Generic placeholder image

Letters in Drug Design & Discovery

Author(s): Hriday Kumar Basak, Soumen Saha, Joydeep Ghosh, Uttam Paswan, Sujoy Karmakar, Ayon Pal and Abhik Chatterjee*

DOI: 10.2174/1570180818666210804141613

DownloadDownload PDF Flyer Cite As
Sequence Analysis, Structure Prediction of Receptor Proteins and In Silico Study of Potential Inhibitors for Management of Life Threatening COVID-19

Page: [108 - 122] Pages: 15

  • * (Excluding Mailing and Handling)

Abstract

Background: Treatment of the Covid-19 pandemic caused by the highly contagious and pathogenic SARS-CoV-2 is a global menace. Day by day, this pandemic is getting worse. Doctors, scientists and researchers across the world are urgently scrambling for a cure for novel corona virus and continuously working at break neck speed to develop vaccines or drugs. But to date, there are no specific drugs or vaccines available in the market to cope up with the virus.

Objective: The present study helps us to elucidate 3D structures of SARS-CoV-2 proteins and also to identify natural compounds as potential inhibitors against COVID-19.

Methods: The 3D structures of the proteins were constructed using Modeller 9.16 modeling tool. Modelled proteins were validated with PROCHECK by Ramachandran plot analysis. In this study, a small library of natural compounds (fifty compounds) was docked to the hACE2 binding site of the modelled surface glycoprotein of SARS-CoV-2 using AutoDock Vina to repurpose these inhibitors against SARS-CoV-2. Conceptual density functional theory calculations of the best eight compounds had been performed by Gaussian-09. Geometry optimizations for these molecules were done at M06-2X/ def2-TZVP level of theory. ADME parameters, pharmacokinetic properties and drug likeness of the compounds were analyzed using swissADME website.

Results: In this study, we analysed the sequences of surface glycoprotein, nucleocapsid phosphoprotein and envelope protein obtained from different parts of the globe. We modelled all the different sequences of surface glycoprotein and envelop protein in order to derive 3D structure of a molecular target, which is essential for the development of therapeutics. Different electronic properties of the inhibitors have been calculated using DFT through M06-2X functional with def2-TZVP basis set. Docking result at the hACE2 binding site of all modelled surface glycoproteins of SARSCoV- 2 showed that all the eight inhibitors (actinomycin D, avellanin C, ichangin, kanglemycin A, obacunone, ursolic acid, ansamiotocin P-3 and isomitomycin A) studied here were many folds better compared to hydroxychloroquine which has been found to be effective to treat patients suffering from COVID-19. All the inhibitors meet most of the criteria of drug likeness assessment.

Conclusion: We expect that eight compounds (actinomycin D, avellanin C, ichangin, kanglemycin A, obacunone, ursolic acid, ansamiotocin P-3 and isomitomycin A) can be used as potential inhibitors against SARS-CoV-2.

Keywords: COVID-19, SARS-CoV-2, hACE2, density functional theory, docking, potential inhibitors.

Graphical Abstract

[1]
Costanzo, M.; De Giglio, M.A.R.; Roviello, G.N. 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), 4536-4541.
[http://dx.doi.org/10.2174/0929867327666200416131117] [PMID: 32297571]
[2]
Zhou, Y.; Hou, Y.; Shen, J.; Huang, Y.; Martin, W.; Cheng, F. Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2. Cell Discov., 2020, 6(1), 14.
[http://dx.doi.org/10.1038/s41421-020-0153-3] [PMID: 33723226]
[3]
Zhou, P. Discovery of a novel coronavirus associated with the recent pneumonia outbreak in humans and its potential bat origin. bioRxiv, 2020.
[http://dx.doi.org/10.1101/2020.01.22.914952]
[4]
Chen, Y.; Guo, Y.; Pan, Y.; Zhao, Z.J. Structure analysis of the receptor binding of 2019-nCoV. Biochem. Biophys. Res. Commun., 2020, 525(1), 135-140.
[http://dx.doi.org/10.1016/j.bbrc.2020.02.071] [PMID: 32081428]
[5]
Hasan, A. A review on the cleavage priming of the spike protein on coronavirus by angiotensin-converting enzyme-2 and furin. J. Biomol. Struct. Dyn., 2020, 39(8), 3025-3033.
[http://dx.doi.org/10.1080/07391102.2020.1754293] [PMID: 32274964]
[6]
Jin, Z.; Du, X.; Xu, Y.; Deng, Y.; Liu, M.; Zhao, Y.; Zhang, B.; Li, X.; Zhang, L.; Peng, C.; Duan, Y.; Yu, J.; Wang, L.; Yang, K.; Liu, F.; Jiang, R.; Yang, X.; You, T.; Liu, X.; Yang, X.; Bai, F.; Liu, H.; Liu, X.; Guddat, L.W.; Xu, W.; Xiao, G.; Qin, C.; Shi, Z.; Jiang, H.; Rao, Z.; Yang, H. Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors. Nature, 2020, 582(7811), 289-293.
[http://dx.doi.org/10.1038/s41586-020-2223-y] [PMID: 32272481]
[7]
Narkhede, R.R.; Pise, A.V.; Cheke, R.S.; Shinde, S.D. Recognition of natural products as potential inhibitors of COVID-19 main protease (Mpro): In-silico evidences. Nat. Prod. Bioprospect., 2020, 10(5), 297-306.
[http://dx.doi.org/10.1007/s13659-020-00253-1] [PMID: 32557405]
[8]
Xian, Y.; Zhang, J.; Bian, Z.; Zhou, H.; Zhang, Z.; Lin, Z.; Xu, H. Bioactive natural compounds against human coronaviruses: A review and perspective. Acta Pharm. Sin. B, 2020, 10(7), 1163-1174.
[http://dx.doi.org/10.1016/j.apsb.2020.06.002] [PMID: 32834947]
[9]
Wang, Z.; Yang, L. Turning the tide: Natural products and natural-product-inspired chemicals as potential counters to SARS-CoV-2 infection. Front. Pharmacol., 2020, 11(1013), 1013.
[http://dx.doi.org/10.3389/fphar.2020.01013] [PMID: 32714193]
[10]
Antonio, A.S.; Wiedemann, L.S.M.; Veiga-Junior, V.F. Natural products’ role against COVID-19. RSC Advances, 2020, 10(39), 23379-23393.
[http://dx.doi.org/10.1039/D0RA03774E]
[11]
Orhan, I.E.; Senol Deniz, F.S. Natural products as potential leads against coronaviruses: Could they be encouraging structural models against SARS-CoV-2? Nat. Prod. Bioprospect., 2020, 10(4), 171-186.
[http://dx.doi.org/10.1007/s13659-020-00250-4] [PMID: 32529545]
[12]
Ibrahim, M.A.A.; Abdeljawaad, K.A.A.; Abdelrahman, A.H.M.; Hegazy, M.F. Natural-like products as potential SARS-CoV-2 Mpro inhibitors: In-silico drug discovery. J. Biomol. Struct. Dyn., 2021, 39(15), 5722-5734.
[http://dx.doi.org/10.1080/07391102.2020.1790037] [PMID: 32643529]
[13]
Parida, P.K.; Paul, D.; Chakravorty, D. The natural way forward: Molecular dynamics simulation analysis of phytochemicals from Indian medicinal plants as potential inhibitors of SARS-CoV-2 targets. Phytother. Res., 2020, 34(12), 3420-3433.
[http://dx.doi.org/10.1002/ptr.6868]
[14]
Lung, J.; Lin, Y.S.; Yang, Y.H.; Chou, Y.L.; Shu, L.H.; Cheng, Y.C.; Liu, H.T.; Wu, C.Y. The potential chemical structure of anti-SARS-CoV-2 RNA-dependent RNA polymerase. J. Med. Virol., 2020, 92(6), 693-697.
[http://dx.doi.org/10.1002/jmv.25761] [PMID: 32167173]
[15]
Kumar, V. Withanone and caffeic acid phenethyl ester are predicted to interact with main protease (M(pro)) of SARS-CoV-2 and inhibit its activity. J. Biomol. Struct. Dyn., 2020, 1-13.
[http://dx.doi.org/10.1080/07391102.2020.1772108]
[16]
Vardhan, S.; Sahoo, S.K. in silico ADMET and molecular docking study on searching potential inhibitors from limonoids and triterpenoids for COVID-19. Comput. Biol. Med., 2020, 124, 103936-103936.
[http://dx.doi.org/10.1016/j.compbiomed.2020.103936] [PMID: 32738628]
[17]
Borges, A.; Simões, M. Quorum sensing inhibition by marine bacteria. 2019, 17(7)
[http://dx.doi.org/10.3390/md17070427]
[18]
Mosaei, H.; Molodtsov, V.; Kepplinger, B.; Harbottle, J.; Moon, C.W.; Jeeves, R.E.; Ceccaroni, L.; Shin, Y.; Morton-Laing, S.; Marrs, E.C.L.; Wills, C.; Clegg, W.; Yuzenkova, Y.; Perry, J.D.; Bacon, J.; Errington, J.; Allenby, N.E.E.; Hall, M.J.; Murakami, K.S.; Zenkin, N. Mode of action of Kanglemycin A, an ansamycin natural product that is active against rifampicin-resistant Mycobacterium tuberculosis. Mol. Cell, 2018, 72(2), 263-274.e5.
[http://dx.doi.org/10.1016/j.molcel.2018.08.028] [PMID: 30244835]
[19]
Asfour, H.Z. Anti-quorum sensing natural compounds. J. Microscopy Ultrastructure, 2018, 6(1), 1-10.
[http://dx.doi.org/10.4103/JMAU.JMAU_10_18]
[20]
Leaf-nosed bat. Encyclopædia Britannica, 2009. Available at: https://www.britannica.com/animal/leaf-nosed-bat
[21]
Igarashi, Y.; Gohda, F.; Kadoshima, T.; Fukuda, T.; Hanafusa, T.; Shojima, A.; Nakayama, J.; Bills, G.F.; Peterson, S. Avellanin C, an inhibitor of quorum-sensing signaling in Staphylococcus aureus, from Hamigera ingelheimensis. J. Antibiot. (Tokyo), 2015, 68(11), 707-710.
[http://dx.doi.org/10.1038/ja.2015.50] [PMID: 25944536]
[22]
Wang, X.; Wang, R.; Kang, Q.; Bai, L. The antitumor agent ansamitocin P-3 binds to cell division protein FtsZ in Actinosynnema pretiosum. Biomolecules, 2020, 10(5), E699.
[http://dx.doi.org/10.3390/biom10050699] [PMID: 32365857]
[23]
Istrefi, Q.; Türkeş, C.; Arslan, M.; Demir, Y.; Nixha, A.R.; Beydemir, Ş.; Küfrevioğlu, Ö.I. Sulfonamides incorporating ketene N, S-acetal bioisosteres as potent carbonic anhydrase and acetylcholinesterase inhibitors. Arch. Pharm. (Weinheim), 2020, 353(6), e1900383.
[http://dx.doi.org/10.1002/ardp.201900383] [PMID: 32285537]
[24]
Jayaprakash, P.; Biswal, J.; Kanagarajan, S.; Prabhu, D.; Gogoi, P.; Prasad Kanaujia, S.; Jeyakanthan, J. Design of novel PhMTNA inhibitors, targeting neurological disorder through homology modeling, molecular docking, and dynamics approaches. J. Recept. Signal Transduct. Res., 2019, 39(1), 28-38.
[http://dx.doi.org/10.1080/10799893.2019.1567786] [PMID: 31241401]
[25]
Bernstein, F.C.; Koetzle, T.F.; Williams, G.J.; Meyer, E.F., Jr; Brice, M.D.; Rodgers, J.R.; Kennard, O.; Shimanouchi, T.; Tasumi, M. The Protein Data Bank. A computer-based archival file for macromolecular structures. Eur. J. Biochem., 1977, 80(2), 319-324.
[http://dx.doi.org/10.1111/j.1432-1033.1977.tb11885.x] [PMID: 923582]
[26]
Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol., 1990, 215(3), 403-410.
[http://dx.doi.org/10.1016/S0022-2836(05)80360-2] [PMID: 2231712]
[27]
Webb, B.; Sali, A. Comparative protein structure modeling using MODELLER; Curr. Protoc. Bioinform, 2014, p. 47.
[http://dx.doi.org/10.1002/0471250953.bi0506s47]
[28]
Chenna, R.; Sugawara, H.; Koike, T.; Lopez, R.; Gibson, T.J.; Higgins, D.G.; Thompson, J.D. Multiple sequence alignment with the clustal series of programs. Nucleic Acids Res., 2003, 31(13), 3497-3500.
[http://dx.doi.org/10.1093/nar/gkg500] [PMID: 12824352]
[29]
Laskowski, R.A. PROCHECK: A program to check the stereochemical quality of protein structures. J. Appl. Cryst., 1993, 26(2), 283-291.
[http://dx.doi.org/10.1107/S0021889892009944]
[30]
Ramachandran, G.N.; Ramakrishnan, C.; Sasisekharan, V. Stereochemistry of polypeptide chain configurations. J. Mol. Biol., 1963, 7(1), 95-99.
[http://dx.doi.org/10.1016/S0022-2836(63)80023-6] [PMID: 13990617]
[31]
Laskowski, R.A.; Rullmannn, J.A.; MacArthur, M.W.; Kaptein, R.; Thornton, J.M. AQUA and PROCHECK-NMR: Programs for checking the quality of protein structures solved by NMR. J. Biomol. NMR, 1996, 8(4), 477-486.
[http://dx.doi.org/10.1007/BF00228148] [PMID: 9008363]
[32]
Micheletti, C.; Orland, H. MISTRAL: A tool for energy-based multiple structural alignment of proteins. Bioinformatics, 2009, 25(20), 2663-2669.
[http://dx.doi.org/10.1093/bioinformatics/btp506] [PMID: 19692555]
[33]
Türkeş, C.; Demir, Y.; Beydemir, Ş. Calcium channel blockers: Molecular docking and inhibition studies on carbonic anhydrase I and II isoenzymes. J. Biomol. Struct. Dyn., 2021, 39(5), 1672-1680.
[34]
Demir, Y.; Türkeş, C.; Beydemir, Ş. Molecular docking studies and inhibition properties of some antineoplastic agents against paraoxonase-I. Anticancer. Agents Med. Chem., 2020, 20(7), 887-896.
[http://dx.doi.org/10.2174/1871520620666200218110645] [PMID: 32067621]
[35]
Trott, O.; Olson, A.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2010, 31(2), 455-461.
[PMID: 19499576]
[36]
Nagy, Á. Density functional. Theory and application to atoms and molecules. Phys. Rep., 1998, 298(1), 1-79.
[http://dx.doi.org/10.1016/S0370-1573(97)00083-5]
[37]
Roy, R.K.; Saha, S. Studies of regioselectivity of large molecular systems using DFT based reactivity descriptors. Annu. Repor. Secti. "C" (Physical Chemistry), 2010, 106, 118-162.
[http://dx.doi.org/10.1039/B811052M]
[38]
Frisch, M.J. T.G.; Schlegel, HB.; Scuseria, GE.; Robb, MA.; Cheeseman, JR.; Scalmani, Gaussian 09; Gaussian, Inc: Wallingford, CT, USA, 2009.
[39]
Parr, R.G. Electronegativity: The density functional viewpoint. J. Chem. Phys., 1978, 68(8), 3801-3807.
[http://dx.doi.org/10.1063/1.436185]
[40]
Parr, R.G.; Pearson, R.G. Absolute hardness: Companion parameter to absolute electronegativity. J. Am. Chem. Soc., 1983, 105(26), 7512-7516.
[http://dx.doi.org/10.1021/ja00364a005]
[41]
Pearson, R.G. Chemical hardness and density functional theory. J. Chem. Sci., 2005, 117(5), 369-377.
[http://dx.doi.org/10.1007/BF02708340]
[42]
Roy, D.R.; Sarkar, U.; Chattaraj, P.K.; Mitra, A.; Padmanabhan, J.; Parthasarathi, R.; Subramanian, V.; Van Damme, S.; Bultinck, P. Analyzing toxicity through electrophilicity. Mol. Divers., 2006, 10(2), 119-131.
[http://dx.doi.org/10.1007/s11030-005-9009-x] [PMID: 16763875]
[43]
Parr, R.G.; Szentpály, L.v.; Liu, S. Electrophilicity Index. J. Am. Chem. Soc., 1999, 121(9), 1922-1924.
[http://dx.doi.org/10.1021/ja983494x]
[44]
Gázquez, J.L.; Cedillo, A.; Vela, A. Electrodonating and electroaccepting powers. J. Phys. Chem. A, 2007, 111(10), 1966-1970.
[http://dx.doi.org/10.1021/jp065459f] [PMID: 17305319]
[45]
Chattaraj, P.K.; Chakraborty, A.; Giri, S. Net electrophilicity. J. Phys. Chem. A, 2009, 113(37), 10068-10074.
[http://dx.doi.org/10.1021/jp904674x] [PMID: 19702288]
[46]
Ramirez-Balderrama, K.; Orrantia-Borunda, E.; Flores-Holguin, N. Calculation of global and local reactivity descriptors of carbodiimides, a DFT study. J. Theor. Comput. Chem., 2017, 16(03), 1750019.
[http://dx.doi.org/10.1142/S0219633617500195]
[47]
Flores-Holguín, N.; Frau, J.; Glossman-Mitnik, D. Calculation of the global and local conceptual DFT indices for the prediction of the chemical reactivity properties of papuamides A-F marine drugs. Molecules, 2019, 24(18), 3312.
[http://dx.doi.org/10.3390/molecules24183312] [PMID: 31514433]
[48]
Demir, Y. Naphthoquinones, benzoquinones, and anthraquinones: Molecular docking, ADME and inhibition studies on human serum paraoxonase-1 associated with cardiovascular diseases. Drug Dev. Res., 2020, 81(5), 628-636.
[http://dx.doi.org/10.1002/ddr.21667] [PMID: 32232985]
[49]
Seal, A.; Aykkal, R.; Babu, R.O.; Ghosh, M. Docking study of HIV-1 reverse transcriptase with phytochemicals. Bioinformation, 2011, 5(10), 430-439.
[http://dx.doi.org/10.6026/97320630005430] [PMID: 21423889]
[50]
Senthilvel, P.; Lavanya, P.; Kumar, K.M.; Swetha, R.; Anitha, P.; Bag, S.; Sarveswari, S.; Vijayakumar, V.; Ramaiah, S.; Anbarasu, A. Flavonoid from Carica papaya inhibits NS2B-NS3 protease and prevents Dengue 2 viral assembly. Bioinformation, 2013, 9(18), 889-895.
[http://dx.doi.org/10.6026/97320630009889] [PMID: 24307765]
[51]
Sever, B.; Türkeş, C.; Altıntop, M.D.; Demir, Y.; Beydemir, Ş. Thiazolyl-pyrazoline derivatives: In vitro and in silico evaluation as potential acetylcholinesterase and carbonic anhydrase inhibitors. Int. J. Biol. Macromol., 2020, 163, 1970-1988.
[http://dx.doi.org/10.1016/j.ijbiomac.2020.09.043] [PMID: 32931834]
[52]
Sorkun, M.C.; Khetan, A.; Er, S. AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds. Sci. Data, 2019, 6(1), 143.
[http://dx.doi.org/10.1038/s41597-019-0151-1] [PMID: 31395888]
[53]
Ghose, A.K.; Viswanadhan, V.N.; Wendoloski, J.J. A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J. Comb. Chem., 1999, 1(1), 55-68.
[http://dx.doi.org/10.1021/cc9800071] [PMID: 10746014]
[54]
Veber, D.F.; Johnson, S.R.; Cheng, H.Y.; Smith, B.R.; Ward, K.W.; Kopple, K.D. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem., 2002, 45(12), 2615-2623.
[http://dx.doi.org/10.1021/jm020017n] [PMID: 12036371]
[55]
Egan, W.J.; Merz, K.M., Jr; Baldwin, J.J. Prediction of drug absorption using multivariate statistics. J. Med. Chem., 2000, 43(21), 3867-3877.
[http://dx.doi.org/10.1021/jm000292e] [PMID: 11052792]
[56]
Muegge, I.; Heald, S.L.; Brittelli, D. Simple selection criteria for drug-like chemical matter. J. Med. Chem., 2001, 44(12), 1841-1846.
[http://dx.doi.org/10.1021/jm015507e] [PMID: 11384230]
[57]
Prabakaran, P.; Gan, J.; Feng, Y.; Zhu, Z.; Choudhry, V.; Xiao, X.; Ji, X.; Dimitrov, D.S. Structure of severe acute respiratory syndrome coronavirus receptor-binding domain complexed with neutralizing antibody. J. Biol. Chem., 2006, 281(23), 15829-15836.
[http://dx.doi.org/10.1074/jbc.M600697200] [PMID: 16597622]
[58]
Azad, G.K. Identification and molecular characterization of mutations in nucleocapsid phosphoprotein of SARS-CoV-2. PeerJ, 2021, 9, e10666-e10666.
[http://dx.doi.org/10.7717/peerj.10666] [PMID: 33505806]
[59]
Samudrala, R.; Levitt, M. A comprehensive analysis of 40 blind protein structure predictions. BMC Struct. Biol., 2002, 2(1), 3.
[http://dx.doi.org/10.1186/1472-6807-2-3] [PMID: 12150712]
[60]
Moussa, S. In-silico studies of antimalarial-agent artemisinin and derivatives portray more potent binding to Lys353 and Lys31-binding hotspots of SARS-CoV-2 spike protein than hydroxychloroquine: potential repurposing of artenimol for COVID-19. 2020.
[61]
Lan, J.; Ge, J.; Yu, J.; Shan, S.; Zhou, H.; Fan, S.; Zhang, Q.; Shi, X.; Wang, Q.; Zhang, L.; Wang, X. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature, 2020, 581(7807), 215-220.
[http://dx.doi.org/10.1038/s41586-020-2180-5] [PMID: 32225176]
[62]
Khelfaoui, H.; Harkati, D.; Saleh, B.A. Molecular docking, molecular dynamics simulations and reactivity, studies on approved drugs library targeting ACE2 and SARS-CoV-2 binding with ACE2. J. Biomol. Struct. Dyn., 2020, 1-17.
[http://dx.doi.org/10.1080/07391102.2020.1803967] [PMID: 32752951]
[63]
Majumder, R.; Mandal, M. Screening of plant-based natural compounds as a potential COVID-19 main protease inhibitor: An in silico docking and molecular dynamics simulation approach. J. Biomol. Struct. Dyn., 2020, 1-16.
[http://dx.doi.org/10.1080/07391102.2020.1817787] [PMID: 32897138]
[64]
Sanchez-Andrada, P.; Alkorta, I.; Elguero, J. A theoretical study of the addition reactions of HF, H2O, H2S, NH3 and HCN to carbodiimide and related heterocumulenes. J. Mol. Struct. THEOCHEM, 2001, 544, 5-23.
[http://dx.doi.org/10.1016/S0166-1280(00)00515-7]
[65]
Fonteh, P. E.A. Omondi B, Guzei I, J Darkwa, D Meyer. Impedance technology reveals correlations between cytotoxicity and lipophilicity of mono and bimetallic phosphine complexes. An International Journal on the Role of Metal Ions in Biology Biochem. Med. (Zagreb), 2015, 28(4), 653-667.
[66]
Han, Y.; Zhang, J.; Hu, C.Q.; Zhang, X.; Ma, B.; Zhang, P. In silico ADME and toxicity prediction of ceftazidime and its impurities. Front. Pharmacol., 2019, 10, 434.
[http://dx.doi.org/10.3389/fphar.2019.00434] [PMID: 31068821]
[67]
Kalaycı, M.; Türkeş, C.; Arslan, M.; Demir, Y.; Beydemir, Ş. Novel benzoic acid derivatives: Synthesis and biological evaluation as multitarget acetylcholinesterase and carbonic anhydrase inhibitors. Arch. Pharm. (Weinheim), 2021, 354(3), e2000282.
[http://dx.doi.org/10.1002/ardp.202000282] [PMID: 33155700]
[68]
Enmozhi, S.K. Andrographolide as a potential inhibitor of SARS-CoV-2 main protease: An in silico approach. J. Biomol. Struct. Dyn., 2020, 1-7.
[http://dx.doi.org/10.1080/07391102.2020.1760136] [PMID: 32329419]
[69]
Gündoğdu, S. New isoindole-1,3-dione substituted sulfonamides as potent inhibitors of carbonic anhydrase and acetylcholinesterase: Design, synthesis, and biological evaluation. ChemistrySelect, 2019, 4, 13347-13355.
[http://dx.doi.org/10.1002/slct.201903458]