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Recent:   

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Niarakis et al., Frontiers in Immunology, doi:10.3389/fimmu.2023.1282859
Feb 2024  
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In silico study integrating multi-omics data analysis, computational modelling, text mining, and AI to suggest targeted COVID-19 therapies. Authors identified 54 potential targets using omic data analysis of SARS-CoV-2 infected cell lines and patient samples. Computational modelling highlighted interferons, renin-angiotensin system, and NLRP3 inflammasome as key antiviral and inflammatory pathways. Text mining retrieved 228 unique drugs/chemicals plus miRNAs targeting 46 of the identified nodes. Pharmacogenomic analysis revealed population differences in response for targets like AGTR1, IKBKE, CASP7, and EGFR.
Niarakis et al., 13 Feb 2024, peer-reviewed, 78 authors. Contact: anna.niarakis@inria.fr.
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Abstract: TYPE Original Research PUBLISHED 13 February 2024 DOI 10.3389/fimmu.2023.1282859 OPEN ACCESS EDITED BY Issam El Naqa, University of Michigan, United States REVIEWED BY Stefano Casarin, Houston Methodist Research Institute, United States Marcus Scotti, Federal University of Paraı´ba, Brazil *CORRESPONDENCE Anna Niarakis anna.niarakis@inria.fr † PRESENT ADDRESS Anna Niarakis, Centre de Biologie Integrative, Pole de Biologie Computationnelle des Systèmes, Univ. Toulouse III - Paul Sabatier, France SPECIALTY SECTION RECEIVED 24 August 2023 ACCEPTED 22 December 2023 PUBLISHED 13 February 2024 CITATION Niarakis A, Ostaszewski M, Mazein A, Kuperstein I, Kutmon M, Gillespie ME, Funahashi A, Acencio ML, Hemedan A, Aichem M, Klein K, Czauderna T, Burtscher F, Yamada TG, Hiki Y, Hiroi NF, Hu F, Pham N, Ehrhart F, Willighagen EL, Valdeolivas A, Dugourd A, Messina F, Esteban-Medina M, Peña-Chilet M, Rian K, Soliman S, Aghamiri SS, Puniya BL, Naldi A, Helikar T, Singh V, Fernández MF, Bermudez V, Tsirvouli E, Montagud A, Noël V, Ponce-de-Leon M, Maier D, Bauch A, Gyori BM, Bachman JA, Luna A, Piñero J, Furlong LI, Balaur I, Rougny A, Jarosz Y, Overall RW, Phair R, Perfetto L, Matthews L, Rex DAB, Orlic-Milacic M, Gomez LCM, De Meulder B, Ravel JM, Jassal B, Satagopam V, Wu G, Golebiewski M, Gawron P, Calzone L, Beckmann JS, Evelo CT, D’Eustachio P, Schreiber F, Saez-Rodriguez J, Dopazo J, Kuiper M, Valencia A, Wolkenhauer O, Kitano H, Barillot E, Auffray C, Balling R, Schneider R and the COVID-19 Disease Map Community (2024) Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches. Front. Immunol. 14:1282859. doi: 10.3389/fimmu.2023.1282859 Frontiers in Immunology Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches Anna Niarakis 1,2*†, Marek Ostaszewski 3, Alexander Mazein 3, Inna Kuperstein 4,5,6, Martina Kutmon 7, Marc E. Gillespie 8,9, Akira Funahashi 10, Marcio Luis Acencio 3, Ahmed Hemedan 3, Michael Aichem 11, Karsten Klein 11, Tobias Czauderna 12, Felicia Burtscher 3, Takahiro G. Yamada 10, Yusuke Hiki 13, Noriko F. Hiroi 14,15, Finterly Hu 7,16, Nhung Pham 7,16, Friederike Ehrhart 16, Egon L. Willighagen 16, Alberto Valdeolivas 17, Aurelien Dugourd 17, Francesco Messina 18, Marina Esteban-Medina 19,20, Maria Peña-Chilet 19,20,21, Kinza Rian 19, Sylvain Soliman 2, Sara Sadat Aghamiri 22, Bhanwar Lal Puniya 22, Aurélien Naldi 2, Tomáš Helikar 22, Vidisha Singh 1, Marco Fariñas Fernández 23, Viviam Bermudez 23, Eirini Tsirvouli 23, Arnau Montagud 24, Vincent Noël 4,5,6, Miguel Ponce-de-Leon 24, Dieter Maier 25, Angela Bauch 25, Benjamin M. Gyori 26, John A. Bachman 26, Augustin Luna 27,28, Janet Piñero 29,30, Laura I. Furlong 29,30, Irina Balaur 3, Adrien Rougny 31,32, Yohan Jarosz 3, Rupert W. Overall 33, Robert Phair 34, Livia Perfetto 35, Lisa Matthews 36, Devasahayam Arokia Balaya Rex 37, Marija Orlic-Milacic 8, Luis Cristobal Monraz Gomez 4,5,6, Bertrand De Meulder 38, Jean Marie Ravel 4,5,6, Bijay Jassal 8, Venkata Satagopam 3,39, Guanming Wu 40, Martin Golebiewski 41, Piotr Gawron 3, Laurence Calzone 4,5,6, Jacques S. Beckmann 42, Chris T. Evelo 16, Peter D’Eustachio 36, Falk Schreiber 11,43, Julio Saez-Rodriguez 17, Joaquin Dopazo 19,20,21,44, Martin Kuiper 23, Alfonso Valencia 24,45, Olaf Wolkenhauer 46,47, Hiroaki Kitano 48, Emmanuel Barillot 4,5,6, Charles Auffray 38, Rudi Balling 49, Reinhard Schneider 3 and the COVID-19..
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' '</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Extensive community ' 'work allowed an impressive step forward in building interfaces between Systems Biology tools ' 'and platforms. Our framework can link biomolecules from omics data analysis and computational ' 'modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug ' 'repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals ' 'and microRNAs that could target the identified key ' 'factors.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Results ' 'revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for ' 'their mode of action, and drugs already in clinical trials for treating other diseases, never ' 'tested against COVID-19. ' '</jats:p></jats:sec><jats:sec><jats:title>Discussion</jats:title><jats:p>The key advance is ' 'that the proposed framework is versatile and expandable, offering a significant upgrade in ' 'the arsenal for virus-host interactions and other complex pathologies.</jats:p></jats:sec>', 'DOI': '10.3389/fimmu.2023.1282859', 'type': 'journal-article', 'created': {'date-parts': [[2024, 2, 13]], 'date-time': '2024-02-13T04:34:21Z', 'timestamp': 1707798861000}, 'update-policy': 'http://dx.doi.org/10.3389/crossmark-policy', 'source': 'Crossref', 'is-referenced-by-count': 0, 'title': 'Drug-target identification in COVID-19 disease mechanisms using computational systems biology ' 'approaches', 'prefix': '10.3389', 'volume': '14', 'author': [ {'given': 'Anna', 'family': 'Niarakis', 'sequence': 'first', 'affiliation': []}, {'given': 'Marek', 'family': 'Ostaszewski', 'sequence': 'additional', 'affiliation': []}, {'given': 'Alexander', 'family': 'Mazein', 'sequence': 'additional', 'affiliation': []}, 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