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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2021
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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. |
format | Online Article Text |
id | pubmed-8827809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
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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