GSBS Student Publications
GSBS Program
Biochemistry & Molecular Pharmacology
Publication Date
2014-04-01
UMMS Affiliation
Program in Gene Function and Expression; Department of Biochemistry and Molecular Pharmacology; Program in Molecular Medicine
Document Type
Article
Disciplines
Biochemistry | Computational Biology
Abstract
Cys(2)-His(2) zinc finger proteins (ZFPs) are the largest family of transcription factors in higher metazoans. They also represent the most diverse family with regards to the composition of their recognition sequences. Although there are a number of ZFPs with characterized DNA-binding preferences, the specificity of the vast majority of ZFPs is unknown and cannot be directly inferred by homology due to the diversity of recognition residues present within individual fingers. Given the large number of unique zinc fingers and assemblies present across eukaryotes, a comprehensive predictive recognition model that could accurately estimate the DNA-binding specificity of any ZFP based on its amino acid sequence would have great utility. Toward this goal, we have used the DNA-binding specificities of 678 two-finger modules from both natural and artificial sources to construct a random forest-based predictive model for ZFP recognition. We find that our recognition model outperforms previously described determinant-based recognition models for ZFPs, and can successfully estimate the specificity of naturally occurring ZFPs with previously defined specificities.
Rights and Permissions
Copyright © The Author(s) 2014. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
DOI of Published Version
10.1093/nar/gku132
Source
Nucleic Acids Res. 2014 Apr;42(8):4800-12. doi: 10.1093/nar/gku132. Epub 2014 Feb 12. Link to article on publisher's site
Journal/Book/Conference Title
Nucleic acids research
Related Resources
PubMed ID
24523353
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 3.0 License
Repository Citation
Gupta A, Christensen RG, Bell HA, Goodwin M, Patel RY, Pandey M, Enuameh MS, Rayla AL, Zhu C, Thibodeau-Beganny S, Brodsky MH, Joung JK, Wolfe SA, Stormo GD. (2014). An improved predictive recognition model for Cys(2)-His(2) zinc finger proteins. GSBS Student Publications. https://doi.org/10.1093/nar/gku132. Retrieved from https://escholarship.umassmed.edu/gsbs_sp/1904