摘要
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/.
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/.
基金
supported partly by the Department of Biotechnology (DBT) under the IYBA scheme and Department of Information Technology (DIT), Govt. of India to DS
partly by a Summer Undergraduate Research Award (SURA) from IIT Delhi to BM and KG.
