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12621 Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action

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 more efficient drug discovery. O...

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Autores principales: Lin, Kevin, Billmann, Maximilian, Ward, Henry, Chang, Ya-Chu, Bielinsky, Anja-Katrin, Myers, Chad L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8827809/
http://dx.doi.org/10.1017/cts.2021.661
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author Lin, Kevin
Billmann, Maximilian
Ward, Henry
Chang, Ya-Chu
Bielinsky, Anja-Katrin
Myers, Chad L.
author_facet Lin, Kevin
Billmann, Maximilian
Ward, Henry
Chang, Ya-Chu
Bielinsky, Anja-Katrin
Myers, Chad L.
author_sort Lin, Kevin
collection PubMed
description 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 more 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. CGI profiles can be derived from phenotypic screen readouts. These profiles are analogous to genetic interaction (GI) profiles, which represent sensitivity/resistance of gene knockouts to a second gene knockout rather than a drug. To computationally predict a drug’s genetic target, we leverage the property that a drug’s CGI profile will be similar to its target’s GI profile. RESULTS/ANTICIPATED RESULTS: Five proof-of-principle screens will be conducted with compounds that have existing genome-wide profiles and well-characterized MOA. I will generate CGI profiles for these five compounds and identify genes that are drug-sensitizers or drug-suppressors. I will then evaluate whether targeted library screens can recapitulate the CGIs found in genome-wide screens. Finally, I will develop a computational tool to integrate these CGI profiles with GI profiles (derived from another project) to predict gene-level and bioprocess-level drug targets. These predictions (from both targeted and genome-wide profiles) will be benchmarked against a drug-target and drug-bioprocess standard. DISCUSSION/SIGNIFICANCE OF FINDINGS: This work will develop a scalable, targeted chemical-genetic screen approach to discovering how putative therapeutics work. The targeted screen workflow provides a method for higher-throughput drug screening. The computational pipeline provides a powerful tool for exploring the MOA of uncharacterized drugs or repurposing FDA-approved drugs.
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spelling pubmed-88278092022-02-28 12621 Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action Lin, Kevin Billmann, Maximilian Ward, Henry Chang, Ya-Chu Bielinsky, Anja-Katrin Myers, Chad L. J Clin Transl Sci Precision Medicine 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 more 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. CGI profiles can be derived from phenotypic screen readouts. These profiles are analogous to genetic interaction (GI) profiles, which represent sensitivity/resistance of gene knockouts to a second gene knockout rather than a drug. To computationally predict a drug’s genetic target, we leverage the property that a drug’s CGI profile will be similar to its target’s GI profile. RESULTS/ANTICIPATED RESULTS: Five proof-of-principle screens will be conducted with compounds that have existing genome-wide profiles and well-characterized MOA. I will generate CGI profiles for these five compounds and identify genes that are drug-sensitizers or drug-suppressors. I will then evaluate whether targeted library screens can recapitulate the CGIs found in genome-wide screens. Finally, I will develop a computational tool to integrate these CGI profiles with GI profiles (derived from another project) to predict gene-level and bioprocess-level drug targets. These predictions (from both targeted and genome-wide profiles) will be benchmarked against a drug-target and drug-bioprocess standard. DISCUSSION/SIGNIFICANCE OF FINDINGS: This work will develop a scalable, targeted chemical-genetic screen approach to discovering how putative therapeutics work. The targeted screen workflow provides a method for higher-throughput drug screening. The computational pipeline provides a powerful tool for exploring the MOA of uncharacterized drugs or repurposing FDA-approved drugs. Cambridge University Press 2021-03-30 /pmc/articles/PMC8827809/ http://dx.doi.org/10.1017/cts.2021.661 Text en © The Association for Clinical and Translational Science 2021 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Precision Medicine
Lin, Kevin
Billmann, Maximilian
Ward, Henry
Chang, Ya-Chu
Bielinsky, Anja-Katrin
Myers, Chad L.
12621 Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action
title 12621 Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action
title_full 12621 Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action
title_fullStr 12621 Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action
title_full_unstemmed 12621 Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action
title_short 12621 Targeted Chemical-Genetic Screen Platform for Identifying Drug Modes-of-Action
title_sort 12621 targeted chemical-genetic screen platform for identifying drug modes-of-action
topic Precision Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8827809/
http://dx.doi.org/10.1017/cts.2021.661
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