In silico Drug Screening Approach Using L1000-Based Connectivity Map and Its Application to COVID-19
Conventional drug screening methods search for a limited number of small molecules that directly interact with the target protein. This process can be slow, cumbersome and has driven the need for developing new drug screening approaches to counter rapidly emerging diseases such as COVID-19. We propo...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-03-01
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| Series: | Frontiers in Cardiovascular Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcvm.2022.842641/full |
| _version_ | 1818315064721014784 |
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| author | Takaharu Asano Sarvesh Chelvanambi Julius L. Decano Mary C. Whelan Elena Aikawa Elena Aikawa Elena Aikawa Masanori Aikawa Masanori Aikawa Masanori Aikawa Masanori Aikawa |
| author_facet | Takaharu Asano Sarvesh Chelvanambi Julius L. Decano Mary C. Whelan Elena Aikawa Elena Aikawa Elena Aikawa Masanori Aikawa Masanori Aikawa Masanori Aikawa Masanori Aikawa |
| author_sort | Takaharu Asano |
| collection | DOAJ |
| description | Conventional drug screening methods search for a limited number of small molecules that directly interact with the target protein. This process can be slow, cumbersome and has driven the need for developing new drug screening approaches to counter rapidly emerging diseases such as COVID-19. We propose a pipeline for drug repurposing combining in silico drug candidate identification followed by in vitro characterization of these candidates. We first identified a gene target of interest, the entry receptor for the SARS-CoV-2 virus, angiotensin converting enzyme 2 (ACE2). Next, we employed a gene expression profile database, L1000-based Connectivity Map to query gene expression patterns in lung epithelial cells, which act as the primary site of SARS-CoV-2 infection. Using gene expression profiles from 5 different lung epithelial cell lines, we computationally identified 17 small molecules that were predicted to decrease ACE2 expression. We further performed a streamlined validation in the normal human epithelial cell line BEAS-2B to demonstrate that these compounds can indeed decrease ACE2 surface expression and to profile cell health and viability upon drug treatment. This proposed pipeline combining in silico drug compound identification and in vitro expression and viability characterization in relevant cell types can aid in the repurposing of FDA-approved drugs to combat rapidly emerging diseases. |
| first_indexed | 2024-12-13T08:59:36Z |
| format | Article |
| id | doaj.art-c21bb98f16154ccb83ea0e2e2490e710 |
| institution | Directory Open Access Journal |
| issn | 2297-055X |
| language | English |
| last_indexed | 2024-12-13T08:59:36Z |
| publishDate | 2022-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cardiovascular Medicine |
| spelling | doaj.art-c21bb98f16154ccb83ea0e2e2490e7102022-12-21T23:53:12ZengFrontiers Media S.A.Frontiers in Cardiovascular Medicine2297-055X2022-03-01910.3389/fcvm.2022.842641842641In silico Drug Screening Approach Using L1000-Based Connectivity Map and Its Application to COVID-19Takaharu Asano0Sarvesh Chelvanambi1Julius L. Decano2Mary C. Whelan3Elena Aikawa4Elena Aikawa5Elena Aikawa6Masanori Aikawa7Masanori Aikawa8Masanori Aikawa9Masanori Aikawa10Center for Interdisciplinary Cardiovascular Sciences, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesCenter for Interdisciplinary Cardiovascular Sciences, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesCenter for Interdisciplinary Cardiovascular Sciences, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesCenter for Interdisciplinary Cardiovascular Sciences, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesCenter for Interdisciplinary Cardiovascular Sciences, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesCenter for Excellence in Vascular Biology, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesDepartment of Human Pathology, I.M. Sechenov First Moscow State Medical University of the Ministry of Health, Moscow, RussiaCenter for Interdisciplinary Cardiovascular Sciences, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesCenter for Excellence in Vascular Biology, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesDepartment of Human Pathology, I.M. Sechenov First Moscow State Medical University of the Ministry of Health, Moscow, RussiaChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United StatesConventional drug screening methods search for a limited number of small molecules that directly interact with the target protein. This process can be slow, cumbersome and has driven the need for developing new drug screening approaches to counter rapidly emerging diseases such as COVID-19. We propose a pipeline for drug repurposing combining in silico drug candidate identification followed by in vitro characterization of these candidates. We first identified a gene target of interest, the entry receptor for the SARS-CoV-2 virus, angiotensin converting enzyme 2 (ACE2). Next, we employed a gene expression profile database, L1000-based Connectivity Map to query gene expression patterns in lung epithelial cells, which act as the primary site of SARS-CoV-2 infection. Using gene expression profiles from 5 different lung epithelial cell lines, we computationally identified 17 small molecules that were predicted to decrease ACE2 expression. We further performed a streamlined validation in the normal human epithelial cell line BEAS-2B to demonstrate that these compounds can indeed decrease ACE2 surface expression and to profile cell health and viability upon drug treatment. This proposed pipeline combining in silico drug compound identification and in vitro expression and viability characterization in relevant cell types can aid in the repurposing of FDA-approved drugs to combat rapidly emerging diseases.https://www.frontiersin.org/articles/10.3389/fcvm.2022.842641/fullL1000connectivity map (CMap)ACE2COVID-19drug repurposinglung epithelial cell |
| spellingShingle | Takaharu Asano Sarvesh Chelvanambi Julius L. Decano Mary C. Whelan Elena Aikawa Elena Aikawa Elena Aikawa Masanori Aikawa Masanori Aikawa Masanori Aikawa Masanori Aikawa In silico Drug Screening Approach Using L1000-Based Connectivity Map and Its Application to COVID-19 Frontiers in Cardiovascular Medicine L1000 connectivity map (CMap) ACE2 COVID-19 drug repurposing lung epithelial cell |
| title | In silico Drug Screening Approach Using L1000-Based Connectivity Map and Its Application to COVID-19 |
| title_full | In silico Drug Screening Approach Using L1000-Based Connectivity Map and Its Application to COVID-19 |
| title_fullStr | In silico Drug Screening Approach Using L1000-Based Connectivity Map and Its Application to COVID-19 |
| title_full_unstemmed | In silico Drug Screening Approach Using L1000-Based Connectivity Map and Its Application to COVID-19 |
| title_short | In silico Drug Screening Approach Using L1000-Based Connectivity Map and Its Application to COVID-19 |
| title_sort | in silico drug screening approach using l1000 based connectivity map and its application to covid 19 |
| topic | L1000 connectivity map (CMap) ACE2 COVID-19 drug repurposing lung epithelial cell |
| url | https://www.frontiersin.org/articles/10.3389/fcvm.2022.842641/full |
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