Systems Biology Approaches for Therapeutics Development Against COVID-19

Jaiswal, Shweta; Kumar, Mohit; Mandeep,; Sunita, Sunita; Singh, Yogendra; Shukla, Pratyoosh

doi:10.3389/fcimb.2020.560240

Cited by 14 publications

(9 citation statements)

References 221 publications

(193 reference statements)

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“…However, due to the complexity of COVID-19 symptomatology, it is important to characterize host response to SARS-CoV-2 infection in different cohorts from asymptomatic individuals to severe patients to better understand disease mechanisms and symptoms with possible medical complications at different levels, and the identification of potential diagnostic markers and drug targets (22)(23)(24)(25). Quantitative proteomics approaches alone or in combination with other omics technologies are key to achieve this goal (24)(25)(26)(27). To contribute in addressing this objective, herein we used a sequential window acquisition of all theoretical mass spectra (SWATH-MS) quantitative proteomics to characterize serum protein profiles in five cohorts of healthy (pre-pandemic sampling) and SARS-CoV-2-infected asymptomatic, recovered (hospital discharge), nonsevere (hospitalized), and severe [intensive care unit (ICU)] individuals.…”

Section: Introductionmentioning

confidence: 99%

Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology

et al. 2021

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The COVID-19 pandemic caused by SARS-CoV-2 challenges the understanding of factors affecting disease progression and severity. The identification of prognostic biomarkers and physiological processes associated with disease symptoms is relevant for the development of new diagnostic and therapeutic interventions to contribute to the control of this pandemic. To address this challenge, in this study, we used a quantitative proteomics together with multiple data analysis algorithms to characterize serum protein profiles in five cohorts from healthy to SARS-CoV-2-infected recovered (hospital discharge), nonsevere (hospitalized), and severe [at the intensive care unit (ICU)] cases with increasing systemic inflammation in comparison with healthy individuals sampled prior to the COVID-19 pandemic. The results showed significantly dysregulated proteins and associated biological processes and disorders associated to COVID-19. These results corroborated previous findings in COVID-19 studies and highlighted how the representation of dysregulated serum proteins and associated BPs increases with COVID-19 disease symptomatology from asymptomatic to severe cases. The analysis was then focused on novel disease processes and biomarkers that were correlated with disease symptomatology. To contribute to translational medicine, results corroborated the predictive value of selected immune-related biomarkers for disease recovery [Selenoprotein P (SELENOP) and Serum paraoxonase/arylesterase 1 (PON1)], severity [Carboxypeptidase B2 (CBP2)], and symptomatology [Pregnancy zone protein (PZP)] using protein-specific ELISA tests. Our results contributed to the characterization of SARS-CoV-2–host molecular interactions with potential contributions to the monitoring and control of this pandemic by using immune-related biomarkers associated with disease symptomatology.

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Section: Introductionmentioning

confidence: 99%

Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology

et al. 2021

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“…System biology plays a vital role in this global scenario to fight against COVID-19 ( Jaiswal et al, 2020 ). Previously we combined meta-analysis, gene expression omnibus (GEO) data and animal models results to identify ACE2 as an indicator of the susceptibility to SARS-CoV-2 infection ( Kong et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Integrative In Silico Investigation Reveals the Host-Virus Interactions in Repurposed Drugs Against SARS-CoV-2

Bai

Raha

et al. 2022

Front. Bioinform.

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The ongoing COVID-19 outbreak have posed a significant threat to public health worldwide. Recently Toll-like receptor (TLR) has been proposed to be the drug target of SARS-CoV-2 treatment, the specificity and efficacy of such treatments remain unknown. In the present study we performed the investigation of repurposed drugs via a framework comprising of Search Tool for Interacting Chemicals (STITCH), Kyoto Encyclopedia of Genes and Genomes (KEGG), molecular docking, and virus-host-drug interactome mapping. Chloroquine (CQ) and hydroxychloroquine (HCQ) were utilized as probes to explore the interaction network that is linked to SARS-CoV-2. 47 drug targets were shown to be overlapped with SARS-CoV-2 network and were enriched in TLR signaling pathway. Molecular docking analysis and molecular dynamics simulation determined the direct binding affinity of TLR9 to CQ and HCQ. Furthermore, we established SARS-CoV-2-human-drug protein interaction map and identified the axis of TLR9-ERC1-Nsp13 and TLR9-RIPK1-Nsp12. Therefore, the elucidation of the interactions of SARS-CoV-2 with TLR9 axis will not only provide pivotal insights into SARS-CoV-2 infection and pathogenesis but also improve the treatment against COVID-19.

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“…However, a strong reductionist approach usually fails when dealing with more complex situations (e.g., for the analysis of many aspects of the COVID-19 pandemic, such as predicting the modulators of inflammation in patients, adjusting proper treatment, or developing new therapeutic drugs, other approaches, such as system biology, may be more fruitful cf. Hajjo and Tropsha 2020;Jaiswal et al 2020;Jung et al 2021). Although geneticists have significantly changed their perspective in recent decades (e.g., they have implemented models of complex traits that no longer rely on classical genetic reductionism) and many critical arguments have been formulated against the naïve application of radical reductionist methodology in biology or medicine (Tauber and Sarkar 1992;Bock and Goode 2008;Greene and Loscalzo 2017;Lerner, 2015), the reductionist approach is still quite common.…”

Section: Introductionmentioning

confidence: 99%

Reductionist methodology and the ambiguity of the categories of race and ethnicity in biomedical research: an exploratory study of recent evidence

Żuradzki

2022

Med Health Care and Philos

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In this article, we analyse how researchers use the categories of race and ethnicity with reference to genetics and genomics. We show that there is still considerable conceptual “messiness” (despite the wide-ranging and popular debate on the subject) when it comes to the use of ethnoracial categories in genetics and genomics that among other things makes it difficult to properly compare and interpret research using ethnoracial categories, as well as draw conclusions from them. Finally, we briefly reconstruct some of the biases of reductionism to which geneticists (as well as other researchers referring to genetic methods and explanations) are particularly exposed to, and we analyse the problem in the context of the biologization of ethnoracial categories. Our work constitutes a novel, in-depth contribution to the debate about reporting race and ethnicity in biomedical and health research. First, we reconstruct the theoretical background assumptions about racial ontology which researchers implicitly presume in their studies with the aid of a sample of recent papers published in medical journals about COVID-19. Secondly, we use the typology of the biases of reductionism to the problem of biologization of ethnoracial categories with reference to genetics and genomics.

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Systems Biology Approaches for Therapeutics Development Against COVID-19

Cited by 14 publications

References 221 publications

Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology

Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology

Integrative In Silico Investigation Reveals the Host-Virus Interactions in Repurposed Drugs Against SARS-CoV-2

Reductionist methodology and the ambiguity of the categories of race and ethnicity in biomedical research: an exploratory study of recent evidence

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