Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action [preprint]

Preprint date

March 30, 2021

Authors

Kevin Lin (Ph.D. student), Maximilian Billmann (post-doctoral associate), Henry Ward (Ph.D. student), Ya-Chu Chang, Anja-Katrin Bielinsky, Chad L. Myers (professor)

Abstract

Impact

The key to advancing precision medicine is to deepen our understanding of drug modes-of-action (MOA). This project aims to develop a novel method for predicting MOA of potential drug compounds, providing an experimental and computational platform for efficient drug discovery.

Objectives/goals

To develop (1) a targeted CRISPR-Cas9 chemical-genetic screen approach, and (2) a computational method to predict drug mode-of-action from chemical-genetic interaction profiles

Methods/study population

Screening drugs against a gene deletion library can identify knockouts that modulate drug sensitivity. These chemical-genetic interaction (CGI) screens can be performed in human cell lines using a pooled lentiviral CRISPR-Cas9 approach to assess drug sensitivity/resistance of single-gene knockouts across the human genome. A targeted, rather than genome-wide, library can enable scaling these screens across many drugs.

Link to full paper

Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action

Keywords

computational biology, bioinformatics