title: ZiF-Predict: a web tool for predicting DNA-binding specificity in C2H2 zinc finger proteins.
abstract: Engineering zinc finger protein motifs for specific DNA targets in genomes is critical in the field of genome engineering. We have developed a computational method for predicting recognition helices for C2H2 zinc fingers that bind to specific target DNA sites. This prediction is based on artificial neural network using an exhaustive dataset of zinc finger proteins and their target DNA triplets. Users can select the option for two or three zinc fingers to be predicted either in a modular or synergistic fashion for the input DNA sequence. This method would be valuable for researchers interested in designing specific zinc finger transcription factors and zinc finger nucleases for several biological and biomedical applications. The web tool ZiF-Predict is available online at http://web.iitd.ac.in/~sundar/zifpredict/.
authors.affiliation: Department of Biochemical Engineering & Biotechnology, Indian Institute of Technology (IIT) Delhi, New Delhi, India.
authors.forename: Bhuvan
authors.initials: B
authors.lastname: Molparia
authors.forename: Kanav
authors.initials: K
authors.lastname: Goyal
authors.forename: Anita
authors.initials: A
authors.lastname: Sarkar
authors.forename: Sonu
authors.initials: S
authors.lastname: Kumar
authors.forename: Durai
authors.initials: D
authors.lastname: Sundar
mesh_terms: D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000378:metabolism*; D004268:DNA-Binding Proteins / Q000378:metabolism*; D020407:Internet; D016571:Neural Networks, Computer; D012984:Software; D016335:Zinc Fingers
chemical_list: D004268:DNA-Binding Proteins; D004247:DNA