journal article·2021-06-30Open access

MONOSACCHARIDE DERIVATIVES: SYNTHESIS, ANTIMICROBIAL, PASS, ANTIVIRAL AND MOLECULAR DOCKING STUDIES AGAINST SARS-COV-2 MPRO INHIBITORS

FARHANA YASMIN, MOHAMMED R. AMIN, MOHAMMED A. HOSEN, MOHAMMED Z. H. BULBUL, SUJAN DEY, SARKAR M. A. KAWSAR

Cellulose Chemistry and Technology· Volume 55· Issue 5-6

Abstract

Several carbohydrate-based drugs are currently being used to treat a number of diseases in humans worldwide. Thus, our research group has focused on the synthesis of new methyl α-D-mannopyranoside (MDM) derivatives and their antimicrobial evaluation through computational studies. A series of MDM derivatives (2-6) were synthesized through facile regioselective acylation, using the direct method affording 6-O-(3-chlorobenzoyl) derivatives. This isolated 6-O-derivative was further transformed to 2,3,4-tri-O-acyl derivatives, bearing a wide variety of functionalities in a single molecular framework. The structures of the newly designed molecules were elucidated with the aid of IR, 1H NMR, mass spectroscopy, and elemental analysis. The prediction of the activity spectra for the compounds (PASS) and their in vitro antimicrobial evaluation were performed, demonstrating them to be potential antimicrobial agents. The antimicrobial tests demonstrated that the compounds 3 and 5 were the most potent with the minimum inhibitory concentration (MIC) values, ranging from 0.312±0.01 to 1.25±0.03 mg/mL, and minimum bactericidal concentration (MBC) values, ranging from 0.625±0.02 to 2.50±0.05 mg/mL. A quantum chemical study was performed to calculate the thermodynamic, molecular orbital and electrostatic potential properties of the designed compounds. Molecular docking simulation was carried out against SARS-CoV-2 Mpro protein 7BQY and 6Y84 to investigate their binding energy and binding tactics with the viral protein, and better binding affinity than that of the parent drug was observed. Also, pharmacokinetic prediction revealed an improved drug-likeness profile for all MDM derivatives.
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Research context

OpenAlex topics: Carbohydrate Chemistry and Synthesis · Synthesis and biological activity · Glycosylation and Glycoproteins Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

"Department of Chemistry, Faculty of Science, University of Chittagong, Chittagong-4331, Bangladesh "

"Department of Microbiology, Faculty of Biological Science, University of Chittagong, Chittagong-4331, Bangladesh "

References (50)

Show source-provided references
1. "1 C. R. Bertozzi and L. L. Kiessling, Science, 291, 2357 (2001), https://doi.org/10.1126/science.105982010.1126/science.1059820 ↗
2. 2 Y. Fujii, N. Dohmae, K. Takio, S. M. A. Kawsar, R. Matsumoto et al., J. Biol. Chem., 287, 44772 (2012), https://doi.org/10.1074/jbc.M112.41801210.1074/jbc.M112.418012 ↗
3. 3 A. Varki, Glycobiology, 3, 97 (1993), https://doi.org/10.1093/glycob/3.2.9710.1093/glycob/3.2.97 ↗
4. 4 S. M. A. Kawsar, A. K. M. S. Kabir, M. M. R. Bhuiyan, M. K. Hossain and M. N. Anwar, J. Pharm. Sci., 2, 107 (2012), https://doi.org/10.5530/rjps.2012.3.1210.5530/rjps.2012.3.12 ↗
5. 5 M. Arifuzzaman, M. M. Islam, M. M. Rahman, A. R. Mohammad and S. M. A. Kawsar, ACTA Pharm. Sci., 56, 22 (2018), https://doi.org/10.23893/1307-2080.APS.0562210.23893/1307-2080.APS.05622 ↗
6. 6 S. M. A Kawsar, A. A. Hamida, A. U. Sheikh, M. K. Hossain, A. C. Shagir et al., Int. J. Org. Chem., 5, 232 (2015), https://doi.org/10.4236/ijoc.2015.5402310.4236/ijoc.2015.54023 ↗
7. 7 S. M. A. Kawsar, M. O. Faruk, M. S. Rahman, Y. Fujii and Y. Ozeki, Scientia Pharm., 82, 1 (2014), https://doi.org/10.3797/scipharm.1308-0310.3797/scipharm.1308-03 ↗
8. 8 K. M. Rana, J. Ferdous, A. Hosen and S. M. A. Kawsar, J. Siberian Fed. Univ. Chem., 13, 465 (2020), https://doi.org/10.17516/1998-2836-019910.17516/1998-2836-0199 ↗
9. 9 M. M. H. Misbah, J. Ferdous, M. Z. H. Bulbul, T. S. Chowdhury, S. Dey et al., Int. J. Biosci., 16, 299 (2020), http://dx.doi.org/10.12692/ijb/16.4.299-309
10. 10 M. Z. H. Bulbul, T. S. Chowdhury, M. M. H. Misbah, J. Ferdous, S. Dey et al., Pharmacia, 68, 23 (2021), https://doi.org/10.3897/pharmacia.68.e5654310.3897/pharmacia.68.e56543.figure1 ↗
11. 11 M. Islam, M. Arifuzzaman, M. Rahman, M. A. Rahman and S. M. A. Kawsar, Hacettepe J. Biol. Chem., 47, 153 (2019), https://doi.org/10.15671/hjbc.62203810.15671/hjbc.622038 ↗
12. 12 S. R. Devi, S. Jesmin, M. Rahman, M. A. Manchur, Y. Fujii et al., Acta Pharm. Sci., 57, 47 (2019), https://doi.org/10.23893/1307-2080.APS.0570410.23893/1307-2080.APS.05704 ↗
13. 13 S. M. A. Kawsar, M. A. Hosen, Y. Fujii, Y. Ozeki, J. Comput. Chem. Mol. Model., 4, 452 (2020), http://www.dx.doi.org/10.25177/JCCMM.4.4.RA.1066310.25177/JCCMM.4.4.RA.10663 ↗
14. 14 H. Lu, Biosci. Trends, 14, 69 (2020), https://doi.org/10.5582/bst.2020.0102010.5582/bst.2020.01020 ↗
15. 15 M. Z. H. Bulbul, M. A. Hosen, J. Ferdous, T. S. Chowdhury, M. M. H. Misbah et al., Int. J. New Chem., 8, 88 (2021), https://doi.org/10.22034/ijnc.2020.131337.1124
16. 16 J. Maowa, M. A. Hosen, A. Alam, K. M. Rana, Y. Fujii et al., Phys. Chem. Res., 9, 385 (2021), https://doi.org/10.22036/pcr.2021.264541.1869
17. 17 A. Alam, M. A. Hosen, A. Hosen, Y. Fujii, Y. Ozeki et al., J. Mex. Chem. Soc., 65, 256 (2021), http://dx.doi.org/10.29356/jmcs.v65i1.146410.29356/jmcs.v65i2.1464 ↗
18. 18 S. M. A. Kawsar and M. A. Hosen, Turkish Comp. Theo. Chem., 4, 59 (2020), https://doi.org/10.33435/tcandtc.71880710.33435/tcandtc.718807 ↗
19. 19 S. M. A. Kawsar, A. K. M. S. Kabir, M. M. Manik, M. K. Hossain and M. N. Anwar, Int. J. Biosci., 2, 66 (2012), http://www.innspub.net10.5530/rjps.2012.3.12 ↗
20. 20 Clinical and Laboratory Standards Institute (CLSI). Performance Standards for Antimicrobial Disk Susceptibility Tests. 23rd Informational Supplement M100–S23, Wayne, USA, 2013
21. 21 R. K. Grover and J. D. Moore, Phytopathology, 52, 876 (1962), https://doi.org/10.4236/jqis.2011.1200610.4236/jqis.2011.12006 ↗
22. 22 S. Kumaresan, V. Senthilkumar, A. Stephen and B. S. Balakumar, World J. Pharm. Res., 4, 1035 (2015)
23. 23 P. H. Seeberger and D. B. Werz, Nature, 446, 1046 (2007), https://doi:10.1038/nature0581910.1038/nature05819 ↗
24. 24 M. J. Frisch, G. W. Trucks, H. B. Schlegel, G. E. Scuseria, A. Robb et al., Gaussian 09. Gaussian Inc, Wallingford, CT, https://gaussian.com/g09citation/
25. 25 A. D. Becke, Phys. Rev., 38, 3098 (1988), https://doi.org/10.1103/PhysRevA.38.309810.1103/PhysRevA.38.3098 ↗
26. 26 C. Lee, W. Yang and R. G. Parr, Phys. Rev., 37, 785 (1988), https://doi.org/10.1103/PhysRevB.37.78510.1103/PhysRevB.37.785 ↗
27. 27 H. M. Berman, J. Westbrook and Z. Feng, Nucleic Acids Res., 28, 235 (2000), https://doi.org/10.1093/nar/28.1.23510.1093/nar/28.1.235 ↗
28. 28 W. L. Delano, PyMOL Molecular Graphics System, De-Lano Scientific, San Carlos, CA, USA, 2002, http://www.pymol.org
29. 29 N. Guex and M. C. Peitsch, Electrophoresis, 18, 2714 (1997), https://doi.org/10.1002/elps.115018150510.1002/elps.1150181505 ↗
30. 30 C. H. Williams (Eds.), “Chemical Biology: Methods and Protocols”, Springer, New York, USA, 2015, p. 243, https://doi.org/10.1007/978-1-4939-2269-710.1007/978-1-4939-2269-7 ↗
31. 31 Version ADS 4.0, (2017), Accelrys, San Diego, USA
32. 32 F. Cheng, W. Li, Y. Zhou J. Shen, Z. Wu et al., J. Chem. Info. Model., 52, 3099 (2012), https://doi.org/10.1021/ci300367a10.1021/ci300367a ↗
33. 33 L. L. G. Ferreira and A. D. Andricopulo, Drug Discov. Today, 24, 1157 (2019), https://doi.org/10.1016/j.drudis.2019.03.01510.1016/j.drudis.2019.03.015 ↗
34. 34 A. Qureshi, G. Kaur and M. Kumar, Chem. Biol. Drug Des., 89, 74 (2016), https://doi.org/10.1111/cbdd.1283410.1111/cbdd.12834 ↗
35. 35 N. Cohen and S. W. Benson, Chem. Rev., 93, 2419 (1993), https://doi.org/10.1021/cr00023a00510.1021/cr00023a005 ↗
36. 36 E. J. Lien, Z. R. Guo and R. L. Li, J. Pharm. Sci., 71, 641 (1982), https://doi.org/10.1002/jps.260071061110.1002/jps.2600710611 ↗
37. 37 S. Saravanan and V. Balachandran, Spectrochim. Acta A, Mol. Biomol. Spectrosc., 120, 351 (2014), https://doi.org/10.1016/j.saa.2013.10.04210.1016/j.saa.2013.10.042 ↗
38. 38 R. G. Pearson, in Procs. The Natural Academy of Sciences of the United States of America, 1986, vol. 83, p. 8440, https://doi.org/10.1073/pnas.83.22.844010.1073/pnas.83.22.8440 ↗
39. 39 M. L. Amin, Drug Target Insights, 7, 27 (2013), https://doi.org/10.4137/DTI.S1251910.4137/DTI.S12519 ↗
40. 40 P. Politzer and J. S. Murray, Rev. Comput. Chem., 2, 273 (1991), https://doi.org/10.1002/wcms.132610.1002/wcms.1326 ↗
41. 41 P. Politzer and D. G. Truhlar (Eds.), “Reactivity, Structure, Scattering, and Energetics of Organic, Inorganic, and Biological Systems”, Springer, USA, 1981, https://www.springer.com/gp/book/978030640657710.1007/978-1-4757-9634-6 ↗
42. 42 H. Heinz and U. W. Suter, J. Phys. Chem., B, 108, 18341 (2004), https://doi.org/10.1021/jp048142t10.1021/jp048142t ↗
43. 43 K. C. Gross, P. G. Seybold and C. M. Hadad, Int. J. Quantum Chem., 90, 445 (2002), https://doi.org/10.1002/qua.1010810.1002/qua.10108 ↗
44. 44 R. S. Mulliken, Int. J. Chem. Phys., 23, 1833 (1955), https://doi.org/10.1063/1.174058810.1063/1.1740588 ↗
45. 45 T. Serseg, K. Benarous and M. Yousfi, Curr. Comput. Aided Drug Des., https://doi.org/10.2174/157340991666620042207544010.2174/1573409916666200422075440 ↗
46. 46 X. Liu and X. Z. Wang, J. Genet. Genom., 47, 119 (2020), https://doi.org/10.1016/j.jgg.2020.02.00110.1016/j.jgg.2020.02.001 ↗
47. 47 D. E. V. Pires, T. L.Blundell and D. B. Ascher, J. Med. Chem., 58, 4066 (2015), https://doi.org/10.1021/acs.jmedchem.5b0010410.1021/acs.jmedchem.5b00104 ↗
48. 48 D. E. Clark, Drug Discov. Today, 8, 927 (2003), https://doi.org/10.1016/s1359-6446(03)02827-710.1016/S1359-6446(03)02827-7 ↗
49. 49 S. Kok-Yong and L. Lawrence, in “Basic Pharmacokinetic Concepts and Some Clinical Applications”, edited by Tarek A. Ahmed, InTechOpen, London, UK, 2015, https://doi.org/10.5772/5992910.5772/59929 ↗
50. 50 C. A. Lipinski, F. Lombardo, B. W. Dominy and P. J. Feeney, Adv. Drug Deliv. Rev., 46, 3 (2001), https://doi.org/10.1016/s0169-409x(00)00129-010.1016/S0169-409X(00)00129-0 ↗