucleotide at each step, and calculates the frequency of each extended motif in the genome by Frequency Counter programme. This step is iterated till the frequency of the extended motif becomes unity in the genome. Thus, for each given motif, we get three possible unique sequences. Closest Sequence Finder program predicts off-target drug binding in the genome. Inclusion of DNA-Protein structural information further makes Onco-Regulon a highly informative repository for gene specific drug development. We believe that Onco-Regulon will help researchers to design drugs which will bind to an exclusive site in the genome with no off-target effects, theoretically.

          Database URL: http://www.scfbio-iitd.res.in/software/onco/NavSite/index.htm

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          Most cited references27

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          Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase.

          L Gold, C Tuerk (1990)
          High-affinity nucleic acid ligands for a protein were isolated by a procedure that depends on alternate cycles of ligand selection from pools of variant sequences and amplification of the bound species. Multiple rounds exponentially enrich the population for the highest affinity species that can be clonally isolated and characterized. In particular one eight-base region of an RNA that interacts with the T4 DNA polymerase was chosen and randomized. Two different sequences were selected by this procedure from the calculated pool of 65,536 species. One is the wild-type sequence found in the bacteriophage mRNA; one is varied from wild type at four positions. The binding constants of these two RNA's to T4 DNA polymerase are equivalent. These protocols with minimal modification can yield high-affinity ligands for any protein that binds nucleic acids as part of its function; high-affinity ligands could conceivably be developed for any target molecule.
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            The role of DNA shape in protein-DNA recognition

            The recognition of specific DNA sequences by proteins is thought to depend on two types of mechanisms: one that involves the formation of hydrogen bonds with specific bases, primarily in the major groove, and one involving sequence-dependent deformations of the DNA helix. By comprehensively analyzing the three dimensional structures of protein-DNA complexes, we show that the binding of arginines to narrow minor grooves is a widely used mode for protein-DNA recognition. This readout mechanism exploits the phenomenon that narrow minor grooves strongly enhance the negative electrostatic potential of the DNA. The nucleosome core particle offers a striking example of this effect. Minor groove narrowing is often associated with the presence of A-tracts, AT-rich sequences that exclude the flexible TpA step. These findings suggest that the ability to detect local variations in DNA shape and electrostatic potential is a general mechanism that enables proteins to use information in the minor groove, which otherwise offers few opportunities for the formation of base-specific hydrogen bonds, to achieve DNA binding specificity.
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              Origins of specificity in protein-DNA recognition.

              Specific interactions between proteins and DNA are fundamental to many biological processes. In this review, we provide a revised view of protein-DNA interactions that emphasizes the importance of the three-dimensional structures of both macromolecules. We divide protein-DNA interactions into two categories: those when the protein recognizes the unique chemical signatures of the DNA bases (base readout) and those when the protein recognizes a sequence-dependent DNA shape (shape readout). We further divide base readout into those interactions that occur in the major groove from those that occur in the minor groove. Analogously, the readout of the DNA shape is subdivided into global shape recognition (for example, when the DNA helix exhibits an overall bend) and local shape recognition (for example, when a base pair step is kinked or a region of the minor groove is narrow). Based on the >1500 structures of protein-DNA complexes now available in the Protein Data Bank, we argue that individual DNA-binding proteins combine multiple readout mechanisms to achieve DNA-binding specificity. Specificity that distinguishes between families frequently involves base readout in the major groove, whereas shape readout is often exploited for higher resolution specificity, to distinguish between members within the same DNA-binding protein family.
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                Author and article information

                Journal
                Database (Oxford)
                Database (Oxford)
                databa
                databa
                Database: The Journal of Biological Databases and Curation
                Oxford University Press
                1758-0463
                2016
                10 August 2016
                10 August 2016
                : 2016
                : baw116
                Affiliations
                1Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology-Delhi, New Delhi, India
                2Kusuma School of Biological Sciences, Indian Institute of Technology-Delhi, Delhi, India
                3Labaratory of Molecular Biology, South Asian University, New Delhi, India
                4Department of Chemistry, Indian Institute of Technology-Delhi, Delhi
                Author notes
                *Corresponding author: Email: nmrinal@ 123456gmail.com
                Correspondence may also be addressed to B. Jayaram. Email: bjayaram@ 123456chemistry.iitd.ac.in

                Citation details: Tomar,N., Mishra,A., Mrinal,N. et al. Onco-Regulon: an integrated database and software suite for site specific targeting of transcription factors of cancer genes. Database (2016) Vol. 2016: article ID baw116; doi:10.1093/database/baw116

                Article
                baw116
                10.1093/database/baw116
                4980569
                27515825
                fdc9bd7e-6f90-4988-8931-36eb784b61eb
                © The Author(s) 2016. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 2 August 2015
                : 12 July 2016
                : 13 July 2016
                Page count
                Pages: 12
                Categories
                Original Article

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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