Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics

Liu, Danyang; Liu, Jiachen; Liang, Shuang; Meng, Xiang-He; Greenbaum, Jonathan; Xiao, Hong‐Mei; Tan, Lijun; Deng, Hong‐Wen

doi:10.3390/pharmaceutics13040545

Cited by 20 publications

(6 citation statements)

References 68 publications

(68 reference statements)

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“…It guards against COVID-19 patients’ neutrophil extracellular traps (Strich et al 2021 ). Thirty synergistic drug combinations, including Tretinoin and Fostamatinib, were suggested by Yang Liu et al using a complementary exposure model to treat COVID-19 (Liu et al 2021 ). Hypercoagulability may be life-threatening in patients with severe COVID-19.…”

Section: Discussionmentioning

confidence: 99%

Deciphering molecular mechanisms of SARS-CoV-2 pathogenesis and drug repurposing through GRN motifs: a comprehensive systems biology study

et al. 2023

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The world has recently been plagued by a new coronavirus infection called SARS-CoV-2. This virus may lead to severe acute respiratory syndrome followed by multiple organ failure. SARS-CoV-2 has approximately 80–90% genetic similarity to SARS-CoV. Given the limited omics data available for host response to the viruses (more limited data for SARS-CoV-2), we attempted to unveil the crucial molecular mechanisms underlying the SARS-CoV-2 pathogenesis by comparing its regulatory network motifs with SARS-CoV. We also attempted to identify the non-shared crucial molecules and their functions to predict the specific mechanisms for each infection and the processes responsible for their different manifestations. Deciphering the crucial shared and non-shared mechanisms at the molecular level and signaling pathways underlying both diseases may help shed light on their pathogenesis and pave the way for other new drug repurposing against COVID-19. We constructed the GRNs for host response to SARS-CoV and SARS-CoV-2 pathogens (in vitro) and identified the significant 3-node regulatory motifs by analyzing them topologically and functionally. We attempted to identify the shared and non-shared regulatory elements and signaling pathways between their host responses. Interestingly, our findings indicated that NFKB1 , JUN , STAT1 , FOS , KLF4 , and EGR1 were the critical shared TFs between motif-related subnetworks in both SARS and COVID-1, which are considered genes with specific functions in the immune response. Enrichment analysis revealed that the NOD-like receptor signaling, TNF signaling, and influenza A pathway were among the first significant pathways shared between SARS and COVID-19 up-regulated DEGs networks, and the term “metabolic pathways” (hsa01100) among the down-regulated DEGs networks. WEE1, PMAIP1, and TSC22D2 were identified as the top three hubs specific to SARS. However, MYPN , SPRY4 , and APOL6 were the tops specific to COVID-19 in vitro. The term “Complement and coagulation cascades” pathway was identified as the first top non-shared pathway for COVID-19 and the MAPK signaling pathway for SARS. We used the identified crucial DEGs to construct a drug–gene interaction network to propose some drug candidates. Zinc chloride, Fostamatinib, Copper, Tirofiban, Tretinoin, and Levocarnitine were the six drugs with higher scores in our drug–gene network analysis. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-023-03518-x.

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Section: Discussionmentioning

confidence: 99%

Deciphering molecular mechanisms of SARS-CoV-2 pathogenesis and drug repurposing through GRN motifs: a comprehensive systems biology study

et al. 2023

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“…Chushak and Stone [ 191 ] employed knowledge-based methodologies to build potential medicine combinations and verified synergies for the SARS-COV2. Liu et al [ 192 ] established a biological network proximity metric to evaluate the synergy between anti-cancer drugs and hypertension. Synergy has been predicted using machine learning techniques, particularly DL approaches [ 193 , 194 ].…”

Section: Synergistic Medicine Combinations For Covid-19 Treatmentmentioning

confidence: 99%

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations

Rafique,

Rehman,

Afghan

et al. 2023

Computers in Biology and Medicine

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“…Besides, network pharmacology is an effective systemic approach to guide in drug repurposing [19]. Drug repurposing for COVID-19 treatment on orchestrated network pharmacology can also accelerate the discovery of significant drugs against COVID-19 [20]. In this research, network pharmacology was utilized to investigate the most significant potential antihistamine(s) against COVID-19.…”

Section: Introductionmentioning

confidence: 99%

Network Pharmacology Study to Elucidate the Key Targets of Underlying Antihistamines against COVID-19

Adnan

Cho

2022

CIMB

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Antihistamines have potent efficacy to alleviate COVID-19 (Coronavirus disease 2019) symptoms such as anti-inflammation and as a pain reliever. However, the pharmacological mechanism(s), key target(s), and drug(s) are not documented well against COVID-19. Thus, we investigated to decipher the most significant components and how its research methodology was utilized by network pharmacology. The list of 32 common antihistamines on the market were retrieved via drug browsing databases. The targets associated with the selected antihistamines and the targets that responded to COVID-19 infection were identified by the Similarity Ensemble Approach (SEA), SwissTargetPrediction (STP), and PubChem, respectively. We described bubble charts, the Pathways-Targets-Antihistamines (PTA) network, and the protein–protein interaction (PPI) network on the RPackage via STRING database. Furthermore, we utilized the AutoDock Tools software to perform molecular docking tests (MDT) on the key targets and drugs to evaluate the network pharmacological perspective. The final 15 targets were identified as core targets, indicating that Neuroactive ligand–receptor interaction might be the hub-signaling pathway of antihistamines on COVID-19 via bubble chart. The PTA network was constructed by the RPackage, which identified 7 pathways, 11 targets, and 30 drugs. In addition, GRIN2B, a key target, was identified via topological analysis of the PPI network. Finally, we observed that the GRIN2B-Loratidine complex was the most stable docking score with −7.3 kcal/mol through molecular docking test. Our results showed that Loratadine might exert as an antagonist on GRIN2B via the neuroactive ligand–receptor interaction pathway. To sum up, we elucidated the most potential antihistamine, a key target, and a key pharmacological pathway as alleviating components against COVID-19, supporting scientific evidence for further research.

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Drug Repurposing for COVID-19 Treatment by Integrating Network Pharmacology and Transcriptomics

Cited by 20 publications

References 68 publications

Deciphering molecular mechanisms of SARS-CoV-2 pathogenesis and drug repurposing through GRN motifs: a comprehensive systems biology study

Deciphering molecular mechanisms of SARS-CoV-2 pathogenesis and drug repurposing through GRN motifs: a comprehensive systems biology study

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations

Network Pharmacology Study to Elucidate the Key Targets of Underlying Antihistamines against COVID-19

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