title: An improved predictive recognition model for Cys(2)-His(2) zinc finger proteins.
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.
authors: Program in Gene Function and Expression, University of Massachusetts Medical School, Worcester, MA 01605, USA, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA, Department of Genetics, Washington University School of Medicine, St Louis, MO 63108, USA, Department of Biochemistry and Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA 01609, USA, Molecular Pathology Unit, Center for Computational and Integrative Biology, and Center for Cancer Research, Massachusetts General Hospital, Charlestown, MA 02129, USA, Department of Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA and Department of Pathology, Harvard Medical School, Boston, MA 02115, USA.
authors: Ankit
authors: A
authors: Gupta
authors: Ryan G
authors: RG
authors: Christensen
authors: Heather A
authors: HA
authors: Bell
authors: Mathew
authors: M
authors: Goodwin
authors: Ronak Y
authors: RY
authors: Patel
authors: Manishi
authors: M
authors: Pandey
authors: Metewo Selase
authors: MS
authors: Enuameh
authors: Amy L
authors: AL
authors: Rayla
authors: Cong
authors: C
authors: Zhu
authors: Stacey
authors: S
authors: Thibodeau-Beganny
authors: Michael H
authors: MH
authors: Brodsky
authors: J Keith
authors: JK
authors: Joung
authors: Scot A
authors: SA
authors: Wolfe
authors: Gary D
authors: GD
authors: Stormo
mesh_terms: D001185:Artificial Intelligence; D001665:Binding Sites; D004247:DNA / Q000737:chemistry; D004268:DNA-Binding Proteins / Q000737:chemistry / Q000378:metabolism*; D008954:Models, Biological; D059372:Nucleotide Motifs; D050436:Regulatory Elements, Transcriptional; D014157:Transcription Factors / Q000737:chemistry / Q000378:metabolism*; D016335:Zinc Fingers
chemical_list: D004268:DNA-Binding Proteins; D014157:Transcription Factors; D004247:DNA