MicroRNAs; Pharmaceutical Preparations; Small Molecule Libraries; Humans; Pandemics; COVID-19 Drug Treatment; COVID-19; Cheminformatics; Clinical trials; Drug repurposing; Machine learning; Systems biology
Abstract :
[en] The COVID-19 pandemic created an unprecedented global healthcare emergency prompting the exploration of new therapeutic avenues, including drug repurposing. A large number of ongoing studies revealed pervasive issues in clinical research, such as the lack of accessible and organised data. Moreover, current shortcomings in clinical studies highlighted the need for a multi-faceted approach to tackle this health crisis. Thus, we set out to explore and develop new strategies for drug repositioning by employing computational pharmacology, data mining, systems biology, and computational chemistry to advance shared efforts in identifying key targets, affected networks, and potential pharmaceutical intervention options. Our study revealed that formulating pharmacological strategies should rely on both therapeutic targets and their networks. We showed how data mining can reveal regulatory patterns, capture novel targets, alert about side-effects, and help identify new therapeutic avenues. We also highlighted the importance of the miRNA regulatory layer and how this information could be used to monitor disease progression or devise treatment strategies. Importantly, our work bridged the interactome with the chemical compound space to better understand the complex landscape of COVID-19 drugs. Machine and deep learning allowed us to showcase limitations in current chemical libraries for COVID-19 suggesting that both in silico and experimental analyses should be combined to retrieve therapeutically valuable compounds. Based on the gathered data, we strongly advocate for taking this opportunity to establish robust practices for treating today's and future infectious diseases by preparing solid analytical frameworks.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Kanapeckaitė, Austė; AK Consulting, Laisvės g. 7, LT 12007 Vilnius, Lithuania. Electronic address:
Mažeikienė, Asta; Department of Physiology, Biochemistry, Microbiology and Laboratory Medicine,
Geris, Liesbet ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > Génie biomécanique
Burokienė, Neringa; Clinics of Internal Diseases, Family Medicine and Oncology, Institute of Clinical
Cottrell, Graeme S; University of Reading, School of Pharmacy, Hopkins Building, Reading RG6 6UB,
Widera, Darius; University of Reading, School of Pharmacy, Hopkins Building, Reading RG6 6UB,
Language :
English
Title :
Computational pharmacology: New avenues for COVID-19 therapeutics search and better preparedness for future pandemic crises.
Chauhan, S., Comprehensive review of coronavirus disease 2019 (COVID-19). Biom. J. 43:4 (2020 Aug 1), 334–340 Available from: https://pubmed.ncbi.nlm.nih.gov/32788071/.
Serafin, M.B., Bottega, A., Foletto, V.S., da Rosa, T.F., Hörner, A., Hörner, R., Drug repositioning is an alternative for the treatment of coronavirus COVID-19. Int. J. Antimicrob. Agents, 55(6), 2020 Jun 1, 105969 Available from: /pmc/articles/PMC7194941/.
Cascella, M., Rajnik, M., Cuomo, A., Dulebohn, S.C., Di Napoli, R., Features, evaluation, and treatment of coronavirus (COVID-19). StatPearls., 2021 Sep 2 Available from: https://www.ncbi.nlm.nih.gov/books/NBK554776/.
Gebhard, C., Regitz-Zagrosek, V., Neuhauser, H.K., Morgan, R., Klein, S.L., Impact of sex and gender on COVID-19 outcomes in Europe. Biol. Sex Differ., 11(1), 2020 May 25 Available from: https://pubmed.ncbi.nlm.nih.gov/32450906/.
Akinbolade, S., Coughlan, Diarmuid, Fairbairn, R., Mcconkey, G., Powell, H., Ogunbayo, D., et al. Combination therapies for COVID-19: An overview of the clinical trials landscape. Br. J. Clin. Pharmacol. 88(4) (2021 Oct 17), 1590–1597 Available from: https://onlinelibrary.wiley.com/doi/full/10.1111/bcp.15089.
Ng, Y.L., Salim, C.K., Chu, J.J.H., Drug repurposing for COVID-19: Approaches, challenges and promising candidates. Pharmacol. Ther., 228, 2021 Dec 1, 107930 Available from: /pmc/articles/PMC8220862/.
Jarada, T.N., Rokne, J.G., Alhajj, R., A review of computational drug repositioning: Strategies, approaches, opportunities, challenges, and directions. J. Chem. Thermodyn. 12:1 (2020 Jul 22), 1–23 Available from: https://jcheminf.biomedcentral.com/articles/10.1186/s13321-020-00450-7.
Ledford, H., Dozens of coronavirus drugs are in development - what happens next?. Nature. 581:7808 (2020 May 1), 247–248.
Pushpakom, S., Iorio, F., Eyers, P.A., Escott, K.J., Hopper, S., Wells, A., et al. Drug repurposing: progress, challenges and recommendations. Nat. Rev. Drug Discov. 18:1 (2018 Oct 12), 41–58 Available from: https://www.nature.com/articles/nrd.2018.168.
Chakraborty, C., Sharma, A.R., Bhattacharya, M., Agoramoorthy, G., Lee, S.-S., The drug repurposing for COVID-19 clinical trials provide very effective therapeutic combinations: lessons learned from major clinical studies. Front. Pharmacol., 2021 Nov 18, 12 Available from: /pmc/articles/PMC8636940/.
Choudhury, C., Fragment tailoring strategy to design novel chemical entities as potential binders of novel corona virus main protease. J. Biomol. Struct. Dyn., 1, 2020 Available from: /pmc/articles/PMC7284137/.
Yu, R., Chen, L., Lan, R., Shen, R., Li, P., Computational screening of antagonists against the SARS-CoV-2 (COVID-19) coronavirus by molecular docking. Int. J. Antimicrob. Agents, 56(2), 2020 Aug 1, 106012.
Bharti, R., Shukla, S.K., Molecules against Covid-19: An in silico approach for drug development. J. Electron. Sci. Technol., 19(1), 2021 Mar 1, 100095.
Tsou, L.K., Yeh, S.H., Ueng, S.H., Chang, C.P., Song, J.S., Wu, M.H., et al. Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery. Sci. Report. 10:1 (2020 Oct 8), 1–11 Available from: https://www.nature.com/articles/s41598-020-73681-1.
Gligorijević, V., Pržulj, N., Methods for biological data integration: perspectives and challenges. J. R. Soc. Interface, 12(112), 2015 Nov 6, 10.1098/rsif.2015.0571.
McCreary, E.K., Meyer, N.J., COVID-19 controversies: the tocilizumab chapter. BMJ., 2021 Jan 27, 372 Available from: https://pubmed.ncbi.nlm.nih.gov/33504502/.
Gupta, A., Malviya, A., Chloroquine and hydroxychloroquine for COVID-19: time to close the chapter. Postgrad. Med. J. 97:1152 (2021 Oct 1), 676–677 Available from: https://pubmed.ncbi.nlm.nih.gov/32788309/.
Gordon, D.E., Jang, G.M., Bouhaddou, M., Xu, J., Obernier, K., White, K.M., et al. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nat. 583:7816 (2020 Apr 30), 459–468 Available from: https://www.nature.com/articles/s41586-020-2286-9.
Lavecchia, A., Cerchia, C., In silico methods to address polypharmacology: current status, applications and future perspectives. Drug Discov. Today Elsevier Ltd. 21 (2016), 288–298.
March-Vila, E., Pinzi, L., Sturm, N., Tinivella, A., Engkvist, O., Chen, H., et al. On the integration of in silico drug design methods for drug repurposing. Front. Pharmacol., 8(MAY), 2017 May 23, 298 Available from: www.frontiersin.org.
Rodgers, F., Pepperrell, T., Keestra, S., Pilkington, V., Missing clinical trial data: the evidence gap in primary data for potential COVID-19 drugs. Trials., 22(1), 2021 Dec 1 Available from: https://pubmed.ncbi.nlm.nih.gov/33451350/.
Yildirim, M.A., Il, Goh K., Cusick, M.E., Barabási, A.L., Vidal, M., Drug-target network. Nat. Biotechnol. 25:10 (2007), 1119–1126.
Hendry, B.M., Stafford, N., Arnold, A.D., Sangwaiya, A., Manglam, V., Rosen, S.D., et al. Hypothesis: pentoxifylline is a potential cytokine modulator therapeutic in COVID-19 patients. Pharmacol. Res. Perspect., 8(4), 2020 Aug 1;8(4). Available from: /pmc/articles/PMC7383088/ https://bpspubs.onlinelibrary.wiley.com/doi/10.1002/prp2.631.
Kanapeckaitė, A., Burokienė, N., Insights into therapeutic targets and biomarkers using integrated multi-’omics’ approaches for dilated and ischemic cardiomyopathies. Integr. Biol. (Camb). 13:5 (2021 May 1), 121–137 Available from: https://pubmed.ncbi.nlm.nih.gov/33969404/.
Zhou, Y., Wang, F., Tang, J., Nussinov, R., Cheng, F., Artificial intelligence in COVID-19 drug repurposing. Lancet Digit Heal. 2:12 (2020 Dec 1), e667–e676 Available from: https://pubmed.ncbi.nlm.nih.gov/32984792/.
Malik, M.A., Wani, M.Y., Hashmi, A.A., Combination therapy: Current status and future perspectives. Combination Therapy Against Multidrug Resistance, 2020, Elsevier Inc., 1–38, 10.1016/B978-0-12-820576-1.00001-1.
Flockhart, D., Bies, R.R., Gastonguay, M.R., Schwartz, S.L., Big Data: Challenges and opportunities for clinical pharmacology. Br. J. Clin. Pharmacol. Blackwell Publish. Ltd 81 (2016), 804–806.
Farr, R.J., Rootes, C.L., Rowntree, L.C., Nguyen, T.H.O., Hensen, L., Kedzierski, L., et al. Altered microRNA expression in COVID-19 patients enables identification of SARS-CoV-2 infection. PLoS Pathog., 17(7), 2021 Jul 1, e1009759 Available from: https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1009759.
Fani, M., Zandi, M., Ebrahimi, S., Soltani, S., Abbasi, S., The role of miRNAs in COVID-19 disease. Futur. Virol. 16:4 (2021 Apr 1), 301–306 Available from: /pmc/articles/PMC7989380/.
Hanna, J., Hossain, G.S., Kocerha, J., The potential for microRNA therapeutics and clinical research. Front. Genet., 10(MAY), 2019, 478.
Bofill-De Ros, X., Gu, S., Guidelines for the optimal design of miRNA-based shRNAs. Methods. 103 (2016 Jul 1), 157–166.
Schneider, H.C., Klabunde, T., Understanding drugs and diseases by systems biology?. Bioorg. Med. Chem. Lett. 23:5 (2013 Mar 1), 1168–1176.
Brogi, S., Ramalho, T.C., Kuca, K., Medina-Franco, J.L., Valko, M., Editorial: in silico methods for drug design and discovery. Front. Chem., 8, 2020 Aug 7, 612 Available from: http://faerun.gdb.tools.
Du, J., Guo, J., Kang, D., Li, Z., Wang, G., Wu, J., et al. New techniques and strategies in drug discovery. Chin. Chem. Lett. 31:7 (2020 Jul 1), 1695–1708.
Downloads - - Diamond Light Source, Available from: https://www.diamond.ac.uk/covid-19/for-scientists/Main-protease-structure-and-XChem/Downloads.html, 2022 Jan 11.
Ekins, S., Mestres, J., Testa, B., In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling. Br. J. Pharmacol., 152(1), 2007 Sep, 9 Available from: /pmc/articles/PMC1978274/.
Abi Hussein, H., Geneix, C., Petitjean, M., Borrel, A., Flatters, D., Camproux, A.C., Global vision of druggability issues: applications and perspectives. Drug Discov. Today Elsevier Ltd. 22 (2017), 404–415.
Koscielny, G., An, P., Carvalho-Silva, D., Cham, J.A., Fumis, L., Gasparyan, R., et al. Open targets: a platform for therapeutic target identification and validation. Nucleic Acids Res. 45:D1 (2017 Jan 1), D985–D994 Available from: https://www.
Home - Open Targets, Available from: https://www.opentargets.org/, 2020 Dec 7.
PubChem, Available from: https://pubchem.ncbi.nlm.nih.gov/, 2020 Dec 16.
PubChem COVID-19 Clinical Trials. [2021 Nov 1]. Available from: https://pubchem.ncbi.nlm.nih.gov/#tab=compound&query=covid-19 clinicaltrials.
STITCH: Chemical Association Networks, Available from: http://stitch.embl.de/, 2020 Dec 7.
Szklarczyk, D., Gable, A.L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., et al. STRING v11: Protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47:D1 (2019 Jan 8), D607–D613.
STRING: Functional Protein Association Networks, Available from: https://string-db.org/, 2021 Nov 1.
Home - Reactome Pathway Database, Available from: https://reactome.org/, 2020 Dec 7.
Kanapeckaite, A., OmicInt package: Exploring omics data and regulatory networks using integrative analyses and machine learning. Artif. Intell Life Sci., 1, 2021 Dec 1, 100025 Available from https://linkinghub.elsevier.com/retrieve/pii/S2667318521000258.
ChEMBL Database, Available from: https://www.ebi.ac.uk/chembl/, 2021 Dec 14.
Download CAS COVID-19 Antiviral Candidate Compounds Dataset | CAS, Available from: https://www.cas.org/covid-19-antiviral-compounds-dataset, 2022 Jan 11.
RStudio | Open Source & Professional Software for Data Science Teams - RStudio, Available from: https://rstudio.com/, 2020 Oct 26.
Bioconductor - STRINGdb, Available from: https://www.bioconductor.org/packages/release/bioc/html/STRINGdb.html, 2022 Jan 15.
Bioconductor - clusterProfiler, Available from: https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html, 2020 Dec 7.
enrichGO function - RDocumentation, Available from: https://www.rdocumentation.org/packages/clusterProfiler/versions/3.0.4/topics/enrichGO, 2022 Aug 22.
enrichPathway function - RDocumentation, Available from: https://www.rdocumentation.org/packages/ReactomePA/versions/1.16.2/topics/enrichPathway, 2022 Aug 22.
Bioconductor - biomaRt, Available from: https://bioconductor.org/packages/release/bioc/html/biomaRt.html, 2022 Aug 22.
Welcome to Python.org, Available from: https://www.python.org/, 2022 Aug 22.
Jaeger, S., Fulle, S., Turk, S., Mol2vec: unsupervised machine learning approach with chemical intuition. J. Chem. Inf. Model. 58:1 (2018), 27–35.
RDKit, Available from: https://www.rdkit.org/, 2022 Jan 15.
NumPy, Available from: https://numpy.org/, 2022 Jan 15.
Pandas - Python Data Analysis Library, Available from: https://pandas.pydata.org/, 2022 Jan 15.
Waskom, M., seaborn: statistical data visualization. J. Open Source Softw., 6(60), 2021 Apr 6, 3021.
Matplotlib — Visualization with Python, Available from: https://matplotlib.org/, 2022 Jan 15.
Chemexpy PyPI, Available from: https://pypi.org/project/chemexpy/, 2022 Jan 15.
Scikit-learn: Machine Learning in Python — Scikit-learn 1.0.2 Documentation. Available from: https://scikit-learn.org/stable/, 2022 Jan 15.
lightgbm.LGBMClassifier — LightGBM 3.3.2.99 documentation. Available from: https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMClassifier.html, 2022 Aug 22.
TensorFlow, Available from: https://www.tensorflow.org/, 2022 Jan 15.
Keras: The Python Deep Learning API. Available from: https://keras.io/, 2022 Aug 22.
Nosengo, N., Can you teach old drugs new tricks?. Nature. 534:7607 (2016 Jun 14), 314–316 Available from: https://pubmed.ncbi.nlm.nih.gov/27306171/.
Wang, C., Lin, W., Playa, H., Sun, S., Cameron, K., Buolamwini, J.K., Dipyridamole analogues as pharmacological inhibitors of equilibrative nucleoside transporters. Identification of novel potent and selective inhibitors of the adenosine transporter function of human equilibrative nucleoside transporter 4 (hENT4). Biochem. Pharmacol. 86:11 (2013), 1531–1540 Available from: /pmc/articles/PMC3866046/.
Aliter, K.F., Al-Horani, R.A., Potential Therapeutic Benefits of Dipyridamole in COVID-19 Patients. Curr. Pharm. Des. 27:6 (2021 Oct 1), 866–875 Available from: https://pubmed.ncbi.nlm.nih.gov/33001004/.
Hanidziar, D., Baldyga, K., Ji, C.S., Lu, J., Zheng, H., Wiener-Kronish, J., et al. Standard sedation and sedation with isoflurane in mechanically ventilated patients with coronavirus Disease 2019. Crit. Care Explor., 3(3), 2021 Mar 5, e0370 Available from: https://journals.lww.com/ccejournal/Fulltext/2021/03000/Standard_Sedation_and_Sedation_With_Isoflurane_in.7.aspx.
Witenko, C.J., Littlefield, A.J., Abedian, S., An, A., Barie, P.S., Berger, K., The safety of continuous infusion propofol in mechanically ventilatedadults with Coronavirus Disease 2019. Ann. Pharmacother., 56(1), 2022 Jan 1;56(1):5. Available from: /pmc/articles/PMC8127019/ https://journals.sagepub.com/doi/10.1177/10600280211017315.
Nieuwenhuijs-Moeke, G.J., Jainandunsing, J.S., Struys MMRF, Sevoflurane, a sigh of relief in COVID-19?. BJA Br. J. Anaesth., 125(2), 2020 Aug 1, 118 Available from: /pmc/articles/PMC7252148/.
Kaura, V., Hopkins, P.M., Sevoflurane may not be a complete sigh of relief in COVID-19. Br. J. Anaesth. 125:6 (2020 Dec 1), e487–e488 Available from: http://www.bjanaesthesia.org.uk/article/S0007091220307625/fulltext.
Agúndez, J.A.G., Blanca, M., Cornejo-García, J.A., García-Martín, E., Pharmacogenomics of cyclooxygenases. Pharmacogenomics. 16:5 (2015 Apr 1), 501–522 Available from: https://pubmed.ncbi.nlm.nih.gov/25916522/.
Park, J.H., Lee, H.K., Re-analysis of single cell transcriptome reveals that the NR3C1-CXCL8-Neutrophil axis determines the severity of COVID-19. Front. Immunol., 11, 2020 Aug 28 Available from: https://pubmed.ncbi.nlm.nih.gov/32983174/.
Zeinalian, M., Salari-Jazi, A., Jannesari, A., Khanahmad, H., A potential protective role of losartan against coronavirus-induced lung damage. Infect. Control Hosp. Epidemiol., 41(6), 2020 Jun 1, 1 Available from: /pmc/articles/PMC7137531/.
Puskarich, M.A., Cummins, N.W., Ingraham, N.E., Wacker, D.A., Reilkoff, R.A., Driver, B.E., et al. A multi-center phase II randomized clinical trial of losartan on symptomatic outpatients with COVID-19. eClinicalMedicine., 37, 2021 Jul 1, 100957 Available from: http://www.thelancet.com/article/S2589537021002376/fulltext.
de Ligt, M., Hesselink, M.K.C., Jorgensen, J., Jocken, J.W.E., Blaak, E.E., Goossens, G.H., The angiotensin II åtype 1 receptor blocker valsartan in the battle against COVID-19. Obesity (Silver Spring) 29:9 (2021 Sep 1), 1423–1426 Available from: https://pubmed.ncbi.nlm.nih.gov/33955183/.
Fisk, M., Althage, M., Moosmang, S., Greasley, P.J., Cope, A.P., Jayne, D.R., et al. Endothelin antagonism and sodium glucose Co-transporter 2 inhibition. A potential combination therapeutic strategy for COVID-19. Pulm. Pharmacol. Ther., 69, 2021 Aug 1, 102035 Available from: /pmc/articles/PMC8084922/.
Ranucci, M., Ballotta, A., Di Dedda, U., Bayshnikova, E., Dei Poli, M., Resta, M., et al. The procoagulant pattern of patients with COVID-19 acute respiratory distress syndrome. J. Thromb. Haemost. 18:7 (2020 Jul 1), 1747–1751 Available from: https://pubmed.ncbi.nlm.nih.gov/32302448/.
Akşit, E., Kırılmaz, B., Gazi, E., Aydın, F., Ticagrelor can be an important agent in the treatment of severe COVID-19 patients with myocardial infarction. Balkan Med. J., 37(4), 2020, 233 Available from: /pmc/articles/PMC7285674/.
Kow, C.S., Hasan, S.S., The use of antiplatelet agents for arterial thromboprophylaxis in COVID-19. Rev. Esp. Cardiol. (Engl. Ed.), 74(1), 2021 Jan, 114 Available from: /pmc/articles/PMC7455174/.
Choubey, A., Dehury, B., Kumar, S., Medhi, B., Mondal, P., Naltrexone a potential therapeutic candidate for COVID-19. J. Biomol. Struct. Dyn. 40:3 (2020), 963–970 Available from: https://pubmed.ncbi.nlm.nih.gov/32930058/.
Sullivan, R., Kilaru, A., Hemmer, B., Campbell Cree, B.A., Greenberg, B.M., Kundu, U., et al. COVID-19 infection in fingolimod- or siponimod-treated patients: case series. Neurol. Neuroimmunol. Neuroinflam., 9(1), 2021 Jan, e1092 Available from: https://pubmed.ncbi.nlm.nih.gov/34848501/.
Gomez-Mayordomo, V., Montero-Escribano, P., Matías-Guiu, J.A., González-García, N., Porta-Etessam, J., Matías-Guiu, J., Clinical exacerbation of SARS-CoV2 infection after fingolimod withdrawal. J. Med. Virol. 93:1 (2021 Jan 1), 546–549 Available from: https://pubmed.ncbi.nlm.nih.gov/32644205/.
Plaze, M., Attali, D., Petit, A.-C., Blatzer, M., Simon-Loriere, E., Vinckier, F., et al. Repurposing chlorpromazine to treat COVID-19: The reCoVery study. Encephale. 46:3 (2020 Jun 1), 169–172 Available from: http://www.ncbi.nlm.nih.gov/pubmed/32425222.
Kindrachuk, J., Ork, B., Hart, B.J., Mazur, S., Holbrook, M.R., Frieman, M.B., et al. Antiviral potential of ERK/MAPK and PI3K/AKT/mTOR signaling modulation for Middle East respiratory syndrome coronavirus infection as identified by temporal kinome analysis. Antimicrob. Agents Chemother. 59:2 (2015 Feb 1), 1088–1099 Available from: https://pubmed.ncbi.nlm.nih.gov/25487801/.
Iba, T., Levy, J.H., Levi, M., Thachil, J., Coagulopathy in COVID-19. J. Thromb. Haemost. 18:9 (2020 Sep 1), 2103–2109 Available from: https://pubmed.ncbi.nlm.nih.gov/32558075/.
Aggarwal, M., Dass, J., Mahapatra, M., Hemostatic Abnormalities in COVID-19: An Update. Indian J. Hematol. Blood Transfus. 36:4 (2020 Oct 1), 616–626 Available from: https://pubmed.ncbi.nlm.nih.gov/32837053/.
NIH Begins Large Clinical Trial to Test Immune Modulators for Treatment of COVID-19, 2022 Jan 16, National Institutes of Health (NIH) Available from: https://www.nih.gov/news-events/news-releases/nih-begins-large-clinical-trial-test-immune-modulators-treatment-covid-19.
Files, D.C., Tacke, F., O'Sullivan, A., Dorr, P., Ferguson, W.G., Powderly, W.G., Rationale of using the dual chemokine receptor CCR2/CCR5 inhibitor cenicriviroc for the treatment of COVID-19. PLoS Pathog., 18(6), 2022 Jun 24, e1010547 Available from: https://pubmed.ncbi.nlm.nih.gov/35749425/.
Shaw, R.J., Bradbury, C., Abrams, S.T., Wang, G., Toh, C.H., COVID-19 and immunothrombosis: emerging understanding and clinical management. Br. J. Haematol. 194:3 (2021 Aug 1), 518–529 Available from: https://onlinelibrary.wiley.com/doi/full/10.1111/bjh.17664.
COVID-19 Therapeutics Prioritized for Testing in Clinical Trials, 2022 Aug 28, National Institutes of Health (NIH) Available from: https://www.nih.gov/research-training/medical-research-initiatives/activ/covid-19-therapeutics-prioritized-testing-clinical-trials.
Mansour, E., Bueno, F.F., de Lima-Júnior, J.C., Palma, A., Monfort-Pires, M., Bombassaro, B., et al. Evaluation of the efficacy and safety of icatibant and C1 esterase/kallikrein inhibitor in severe COVID-19: study protocol for a three-armed randomized controlled trial. Trials., 22(1), 2021 Dec 1 Available from: /pmc/articles/PMC7816150/.
Pérez-Jeldres, T., Alvarez-Lobos, M., Rivera-Nieves, J., Targeting Sphingosine-1-Phosphate signaling in immune-mediated diseases: beyond multiple sclerosis. Drugs. 81:9 (2021 Jun 1), 985–1002 Available from: https://pubmed.ncbi.nlm.nih.gov/33983615/.
Duecker, R.P., Adam, E.H., Wirtz, S., Gronau, L., Khodamoradi, Y., Eberhardt, F.J., et al. The mir-320 family is strongly downregulated in patients with COVID-19 induced severe respiratory failure. Int. J. Mol. Sci., 22(19), 2021 Oct 1 Available from: /pmc/articles/PMC8508658/.
Paul, S., Bravo Vázquez, L.A., Reyes-Pérez, P.R., Estrada-Meza, C., Aponte Alburquerque, R.A., Pathak, S., et al. The role of microRNAs in solving COVID-19 puzzle from infection to therapeutics: A mini-review. Virus Res., 308, 2022 Jan 15, 198631.
Alvarsson, J., Eklund, M., Engkvist, O., Spjuth, O., Carlsson, L., Wikberg, J.E.S., et al. Ligand-based target prediction with signature fingerprints. J. Chem. Inf. Model. 54:10 (2014 Oct 27), 2647–2653.
Messina, F., Giombini, E., Montaldo, C., Sharma, A.A., Zoccoli, A., Sekaly, R.P., et al. Looking for pathways related to COVID-19: confirmation of pathogenic mechanisms by SARS-CoV-2–host interactome. Cell Death Dis. 12:8 (2021 Aug 12), 1–10 Available from: https://www.nature.com/articles/s41419-021-03881-8.
Farahani, M., Niknam, Z., Mohammadi Amirabad, L., Amiri-Dashatan, N., Koushki, M., Nemati, M., et al. Molecular pathways involved in COVID-19 and potential pathway-based therapeutic targets. Biomed. Pharmacother., 145, 2022 Jan 1, 112420.
Nashiry, A., Sarmin Sumi, S., Islam, S., Quinn, J.M.W., Moni, M.A., Bioinformatics and system biology approach to identify the influences of COVID-19 on cardiovascular and hypertensive comorbidities. Brief. Bioinform. 22:2 (2021 Mar 1), 1387–1401 Available from: https://pubmed.ncbi.nlm.nih.gov/33458761/.
Dexmedetomidine: Uses, Interactions, Mechanism of Action | DrugBank Online. Available from: https://go.drugbank.com/drugs/DB00633, 2022 Jan 16.
Melatonin: Uses, Interactions, Mechanism of Action | DrugBank Online. Available from: https://go.drugbank.com/drugs/DB01065, 2022 Jan 16.
Bajusz, D., Rácz, A., Héberger, K., Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?. J. Chem. Thermodyn., 7(1), 2015 Dec 8, 20, 10.1186/s13321-015-0069-3.
Lavecchia, A., Machine-learning approaches in drug discovery: methods and applications. Drug Discov. Today Elsevier Ltd. 20 (2015), 318–331.
Zhang, J., Mucs, D., Norinder, U., Svensson, F., LightGBM: an effective and scalable algorithm for prediction of chemical toxicity-application to the Tox21 and mutagenicity data sets. J. Chem. Inf. Model., 59(10), 2019 Available from https://pubmed.ncbi.nlm.nih.gov/31560206/.
Asif, M., Saleem, M., Saadullah, M., Yaseen, H.S., Al, Zarzour R., COVID-19 and therapy with essential oils having antiviral, anti-inflammatory, and immunomodulatory properties. Inflammopharmacology., 28(5), 2020 Oct 1, 1 Available from: /pmc/articles/PMC7427755/.
Toft-Bertelsen, T.L., Jeppesen, M.G., Tzortzini, E., Xue, K., Giller, K., Becker, S., et al. Amantadine has potential for the treatment of COVID-19 because it inhibits known and novel ion channels encoded by SARS-CoV-2. Commun. Biol., 4(1), 2021 Dec Available from https://pubmed.ncbi.nlm.nih.gov/34853399/.
Lipinski, C.F., Maltarollo, V.G., Oliveira, P.R., da Silva, A.B.F., Honorio, K.M., Advances and perspectives in applying deep learning for drug design and discovery. Front. Robot. AI., 6, 2019 Nov 5, 108.
Camp, O.G., Bai, D., Gonullu, D.C., Nayak, N., Abu-Soud, H.M., Melatonin interferes with COVID-19 at several distinct ROS-related steps. J. Inorg. Biochem., 223, 2021 Oct 1, 111546.
Earm, K., Earm, Y.E., Integrative approach in the era of failing drug discovery and development. Integr. Med. Res., 3(4), 2014 Dec, 211 Available from: /pmc/articles/PMC5481768/.
Schett, G., Sloan, V.S., Stevens, R.M., Schafer, P., Apremilast: a novel PDE4 inhibitor in the treatment of autoimmune andinflammatory diseases. Ther. Adv. Musculoskelet. Dis., 2(5), 2010, 271 Available from: /pmc/articles/PMC3383510/.
Rosenbrier Ribeiro, L., Ian, Storer R., A semi-quantitative translational pharmacology analysis to understand the relationship between in vitro ENT1 inhibition and the clinical incidence of dyspnoea and bronchospasm. Toxicol. Appl. Pharmacol. 317 (2017 Feb 15), 41–50 Available from: https://pubmed.ncbi.nlm.nih.gov/28041785/.
Dipyridamole to Prevent Coronavirus Exacerbation of Respiratory Status (DICER) in COVID-19 - Full Text View - ClinicalTrials.gov. Available from: https://clinicaltrials.gov/ct2/show/NCT04391179, 2022 Jan 24.
Zhou, H.Y., Chen, W.D., Zhu, D.L., Wu, L.Y., Zhang, J., Han, W.Q., et al. The PDE1A-PKCα signaling pathway is involved in the upregulation of α-smooth muscle actin by TGF-β1 in adventitial fibroblasts. J. Vasc. Res., 47(1), 2010 Jan, 9 Available from: /pmc/articles/PMC2855283/.
Westermann, D., Becher, P.M., Lindner, D., Savvatis, K., Xia, Y., Fröhlich, M., et al. Selective PDE5A inhibition with sildenafil rescues left ventricular dysfunction, inflammatory immune response and cardiac remodeling in angiotensin II-induced heart failure in vivo. Basic Res. Cardiol., 107(6), 2012 Nov 1 Available from: https://pubmed.ncbi.nlm.nih.gov/23117837/.
Brown, R.A., Spina, D., Page, C.P., Adenosine receptors and asthma. Br. J. Pharmacol. 153:S1 (2008 Mar 1), S446–S456 Available from: https://onlinelibrary.wiley.com/doi/full/10.1038/bjp.2008.22.
Konrad, F.M., Neudeck, G., Vollmer, I., Ngamsri, K.C., Thiel, M., Reutershan, J., Protective effects of pentoxifylline in pulmonary inflammation are adenosine receptor A2A dependent. FASEB J. 27:9 (2013 Sep), 3524–3535 Available from: https://pubmed.ncbi.nlm.nih.gov/23699177/.
Pergolizzi, J.V., Varrassi, G., Magnusson, P., LeQuang, J.A., Paladini, A., Taylor, R., et al. COVID-19 and NSAIDS: a narrative review of knowns and unknowns. Pain Ther. 9:2 (2020 Dec 1), 353–358 Available from: https://pubmed.ncbi.nlm.nih.gov/32447629/.
Wagner, C., Griesel, M., Mikolajewska, A., Mueller, A., Nothacker, M., Kley, K., et al. Systemic corticosteroids for the treatment of COVID-19. Cochrane Database Syst. Rev., 8(8), 2021 Aug 16 Available from: https://pubmed.ncbi.nlm.nih.gov/34396514/.
Park, J., Lee, S.H., You, S.C., Kim, J., Yang, K., Non-steroidal anti-inflammatory agent use may not be associated with mortality of coronavirus disease 19. Sci. Report. 11:1 (2021 Mar 3), 1–7 Available from: https://www.nature.com/articles/s41598-021-84539-5.
Poutoglidou, F., Saitis, A., Kouvelas, D., Ibuprofen and COVID-19 disease: separating the myths from facts. Exp. Rev. Respir. Med. 15:8 (2021), 979–983 Available from: https://pubmed.ncbi.nlm.nih.gov/34196258/.
Rinott, E., Kozer, E., Shapira, Y., Bar-Haim, A., Youngster, I., Ibuprofen use and clinical outcomes in COVID-19 patients. Clin. Microbiol. Infect. 26:9 (2020 Sep 1), 1259.e5–1259.e7 Available from: https://pubmed.ncbi.nlm.nih.gov/32535147/.
Manjani, L., Desai, N., Kohli, A., Arya, R., Woods, C., Desale, S., Effects of acetaminophen on outcomes in patients hospitalized with COVID-19. Chest., 160(4), 2021 Oct, A1072 Available from: /pmc/articles/PMC8503320/.
Awasthi, S., Wagner, T., Venkatakrishnan, A.J., Puranik, A., Hurchik, M., Agarwal, V., et al. Plasma IL-6 levels following corticosteroid therapy as an indicator of ICU length of stay in critically ill COVID-19 patients. Cell Death Dis., 7(1), 2021 Jun 1 Available from: https://pubmed.ncbi.nlm.nih.gov/33723251/.
van Paassen, J., Vos, J.S., Hoekstra, E.M., Neumann, K.M.I., Boot, P.C., Arbous, S.M., Corticosteroid use in COVID-19 patients: a systematic review and meta-analysis on clinical outcomes. Crit. Care, 24(1), 2020 Dec 1 Available from: https://pubmed.ncbi.nlm.nih.gov/33317589/.
Morán Blanco, J.I., Alvarenga Bonilla, J.A., Homma, S., Suzuki, K., Fremont-Smith, P., Villar Gómez De Las Heras, K., Antihistamines and azithromycin as a treatment for COVID-19 on primary health care – A retrospective observational study in elderly patients. Pulm. Pharmacol. Ther., 67, 2021 Apr 1, 101989 Available from: /pmc/articles/PMC7833340/.
Hirasawa, N., Expression of histidine decarboxylase and its roles in inflammation. Int. J. Mol. Sci., 20(2), 2019 Jan 2 Available from: https://pubmed.ncbi.nlm.nih.gov/30654600/.
Hogan, R.B., Hogan, R.B., Cannon, T., Rappai, M., Studdard, J., Paul, D., et al. Dual-histamine receptor blockade with cetirizine - famotidine reduces pulmonary symptoms in COVID-19 patients. Pulm. Pharmacol. Ther., 63, 2020 Aug 1 Available from: https://pubmed.ncbi.nlm.nih.gov/32871242/.
Crespi, B., Alcock, J., Conflicts over calcium and the treatment of COVID-19. Evol. Med. Public Heal., 9(1), 2021, 149 Available from: /pmc/articles/PMC7717197/.
Jiang, B., Liang, S., Liang, G., Wei, H., Could dantrolene be explored as a repurposed drug to treat COVID-19 patients by restoring intracellular calcium homeostasis?. Eur. Rev. Med. Pharmacol. Sci. 24:19 (2020), 10228–10238 Available from: https://pubmed.ncbi.nlm.nih.gov/33090434/.
Cesta MC, Zippoli M, Marsiglia C, Gavioli EM, Mantelli F, Allegretti M, et al. The role of Interleukin-8 in lung inflammation and injury: implications for the management of COVID-19 and hyperinflammatory acute respiratory distress syndrome. Front. Pharmacol. 2022 Jan 12;3931. Available from: https://www.frontiersin.org/articles/10.3389/fphar.2021.808797/full.
Chiang, C.C., Korinek, M., Cheng, W.J., Hwang, T.L., Targeting neutrophils to treat acute respiratory distress syndrome in coronavirus disease. Front. Pharmacol., 11, 2020 Oct 9, 1576.
WHO Expert Panel Strongly Advises Against Use of Hydroxychloroquine to Prevent COVID-19 | BMJ. Available from: https://www.bmj.com/company/newsroom/who-expert-panel-strongly-advises-against-use-of-hydroxychloroquine-to-prevent-covid-19/, 2022 Feb 6.
Caldwell, B., Aldington, S., Weatherall, M., Shirtcliffe, P., Beasley, R., Risk of cardiovascular events and celecoxib: a systematic review and meta-analysis. J. R. Soc. Med., 99(3), 2006 Mar, 132 Available from: /pmc/articles/PMC1383759/.
Bakker, T., Klopotowska, J.E., Eslami, S., De Lange, D.W., Van Marum, R., Van Der Sijs, H., et al. The effect of ICU-tailored drug-drug interaction alerts on medication prescribing and monitoring: Protocol for a cluster randomized stepped-wedge trial. BMC Med. Inform. Decis Mak. 19:1 (2019 Aug 13), 1–10 Available from: https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-019-0888-7.
Alshalalfa, M., Alhajj, R., Using context-specific effect of miRNAs to identify functional associations between miRNAs and gene signatures. BMC Bioinform., 14(SUPPL12), 2013 Sep 24.
Zhang, S., Amahong, K., Sun, X., Lian, X., Liu, J., Sun, H., et al. The miRNA: a small but powerful RNA for COVID-19. Brief. Bioinform. 22:2 (2021 Mar 1), 1137–1149 Available from: /pmc/articles/PMC7989616/.
Gutmann, C., Khamina, K., Theofilatos, K., Diendorfer, A.B., Burnap, S.A., Nabeebaccus, A., et al. Association of cardiometabolic microRNAs with COVID-19 severity and mortality. Cardiovasc. Res. 118:2 (2021 Nov 10), 461–474 Available from: /pmc/articles/PMC8689968/.
Hirohara, M., Saito, Y., Koda, Y., Sato, K., Sakakibara, Y., Convolutional neural network based on SMILES representation of compounds for detecting chemical motif. BMC Bioinform. 19:19 (2018 Dec 31), 83–94 Available from: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2523-5.
Wu, F., Zhou, Y., Li, L., Shen, X., Chen, G., Wang, X., et al. Computational approaches in preclinical studies on drug discovery and development. Front. Chem., 2020 Sep 11, 726.