Basu Sushmita, Kurgan Lukasz
Department of Computer Science, College of Engineering, Virginia Commonwealth University, Virginia, VA, USA.
Methods Mol Biol. 2025;2947:269-284. doi: 10.1007/978-1-0716-4662-5_15.
DEPICTER2 is a modern web server that provides convenient access to a broad selection of sequence-based predictions of intrinsic disorder and disorder functions. It incorporates six state-of-the-art methods that include ANCHOR2, DFLpred, DisoLipPred, DisoRDPbind, flDPnn, and MoRF, which predict disordered linkers and disordered regions that bind proteins, peptides, DNA, RNA, and lipids. DEPICTER2 facilitates selection of any combination of the six methods and batch predictions for multiple protein sequences. The prediction process is fully automated, performed on the server side, and does not require installation of any software. We describe and motivate selection of the six predictors, detail the prediction process, and explain how to interact with this web resource. We focus on the aspects related to the prediction of intrinsic disorder functions and provide a case study that illustrates how to interpret results produced by DEPICTER2. The web server is freely available at http://biomine.cs.vcu.edu/servers/DEPICTER2/ .
DEPICTER2是一个现代的网络服务器，可方便地访问大量基于序列的内在无序和无序功能预测。它整合了六种先进方法，包括ANCHOR2、DFLpred、DisoLipPred、DisoRDPbind、flDPnn和MoRF，这些方法可预测与蛋白质、肽、DNA、RNA和脂质结合的无序连接子和无序区域。DEPICTER2便于选择六种方法的任意组合，并对多个蛋白质序列进行批量预测。预测过程完全自动化，在服务器端执行，无需安装任何软件。我们描述并推动了六种预测器的选择，详细介绍了预测过程，并解释了如何与这个网络资源进行交互。我们专注于与内在无序功能预测相关的方面，并提供了一个案例研究，说明如何解释DEPICTER2产生的结果。该网络服务器可在http://biomine.cs.vcu.edu/servers/DEPICTER2/ 免费获取。
