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A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

PAVOOC: designing CRISPR sgRNAs using 3D protein structures and functional domain annotations

Moritz Schaefer¹, Djork-Arné Clevert², Bertram Weiss²

¹Computer Science, TU Berlin, D-10623 Berlin, Germany.

Bioinformatics (Oxford, England)

|November 17, 2018

Abstract

Summary:

Single-guide RNAs (sgRNAs) targeting the same gene can significantly vary in terms of efficacy and specificity. PAVOOC (Prediction And Visualization of On- and Off-targets for CRISPR) is a web-based CRISPR sgRNA design tool that employs state of the art machine learning models to prioritize most effective candidate sgRNAs. In contrast to other tools, it maps sgRNAs to functional domains and protein structures and visualizes cut sites on corresponding protein crystal structures. Furthermore, PAVOOC supports homology-directed repair template generation for genome editing experiments and the visualization of the mutated amino acids in 3D.

Availability And Implementation:

PAVOOC is available under https://pavooc.me and accessible using modern browsers (Chrome/Chromium recommended). The source code is hosted at github.com/moritzschaefer/pavooc under the MIT License. The backend, including data processing steps, and the frontend are implemented in Python 3 and ReactJS, respectively. All components run in a simple Docker environment.

Supplementary Information:

Supplementary data are available at Bioinformatics online.

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