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ZiF-Predict：用于预测 C2H2 锌指蛋白 DNA 结合特异性的网络工具。

ZiF-Predict: a web tool for predicting DNA-binding specificity in C2H2 zinc finger proteins.

机构信息

Department of Biochemical Engineering & Biotechnology, Indian Institute of Technology (IIT) Delhi, New Delhi, India.

出版信息

Genomics Proteomics Bioinformatics. 2010 Jun;8(2):122-6. doi: 10.1016/S1672-0229(10)60013-7.

DOI:10.1016/S1672-0229(10)60013-7
PMID:20691397
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5054441/
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/.

摘要

在基因组工程领域，针对特定的 DNA 目标设计锌指蛋白结构域是至关重要的。我们开发了一种计算方法，可以预测 C2H2 锌指蛋白与特定靶 DNA 位点结合的识别螺旋。该预测是基于人工神经网络，使用了锌指蛋白及其靶 DNA 三核苷酸的详尽数据集。用户可以选择以模块化或协同方式预测两个或三个锌指，用于输入 DNA 序列。对于有兴趣设计特定锌指转录因子和锌指核酸酶的研究人员来说，该方法具有重要价值，可应用于多个生物学和生物医学领域。在线 Web 工具 ZiF-Predict 可在 http://web.iitd.ac.in/~sundar/zifpredict/ 获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4d5/5054441/a11ac5ce7c6d/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4d5/5054441/c11dbbe97399/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4d5/5054441/a11ac5ce7c6d/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4d5/5054441/c11dbbe97399/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4d5/5054441/a11ac5ce7c6d/gr2.jpg

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BMC Genomics. 2009 Sep 9;10:421. doi: 10.1186/1471-2164-10-421.
2
Rapid "open-source" engineering of customized zinc-finger nucleases for highly efficient gene modification.用于高效基因修饰的定制锌指核酸酶的快速“开源”工程。
Mol Cell. 2008 Jul 25;31(2):294-301. doi: 10.1016/j.molcel.2008.06.016.
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Zinc finger nucleases: custom-designed molecular scissors for genome engineering of plant and mammalian cells.
Trends Genet. 2017 Nov;33(11):871-881. doi: 10.1016/j.tig.2017.08.006. Epub 2017 Sep 19.
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An ensemble micro neural network approach for elucidating interactions between zinc finger proteins and their target DNA.一种用于阐明锌指蛋白与其靶DNA之间相互作用的集成微神经网络方法。
BMC Genomics. 2016 Dec 22;17(Suppl 13):1033. doi: 10.1186/s12864-016-3323-9.
5
Exploiting the recognition code for elucidating the mechanism of zinc finger protein-DNA interactions.利用识别密码阐明锌指蛋白与DNA相互作用的机制。
BMC Genomics. 2016 Dec 22;17(Suppl 13):1037. doi: 10.1186/s12864-016-3324-8.
6
nDNA-Prot: identification of DNA-binding proteins based on unbalanced classification.nDNA-Prot：基于不平衡分类的 DNA 结合蛋白识别。
BMC Bioinformatics. 2014 Sep 8;15(1):298. doi: 10.1186/1471-2105-15-298.
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enDNA-Prot: identification of DNA-binding proteins by applying ensemble learning.enDNA-Prot：通过应用集成学习识别DNA结合蛋白。
Biomed Res Int. 2014;2014:294279. doi: 10.1155/2014/294279. Epub 2014 May 26.
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Prediction of DNA-binding specificity in zinc finger proteins.锌指蛋白中 DNA 结合特异性的预测。
J Biosci. 2012 Jul;37(3):483-91. doi: 10.1007/s12038-012-9213-7.
9
Re-programming DNA-binding specificity in zinc finger proteins for targeting unique address in a genome.重编程锌指蛋白中的DNA结合特异性以靶向基因组中的独特位点。
Syst Synth Biol. 2010 Dec;4(4):323-9. doi: 10.1007/s11693-011-9077-4. Epub 2011 Feb 19.
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