NDLI: Prediction of Specific Protein-DNA Recognition by Knowledge-based Two-body and Three-body Interaction Potentials

Content Provider	IEEE Xplore Digital Library
Author	Guijun Zhao Carson, M.B. Hui Lu
Copyright Year	2007
Description	Author affiliation: Univ. of Ilinois at Chicago, Chicago (Guijun Zhao; Carson, M.B.; Hui Lu)
Abstract	Gene regulation requires specific protein-DNA interactions. Detecting the short and variable DNA sequences in gene promoter regions to which transcription factors (TF) bind is a difficult challenge in bioinformatics. Here we have developed two-body and three-body interaction potentials that are able to assess protein-DNA interaction and achieve a higher level of specificity in the recognition of TF-binding sites. The potentials were calculated using experimentally characterized 3-D structures of protein-DNA complexes. We implemented two approaches in order to evaluate the potentials. Using the first method, we calculated the Z-score of the potential energy of a true TF-binding sequence when compared to 50,000 randomly generated DNA sequences. The second method allowed us to take advantage of the ability of statistical potentials to recognize novel TF-binding sites within the promoter region of genes. We found that the three-body potential, which takes into account the interaction between a DNA base and a protein residue with regard to the effect of a neighboring DNA base, had a better average Z-score than that of the two-body potential. This neighbor effect suggests that the local conformation of DNA does play a critical role in specific residue-base recognition. In all cases, the potentials developed here outperformed published results. The two sets of potentials were tested further by applying them in genome-scale TF-binding site prediction for the CRP protein in E. coli. Out of the 142 cases, 28% of the true binding sites ranked first (i.e. had the lowest Z-score), while in 59 % of cases the true binding site ranked in the top 5. We show with these results that statistical potentials can be used in genome-scale TF-binding site prediction.
Starting Page	5017
Ending Page	5020
File Size	173656
Page Count	4
File Format	PDF
ISBN	9781424407873
ISSN	1557170X
DOI	10.1109/IEMBS.2007.4353467
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	DNA Sequences Protein engineering Bioinformatics Genomics Amino acids Statistical analysis Protocols Crystallography Nuclear magnetic resonance
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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