Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2023.01.04.522819v1?rss=1
Authors: Park, H.-m., Won, J., Park, Y., Anzaku, E. T., Vankerschaver, J., Van Messem, A., De Neve, W., Shim, H.
Abstract:
CRISPR-Cas-Docker is a web server for in silico docking experiments with CRISPR RNAs (crRNAs) and Cas proteins. This web server aims at providing experimentalists with the optimal crRNA-Cas pair predicted computationally when prokaryotic genomes have multiple CRISPR arrays and Cas systems, as frequently observed in metagenomic data. CRISPR-Cas-Docker provides two methods to predict the optimal Cas protein given a particular crRN sequence: a structure-based method (in silico docking) and a sequence-based method (machine learning classification). For the structure-based method, users can either provide experimentally determined 3D structures of these macromolecules or use an integrated pipeline to generate 3D-predicted structures for in silico docking experiments. CRISPR-Cas-Docker is an optimized and integrated platform that provides users with 1) 3D-predicted crRNA structures and AlphaFold-predicted Cas protein structures, 2) the top-10 docking models for a particular crRNA-Cas protein pair, and 3) machine learning-based classification of crRNA into its Cas system type.
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