CRISPR-Cas-Docker: web-based in silico docking and machine learning-based classification of crRNAs with Cas proteins

• DOI: 10.1186/s12859-023-05296-y
• Publication Date: 2023-04-25T10:03:30Z
• Authors: Ho-min Park; Jongbum Won; Yunseol Park; Esla Timothy Anzaku; Joris Vankerschaver; Arnout Van Messem; Wesley De Neve; Hyunjin Shim
• Keywords: Trans-activating crRNA

CRISPR-Cas-Docker is a web server for in silico docking experiments with CRISPR RNAs (crRNAs) and Cas proteins. This aims at providing experimentalists the optimal crRNA-Cas pair predicted computationally when prokaryotic genomes have multiple arrays systems, as frequently observed metagenomic data.CRISPR-Cas-Docker provides two methods to predict protein given particular crRNA sequence: structure-based method (in docking) sequence-based (machine learning classification). For method, users can either provide experimentally determined 3D structures of these macromolecules or use an integrated pipeline generate 3D-predicted experiments.CRISPR-Cas-Docker addresses need CRISPR-Cas community RNA-protein interactions by optimizing stages computation evaluation, specifically systems. available www.crisprcasdocker.org server, https://github.com/hshimlab/CRISPR-Cas-Docker open-source tool.