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Advances in the computational landscape for repurposed drugs against COVID-19.

ABSTRACT: The COVID-19 pandemic has caused millions of deaths and massive societal distress worldwide. Therapeutic solutions are urgently needed but de novo drug development remains a lengthy process. One promising alternative is computational drug repurposing, which enables the prioritization of existing compounds through fast in silico analyses. Recent efforts based on molecular docking, machine learning, and network analysis have produced actionable predictions. Some predicted drugs, targeting viral proteins and pathological host pathways are undergoing clinical trials. Here, we review this work, highlight drugs with high predicted efficacy and classify their mechanisms of action. We discuss the strengths and limitations of the published methodologies and outline possible future directions. Finally, we curate a list of COVID-19 data portals and other repositories that could be used to accelerate future research.

SUBMITTER: Aronskyy I

PROVIDER: S-EPMC8323501 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Advances in the computational landscape for repurposed drugs against COVID-19.

Aronskyy Illya I Masoudi-Sobhanzadeh Yosef Y Cappuccio Antonio A Zaslavsky Elena E

Drug discovery today 20210730 12

The COVID-19 pandemic has caused millions of deaths and massive societal distress worldwide. Therapeutic solutions are urgently needed, but de novo drug development remains a lengthy process. One promising alternative is computational drug repurposing, which enables the prioritization of existing compounds through fast in silico analyses. Recent efforts based on molecular docking, machine learning, and network analysis have produced actionable predictions. Some predicted drugs, targeting viral p ...[more]

PMID: 34339864

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Project description:The rapid breakout of the coronavirus disease of 2019 (COVID-19) has been declared pandemic with serious global concern due to high morbidity and mortality. As we enter the phase beyond limitations there is an urgent need for explicit treatment against COVID-19. To face this immediate global challenge, drug development from scratch is a lengthy process and unrealistic to conquer this battle. Drug repurposing is an emerging and practical approach where existing drugs, safe for humans, are redeployed to fight this harder to treat disease. A number of multi clinical studies have repurposed combined cocktail (remdesivir + chloroquine and favipiravir + chloroquine) to be effective against COVID-19. However, the exact mechanistic aspect has not yet been revealed. In the present study, we have tried to decipher the mechanistic aspects of existing medicines at the viral entry and replication stage via the structural viroinformatics approach. Here we implied the molecular docking and dynamic simulations with emphasis on the unique structural properties of host receptor angiotensin-converting enzyme 2 (ACE2), SARS-CoV2 spike protein and RNA dependent RNA polymerase enzyme (RdRp) of the SARS-CoV2. Deep structural analysis of target molecules exposed key binding residues and structural twists involved in binding with important pharmacophore features of existing drugs [(7-chloro-N-[5-(diethylamino)pentan-2-yl]quinolin-4-amine (chloroquine),N-[[4-(4-methylpiperazin-1-yl)phenyl]methyl]-1,2-oxazole-5-carboxamide N-[[4-(4-methylpiperazin-1-yl)phenyl]methyl]-1,2-oxazole-5-carboxamide) (SSAA09E2), 2-ethylbutyl (2S)-2-{[(S)-{[(2R,3S,4R,5R)-5-{4-aminopyrrolo[2,1-f][1,2,4]triazin-7-yl}-5-cyano-3 (remdesivir) and 6-Fluor-3-oxo-3,4-dihydro-2-pyrazincarboxamid (favipiravir)]. It is evident from this structural informatics study that combo of chloroquine + SSAA09E2 with remdesivir or favipiravir could significantly restrain the virus at the entry and replication stage. Thus, drug repurposition is an attractive approach with reduced time and cost to treat COVID-19, we don't have enough time as the whole world is lockdown and we are in urgent need of an obvious therapeutics' measures.

Project description:Background: Coronavirus disease (COVID-19) is an infectious disease discovered in 2019 and currently in outbreak across the world. Lung injury with severe respiratory failure is the leading cause of death in COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there still lacks efficient treatment for COVID-19 induced lung injury and acute respiratory failure. Methods: Inhibition of angiotensin-converting enzyme 2 (ACE2) caused by the spike protein of SARS-CoV-2 is the most plausible mechanism of lung injury in COVID-19. We performed drug repositioning analysis to identify drug candidates that reverse gene expression pattern in L1000 lung cell line HCC515 treated with ACE2 inhibitor. We confirmed these drug candidates by similar bioinformatics analysis using lung tissues from patients deceased from COVID-19. We further investigated deregulated genes and pathways related to lung injury, as well as the gene-pathway-drug candidate relationships. Results: We propose two candidate drugs, COL-3 (a chemically modified tetracycline) and CGP-60474 (a cyclin-dependent kinase inhibitor), for treating lung injuries in COVID-19. Further bioinformatics analysis shows that 12 significantly enriched pathways (P-value <0.05) overlap between HCC515 cells treated with ACE2 inhibitor and human COVID-19 patient lung tissues. These include signaling pathways known to be associated with lung injury such as TNF signaling, MAPK signaling and chemokine signaling pathways. All 12 pathways are targeted in COL-3 treated HCC515 cells, in which genes such as RHOA, RAC2, FAS, CDC42 have reduced expression. CGP-60474 shares 11 of 12 pathways with COL-3 and common target genes such as RHOA. It also uniquely targets other genes related to lung injury, such as CALR and MMP14. Conclusions: This study shows that ACE2 inhibition is likely part of the mechanisms leading to lung injury in COVID-19, and that compounds such as COL-3 and CGP-60474 have potential as repurposed drugs for its treatment.

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Advances in the computational landscape for repurposed drugs against COVID-19.

Publications

Advances in the computational landscape for repurposed drugs against COVID-19.

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