Login Register Cart 0
Generic placeholder image

Current Drug Discovery Technologies

Editor-in-Chief

ISSN (Print): 1570-1638
ISSN (Online): 1875-6220

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Review Article

Computational Approach to Combat COVID-19 Infection: Emerging Tools for Accelerating Drug Research

Author(s): Biswa Mohan Sahoo*, Subrat Kumar Bhattamisra, Sarita Das, Abhishek Tiwari, Varsha Tiwari, Manish Kumar and Sunil Singh

Volume 19, Issue 3, 2022

Published on: 21 February, 2022

Article ID: e170122200314 Pages: 14

DOI: 10.2174/1570163819666220117161308

Price: $65

Abstract

Background: The process of drug discovery and development is expensive, complex, timeconsuming, and risky. There are different techniques involved in the process of drug development, including random screening, computational approaches, molecular manipulation, and serendipitous research. Among these methods, the computational approach is considered an efficient strategy to accelerate and economize the drug discovery process.

Objective: This approach is mainly applied in various phases of the drug discovery process, including target identification, target validation, lead identification, and lead optimization. Due to the increase in the availability of information regarding various biological targets of different disease states, computational approaches such as molecular docking, de novo design, molecular similarity calculation, virtual screening, pharmacophore-based modeling, and pharmacophore mapping have been applied extensively.

Methods: Various drug molecules can be designed by applying computational tools to explore the drug candidates for the treatment of Coronavirus infection. The World Health Organization announced the coronavirus disease as COVID-19 and declared it a global pandemic on 11 February 2020. Therefore, it is thought of interest to the scientific community to apply computational methods to design and optimize the pharmacological properties of various clinically available and FDA-approved drugs such as remdesivir, ribavirin, favipiravir, oseltamivir, ritonavir, arbidol, chloroquine, hydroxychloroquine, carfilzomib, baraticinib, prulifloxacin, etc., for effective treatment of COVID-19 infection.

Results: Further, various survey reports suggest that extensive studies are carried out by various research communities to find out the safety and efficacy profile of these drug candidates.

Conclusion: This review is focused on the study of various aspects of these drugs related to their target sites on the virus, binding interactions, physicochemical properties, etc.

Keywords: Computational tools, design, drugs, molecular docking, coronavirus, physiochemical properties.

Graphical Abstract

[1]
Myers S, Baker A. Drug discovery-an operating model for a new era. Nat Biotechnol 2001; 19(8): 727-30.
[http://dx.doi.org/10.1038/90765] [PMID: 11479559]
[2]
Elhassa GO, Alfarouk KO. Drug development: Stages of drug development. J Pharmacovigil 2015; 3(3): 1-3.
[http://dx.doi.org/10.4172/2329-6887.1000e141]
[3]
Mohs RC, Greig NH. Drug discovery and development: Role of basic biological research. Alzheimers Dement (N Y) 2017; 3(4): 651-7.
[http://dx.doi.org/10.1016/j.trci.2017.10.005] [PMID: 29255791]
[4]
Singh S, Malik BK, Sharma DK. Molecular drug targets and structure based drug design: A holistic approach. Bioinformation 2006; 1(8): 314-20.
[http://dx.doi.org/10.6026/97320630001314] [PMID: 17597912]
[5]
Keiser MJ, Setola V, Irwin JJ, et al. Predicting new molecular targets for known drugs. Nature 2009; 462(7270): 175-81.
[http://dx.doi.org/10.1038/nature08506] [PMID: 19881490]
[6]
Sliwoski G, Kothiwale S, Meiler J, Lowe EW Jr. Computational methods in drug discovery. Pharmacol Rev 2013; 66(1): 334-95.
[http://dx.doi.org/10.1124/pr.112.007336] [PMID: 24381236]
[7]
Akamatsu M. Current state and perspectives of 3D-QSAR. Curr Top Med Chem 2002; 2(12): 1381-94.
[http://dx.doi.org/10.2174/1568026023392887] [PMID: 12470286]
[8]
McCammon JA. Computer-aided molecular design. Science 1987; 238(4826): 486-91.
[http://dx.doi.org/10.1126/science.3310236] [PMID: 3310236]
[9]
Zhang S. Computer-aided drug discovery and development. Methods Mol Biol 2011; 716: 23-38.
[http://dx.doi.org/10.1007/978-1-61779-012-6_2] [PMID: 21318898]
[10]
Finn PW, Kavraki LE. Computational approaches to drug design. Algorithmica 1999; 25(2-3): 347-71.
[http://dx.doi.org/10.1007/PL00008282]
[11]
Leelananda SP, Lindert S. Computational methods in drug discovery. Beilstein J Org Chem 2016; 12: 2694-718.
[http://dx.doi.org/10.3762/bjoc.12.267] [PMID: 28144341]
[12]
Lengauer T, Rarey M. Computational methods for biomolecular docking. Curr Opin Struct Biol 1996; 6(3): 402-6.
[http://dx.doi.org/10.1016/S0959-440X(96)80061-3] [PMID: 8804827]
[13]
Hung CL, Chen CC. Computational approaches for drug discovery. Drug Dev Res 2014; 75(6): 412-8.
[http://dx.doi.org/10.1002/ddr.21222] [PMID: 25195585]
[14]
Xiang M, Cao Y, Fan W, Chen L, Mo Y. Computer-aided drug design: lead discovery and optimization. Comb Chem High Throughput Screen 2012; 15(4): 328-37.
[http://dx.doi.org/10.2174/138620712799361825] [PMID: 22221065]
[15]
Jorgensen WL. The many roles of computation in drug discovery. Science 2004; 303(5665): 1813-8.
[http://dx.doi.org/10.1126/science.1096361] [PMID: 15031495]
[16]
Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020; 323(11): 1061-9.
[http://dx.doi.org/10.1001/jama.2020.1585] [PMID: 32031570]
[17]
Li G, Fan Y, Lai Y, et al. Coronavirus infections and immune responses. J Med Virol 2020; 92(4): 424-32.
[http://dx.doi.org/10.1002/jmv.25685] [PMID: 31981224]
[18]
Mitjà O, Clotet B. Use of antiviral drugs to reduce COVID-19 transmission. Lancet Glob Health 2020; 8(5): e639-40.
[http://dx.doi.org/10.1016/S2214-109X(20)30114-5] [PMID: 32199468]
[19]
de Wit E, van Doremalen N, Falzarano D, Munster VJ. SARS and MERS: Recent insights into emerging coronaviruses. Nat Rev Microbiol 2016; 14(8): 523-34.
[http://dx.doi.org/10.1038/nrmicro.2016.81] [PMID: 27344959]
[20]
Sheahan TP, Sims AC, Zhou S, et al. An orally bioavailable broad-spectrum antiviral inhibits SARS-CoV-2 in human airway epithelial cell cultures and multiple coronaviruses in mice. Sci Transl Med 2020; 12(541), eabb5883.
[http://dx.doi.org/10.1126/scitranslmed.abb5883] [PMID: 32253226]
[21]
Tok TT, Tatar G. Structures and functions of coronavirus proteins: Molecular modeling of viral nucleoprotein. Int J Virol Infect Dis 2017; 2(1): 1-7.
[22]
Walls AC, Park YJ, Tortorici MA, Wall A, McGuire AT, Veesler D. Structure, function and antigenicity of the SARS-CoV-2 spike glycoprotein. Cell 2020; 181(2): 281-292.e6.
[http://dx.doi.org/10.1016/j.cell.2020.02.058] [PMID: 32155444]
[23]
Guo YR, Cao QD, Hong ZS, et al. The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak-An update on the status. Mil Med Res 2020; 7(1): 11.
[http://dx.doi.org/10.1186/s40779-020-00240-0] [PMID: 32169119]
[24]
Jin Z, Du X, Xu Y, et al. Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors. Nature 2020; 582(7811): 289-93.
[http://dx.doi.org/10.1038/s41586-020-2223-y] [PMID: 32272481]
[25]
Guan WJ, Ni ZY, Hu Y, et al. China medical treatment expert group for Covid-19. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020; 382(18): 1708-20.
[http://dx.doi.org/10.1056/NEJMoa2002032] [PMID: 32109013]
[26]
Shereen MA, Khan S, Kazmi A, Bashir N, Siddique R. COVID-19 infection: Origin, transmission, and characteristics of human coronaviruses. J Adv Res 2020; 24: 91-8.
[http://dx.doi.org/10.1016/j.jare.2020.03.005] [PMID: 32257431]
[27]
Weiss SR, Navas-Martin S. Coronavirus pathogenesis and the emerging pathogen severe acute respiratory syndrome coronavirus. Microbiol Mol Biol Rev 2005; 69(4): 635-64.
[http://dx.doi.org/10.1128/MMBR.69.4.635-664.2005] [PMID: 16339739]
[28]
Soltani S, Zokeri AM. A systemic literature review of current therapeutic approaches for COVID-19 patient. J Pharm Res Int 2020; 32(7): 13-25.
[http://dx.doi.org/10.9734/jpri/2020/v32i730455]
[29]
Fan K, Wei P, Feng Q, et al. Biosynthesis, purification, and substrate specificity of severe acute respiratory syndrome coronavirus 3C-like proteinase. J Biol Chem 2004; 279(3): 1637-42.
[http://dx.doi.org/10.1074/jbc.M310875200] [PMID: 14561748]
[30]
Thiel V, Ivanov KA, Putics Á, et al. Mechanisms and enzymes involved in SARS coronavirus genome expression. J Gen Virol 2003; 84(Pt 9): 2305-15.
[http://dx.doi.org/10.1099/vir.0.19424-0] [PMID: 12917450]
[31]
Dyall J, Gross R, Kindrachuk J, et al. Middle east respiratory syndrome and severe acute respiratory syndrome: Current therapeutic options and potential targets for novel therapies. Drugs 2017; 77(18): 1935-66.
[http://dx.doi.org/10.1007/s40265-017-0830-1] [PMID: 29143192]
[32]
Zhu N, Zhang D, Wang W, et al. China novel coronavirus investigating and research team. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020; 382(8): 727-33.
[http://dx.doi.org/10.1056/NEJMoa2001017] [PMID: 31978945]
[33]
Jogalekar MP, Veerabathini A, Gangadaran P. Novel 2019 coronavirus: Genome structure, clinical trials, and outstanding questions. Exp Biol Med (Maywood) 2020; 245(11): 964-9.
[http://dx.doi.org/10.1177/1535370220920540] [PMID: 32306751]
[34]
Barlow A, Landolf KM, Barlow B, et al. Review of emerging pharmacotherapy for the treatment of coronavirus disease 2019. Pharmacotherapy 2020; 40(5): 416-37.
[http://dx.doi.org/10.1002/phar.2398] [PMID: 32259313]
[35]
Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020; 395(10223): 497-506.
[http://dx.doi.org/10.1016/S0140-6736(20)30183-5] [PMID: 31986264]
[36]
Wang F, Liu D, Wang H, et al. Computational screening for active compounds targeting protein sequences: methodology and experimental validation. J Chem Inf Model 2011; 51(11): 2821-8.
[http://dx.doi.org/10.1021/ci200264h] [PMID: 21955088]
[37]
Singh B, Mal G, Gautam SK, Mukesh M. Computer-aided drug discovery Adv Anim Biotechnol. 2019; 471-81.
[http://dx.doi.org/10.1007/978-3-030-21309-1_44]
[38]
Kalyaanamoorthy S, Chen YP. Structure-based drug design to augment hit discovery. Drug Discov Today 2011; 16(17-18): 831-9.
[http://dx.doi.org/10.1016/j.drudis.2011.07.006] [PMID: 21810482]
[39]
Shuker SB, Hajduk PJ, Meadows RP, Fesik SW. Discovering high-affinity ligands for proteins: SAR by NMR. Science 1996; 274(5292): 1531-4.
[http://dx.doi.org/10.1126/science.274.5292.1531] [PMID: 8929414]
[40]
Chen L, Morrow JK, Tran HT, Phatak SS, Du-Cuny L, Zhang S. From laptop to benchtop to bedside: structure-based drug design on protein targets. Curr Pharm Des 2012; 18(9): 1217-39.
[http://dx.doi.org/10.2174/138161212799436386] [PMID: 22316152]
[41]
Song CM, Lim SJ, Tong JC. Recent advances in computer-aided drug design. Brief Bioinform 2009; 10(5): 579-91.
[http://dx.doi.org/10.1093/bib/bbp023] [PMID: 19433475]
[42]
Acharya C, Coop A, Polli JE, Mackerell AD Jr. Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach. Curr Computeraided Drug Des 2011; 7(1): 10-22.
[http://dx.doi.org/10.2174/157340911793743547] [PMID: 20807187]
[43]
Anderson AC. The process of structure-based drug design. Chem Biol 2003; 10(9): 787-97.
[http://dx.doi.org/10.1016/j.chembiol.2003.09.002] [PMID: 14522049]
[44]
Bakheet TM, Doig AJ. Properties and identification of human protein drug targets. Bioinformatics 2009; 25(4): 451-7.
[http://dx.doi.org/10.1093/bioinformatics/btp002] [PMID: 19164304]
[45]
Wang R, Fang X, Lu Y, Wang S. The PDBbind database: Collection of binding affinities for protein-ligand complexes with known three-dimensional structures. J Med Chem 2004; 47(12): 2977-80.
[http://dx.doi.org/10.1021/jm030580l] [PMID: 15163179]
[46]
Chen XP, Du GH. Target validation: A door to drug discovery Drug discov therap 2007; 1: 23-9..
[47]
Aminpour M, Montemagno C, Tuszynski JA. An overview of molecular modelling for drug discovery with specific illustrative examples of applications. Molecules 2019; 24(9): 1693.
[http://dx.doi.org/10.3390/molecules24091693] [PMID: 31052253]
[48]
Kitchen DB, Decornez H, Furr JR, Bajorath J. Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 2004; 3(11): 935-49.
[http://dx.doi.org/10.1038/nrd1549] [PMID: 15520816]
[49]
Blaney J, Dixon S. A good ligand is hard to find: automated docking methods. Perspect Drug Discov Des 1993; 1: 301-19.
[http://dx.doi.org/10.1007/BF02174531]
[50]
Liu M, Wang S. MCDOCK: a Monte Carlo simulation approach to the molecular docking problem. J Comput Aided Mol Des 1999; 13(5): 435-51.
[http://dx.doi.org/10.1023/A:1008005918983] [PMID: 10483527]
[51]
Barcellos GB, Pauli I, Caceres RA, Timmers LF, Dias R, de Azevedo WF Jr. Molecular modeling as a tool for drug discovery. Curr Drug Targets 2008; 9(12): 1084-91.
[http://dx.doi.org/10.2174/138945008786949388] [PMID: 19128219]
[52]
Oshiro CM, Kuntz ID, Dixon JS. Flexible ligand docking using a genetic algorithm. J Comput Aided Mol Des 1995; 9(2): 113-30.
[http://dx.doi.org/10.1007/BF00124402] [PMID: 7608743]
[53]
Willett P. Searching for pharmacophoric patterns in databases of three-dimensional chemical structures. J Mol Recognit 1995; 8(5): 290-303.
[http://dx.doi.org/10.1002/jmr.300080503] [PMID: 8619950]
[54]
Dudek AZ, Arodz T, Gálvez J. Computational methods in developing quantitative structure-activity relationships (QSAR): A review. Comb Chem High Throughput Screen 2006; 9(3): 213-28.
[http://dx.doi.org/10.2174/138620706776055539] [PMID: 16533155]
[55]
Vilar S, Costanzi S. Predicting the biological activities through QSAR analysis and docking-based scoring. Methods Mol Biol 2012; 914: 271-84.
[http://dx.doi.org/10.1007/978-1-62703-023-6_16] [PMID: 22976034]
[56]
Cramer RD III, Patterson DE, Bunce JD. Recent advances in comparative molecular field analysis (CoMFA). Prog Clin Biol Res 1989; 291: 161-5.
[PMID: 2726839]
[57]
Geladi P, Kowalski BR. Partial least-squares regression: A tutorial. Anal Chim Acta 1986; 185: 1-17.
[http://dx.doi.org/10.1016/0003-2670(86)80028-9]
[58]
Klebe G, Abraham U, Mietzner T. Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. J Med Chem 1994; 37(24): 4130-46.
[http://dx.doi.org/10.1021/jm00050a010] [PMID: 7990113]
[59]
Clark D, Jones G, Willett P, Kenny P, Glen R. Pharmacophoric pattern matching in files of three-dimensional chemical structures: Comparison of conformational searching algorithms for flexible searching. J Chem Inf Comput Sci 1994; 34: 197-206.
[http://dx.doi.org/10.1021/ci00017a026]
[60]
Leach AR, Gillet VJ, Lewis RA, Taylor R. Three-dimensional pharmacophore methods in drug discovery. J Med Chem 2010; 53(2): 539-58.
[http://dx.doi.org/10.1021/jm900817u] [PMID: 19831387]
[61]
Sanders MP, Barbosa AJ, Zarzycka B, et al. Comparative analysis of pharmacophore screening tools. J Chem Inf Model 2012; 52(6): 1607-20.
[http://dx.doi.org/10.1021/ci2005274] [PMID: 22646988]
[62]
Vincent MJ, Bergeron E, Benjannet S, et al. Chloroquine is a potent inhibitor of SARS coronavirus infection and spread. Virol J 2005; 2(1): 69.
[http://dx.doi.org/10.1186/1743-422X-2-69] [PMID: 16115318]
[63]
Pardi N, Weissman D. Development of vaccines and antivirals for combating viral pandemics. Nat Biomed Eng 2020; 4(12): 1128-33.
[http://dx.doi.org/10.1038/s41551-020-00658-w] [PMID: 33293724]
[64]
Hoffmann M, Kleine-Weber H, Schroeder S, et al. SARSCoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell 2020; 181(2): 271-280.e8.
[http://dx.doi.org/10.1016/j.cell.2020.02.052] [PMID: 32142651]
[65]
Gurwitz D. Angiotensin receptor blockers as tentative SARS-CoV-2 therapeutics. Drug Dev Res 2020; 81(5): 537-40.
[http://dx.doi.org/10.1002/ddr.21656] [PMID: 32129518]
[66]
Kadam RU, Wilson IA. Structural basis of influenza virus fusion inhibition by the antiviral drug Arbidol. Proc Natl Acad Sci USA 2017; 114(2): 206-14.
[http://dx.doi.org/10.1073/pnas.1617020114] [PMID: 28003465]
[67]
Gupta S, Mishra KP, Ganju L. Broad-spectrum antiviral properties of andrographolide. Arch Virol 2017; 162(3): 611-23.
[http://dx.doi.org/10.1007/s00705-016-3166-3] [PMID: 27896563]
[68]
Enmozhi SK, Raja K, Sebastine I, Joseph J. Andrographolide as a potential inhibitor of SARS-CoV-2 main protease: An in silico approach. J Biomol Struct Dyn 2021; 39(9): 3092-8.
[http://dx.doi.org/10.1080/07391102.2020.1760136] [PMID: 32329419]
[69]
Nivetha R, Bhuvaragavan S, Muthu Kumar T, Ramanathan K, Janarthanan S. Inhibition of multiple SARS-CoV-2 proteins by an antiviral biomolecule, seselin from Aegle marmelos deciphered using molecular docking analysis. J Biomol Struct Dyn 2021; 25: 1-12.
[http://dx.doi.org/10.1080/07391102.2021.1955009] [PMID: 34431451]
[70]
Somu C, Karuppiah H, Sundaram J. Antiviral activity of seselin from Aegle marmelos against nuclear polyhedrosis virus infection in the larvae of silkworm, Bombyx mori. J Ethnopharmacol 2019; 245, 112155.
[http://dx.doi.org/10.1016/j.jep.2019.112155] [PMID: 31449858]
[71]
McKeage K, Lyseng-Williamson KA. Fostamatinib in chronic immune thrombocytopenia: a profile of its use in the USA. Drugs Ther Perspect 2018; 34(10): 451-6.
[http://dx.doi.org/10.1007/s40267-018-0551-x] [PMID: 30459507]
[72]
Saha S, Halder AK, Bandyopadhyay SS, et al. Drug repurposing for COVID-19 using computational screening: Is Fostamatinib/R406 a potential candidate? Methods 2021; S1046.
[http://dx.doi.org/10.1016/j.ymeth.2021.08.007] [PMID: 34455072]
[73]
Costanzo M, De Giglio MAR, Roviello GN. SARS-CoV-2: Recent reports on antiviral therapies based on lopinavir/ritonavir, darunavir/umifenovir, hydroxychloroquine, remdesivir, favipiravir and other drugs for the treatment of the new coronavirus. Curr Med Chem 2020; 27(27): 4536-41.
[http://dx.doi.org/10.2174/0929867327666200416131117] [PMID: 32297571]
[74]
Narkhede RR, Cheke RS, Ambhore JP, Shinde SD. The molecular docking study of potential drug candidates showing anti-COVID-19 activity by exploring of therapeutic targets of SARS-CoV-2. Eurasian J Med Oncol 2020; 4(3): 185-95.
[75]
Joo K, Lee J, Lee J. Methods for accurate homology modeling by global optimization. Methods Mol Biol 2012; 857: 175-88.
[http://dx.doi.org/10.1007/978-1-61779-588-6_7] [PMID: 22323221]
[76]
Prabakaran P, Xiao X, Dimitrov DS. A model of the ACE2 structure and function as a SARS-CoV receptor. Biochem Biophys Res Commun 314(1): 235e41..
[77]
Hodos RA, Kidd BA, Khader S, Readhead BP, Dudley JT. Computational approaches to drug repurposing and pharmacology. Wiley Interdiscip Rev Syst Biol Med 2016; 8(3): 186-210.
[http://dx.doi.org/10.1002/wsbm.1337] [PMID: 27080087]
[78]
Zhavoronkov A. Artificial intelligence for drug discovery, biomarker development, and generation of novel chemistry. Mol Pharm 2018; 15(10): 4311-3.
[http://dx.doi.org/10.1021/acs.molpharmaceut.8b00930] [PMID: 30269508]
[79]
Cui W, Yang K, Yang H. Recent Progress in the drug development targeting SARS-CoV-2 main protease as treatment for COVID-19. Front Mol Biosci 2020; 7, 616341.
[http://dx.doi.org/10.3389/fmolb.2020.616341] [PMID: 33344509]
[80]
Wang J. Fast identification of possible drug treatment of Coronavirus Disease-19 (COVID-19) through computational drug repurposing study. J Chem Inf Model 2020; 60(6): 3277-86.
[http://dx.doi.org/10.1021/acs.jcim.0c00179] [PMID: 32315171]
[81]
Katakam P, Adiki SK, Assaleh FH, Ahmed MM. An update on therapeutic repurposing strategies for COVID-19. Indo Global J Pharm Sci 2020; 10(1): 12-8.
[http://dx.doi.org/10.35652/IGJPS.2020.10102]
[82]
Ciemny M, Kurcinski M, Kamel K, et al. Protein-peptide docking: opportunities and challenges. Drug Discov Today 2018; 23(8): 1530-7.
[http://dx.doi.org/10.1016/j.drudis.2018.05.006] [PMID: 29733895]
[83]
Mahdian S, Zarrabi M, Panahi Y, Dabbagh S. Repurposing FDA-approved drugs to fight COVID-19 using in silico methods: Targeting SARS-CoV-2 RdRp enzyme and host cell receptors (ACE2, CD147) through virtual screening and molecular dynamic simulations. Inform Med Unlocked 2021; 23, 100541.
[http://dx.doi.org/10.1016/j.imu.2021.100541] [PMID: 33649734]
[84]
Kumar S. Novel Coronavirus (COVID-19) Outbreak: Hope and search for effective therapeutic agent. Lett Drug Des Discov 2020; 17(8): 940-2.
[http://dx.doi.org/10.2174/1570180817999200612095513]
[85]
Wang M, Cao R, Zhang L, et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res 2020; 30(3): 269-71.
[http://dx.doi.org/10.1038/s41422-020-0282-0] [PMID: 32020029]
[86]
Sen Gupta PS, Biswal S, Singha D, Rana MK. Binding insight of clinically oriented drug famotidine with the identified potential target of SARS-CoV-2. J Biomol Struct Dyn 2021; 39(14): 5327-33.
[http://dx.doi.org/10.1080/07391102.2020.1784795] [PMID: 32579065]
[87]
Sen Gupta PS, Rana MK. Ivermectin, famotidine and doxycycline: A suggested combinatorial therapeutic for the treatment of COVID-19. ACS Pharmacol Transl Sci 2020; 3(5): 1037-8.
[http://dx.doi.org/10.1021/acsptsci.0c00140] [PMID: 33073202]
[88]
Grifoni A, Sidney J, Zhang Y, Scheuermann RH, Peters B, Sette A. A sequence homology and bioinformatic approach can predict candidate targets for immune responses to SARS-CoV-2. Cell Host Microbe 2020; 27(4): 671-680.e2.
[http://dx.doi.org/10.1016/j.chom.2020.03.002] [PMID: 32183941]
[89]
Russell CD, Millar JE, Baillie JK. Clinical evidence does not support corticosteroid treatment for 2019-nCoV lung injury. Lancet 2020; 395(10223): 473-5.
[http://dx.doi.org/10.1016/S0140-6736(20)30317-2] [PMID: 32043983]
[90]
Ojha PK, Kar S, Krishna JG, Roy K, Leszczynski J. Therapeutics for COVID-19: from computation to practices-where we are, where we are heading to. Mol Divers 2021; 25(1): 625-59.
[http://dx.doi.org/10.1007/s11030-020-10134-x] [PMID: 32880078]
[91]
Biggioggero M, Crotti C, Becciolini A, Favalli EG. Tocilizumab in the treatment of rheumatoid arthritis: an evidence-based review and patient selection. Drug Des Devel Ther 2018; 13: 57-70.
[http://dx.doi.org/10.2147/DDDT.S150580] [PMID: 30587928]
[92]
Clinical trial of combined use of hydroxychloroquine, azithromycin, and tocilizumab for the treatment of COVID-19 - full text view - ClinicalTrials.gov Available from: . https://clinicaltrials.gov/ct2/show/
[93]
Hussain A, Hussain A, Verma CK. COVID-19 infection: A review of summarized clinical trials study for the treatment. Coronaviruses 2021; 2: 431-44.
[http://dx.doi.org/10.2174/2666796701999200925204309]
[94]
Vardhan G, Kumar V, Agrawal M, Dhamija P. Combination of Hydroxychloroquine, Melatonin and Mercaptopurine as a possible intervention for prophylaxis and treatment of novel COVID-19 Infection. Coronaviruses 2021; 2: 415-8.
[http://dx.doi.org/10.2174/2666796701999201016154957]
[95]
Hwang W, Lei W, Katritsis NM, MacMahon M, Chapman K, Han N. Current and prospective computational approaches and challenges for developing COVID-19 vaccines. Adv Drug Deliv Rev 2021; 172: 249-74.
[http://dx.doi.org/10.1016/j.addr.2021.02.004] [PMID: 33561453]
[96]
Grein J, Ohmagari N, Shin D, et al. Compassionate use of remdesivir for patients with severe Covid-19. N Engl J Med 2020; 382(24): 2327-36.
[http://dx.doi.org/10.1056/NEJMoa2007016] [PMID: 32275812]
[97]
Dong L, Hu S, Gao J. Discovering drugs to treat coronavirus disease 2019 (COVID-19). Drug Discov Ther 2020; 14(1): 58-60.
[http://dx.doi.org/10.5582/ddt.2020.01012] [PMID: 32147628]
[98]
Naz A, Shahid F, Butt TT, Awan FM, Ali A, Malik A. Designing multi-epitope vaccines to combat emerging Coronavirus disease 2019 (COVID-19) by employing immuno-informatics approach. Front Immunol 2020; 11: 1663.
[http://dx.doi.org/10.3389/fimmu.2020.01663] [PMID: 32754160]
[99]
Dong Y, Dai T, Wei Y, Zhang L, Zheng M, Zhou F. A systematic review of SARS-CoV-2 vaccine candidates. Signal Transduct Target Ther 2020; 5(1): 237.
[http://dx.doi.org/10.1038/s41392-020-00352-y] [PMID: 33051445]
[100]
Ashburn TT, Thor KB. Drug repositioning: Identifying and developing new uses for existing drugs. Nat Rev Drug Discov 2004; 3(8): 673-83.
[http://dx.doi.org/10.1038/nrd1468] [PMID: 15286734]
[101]
Mouton A, Pitcher R, Douglas T. Computer-aided detection of pulmonary pathology in pediatric chest radiographs. Med Image Comput Comput Assist Interv 2010; 13: 619-25..
[http://dx.doi.org/10.1007/978-3-642-15711-0_77]
[102]
Qin C, Yao D, Shi Y, Song Z. Computer-aided detection in chest radiography based on artificial intelligence: A survey. Biomed Eng Online 2018; 17(1): 113.
[http://dx.doi.org/10.1186/s12938-018-0544-y] [PMID: 30134902]

Rights & Permissions Print Cite
Article Metrics
22
1
© 2024 Bentham Science Publishers | Privacy Policy