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Current Pharmaceutical Design

Author(s): Atul Kumar Singh, Kumari Sunita Prajapati and Shashank Kumar*

DOI: 10.2174/1381612828666220922100556

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Acarbose Potentially Binds to the Type I Peptide Deformylase Catalytic Site and Inhibits Bacterial Growth: An In Silico and In Vitro Study

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Abstract

Background: In bacteria, peptide deformylase (PDF), a metalloenzyme, removes N-formyl methionine from a nascent protein, which is a critical step in the protein maturation process. The enzyme is ubiquitously present in bacteria and possesses therapeutic target potential. Acarbose, an FDA-approved antidiabetic drug, is an alpha-glucosidase inhibitor of microbial origin. Clinical studies indicate that acarbose administration in humans can alter gut microbiota. As per the best of our knowledge, the antibacterial potential of acarbose has not been reported.

Objective: The present study aimed to check the binding ability of acarbose to the catalytic site of E. coli PDF and assess its in vitro antibacterial activity.

Methods: Molecular docking, molecular dynamic (MD) simulation, and MM-PBSA experiments were performed to study the binding potential of the catalytic site, and a disc diffusion assay was also employed to assess the antibacterial potential of acarbose.

Results: Acarbose was found to form a hydrogen bond and interact with the metal ion present at the catalytic site. The test compound showed a better docking score in comparison to the standard inhibitor of PDF. MD simulation results showed energetically stable acarbose-PDF complex formation in terms of RMSD, RMSF, Rg, SASA, and hydrogen bond formation throughout the simulation period compared to the actinonin-PDF complex. Furthermore, MM-PBSA calculations showed better binding free energy (ΔG) of acarbose PDF than the actinonin-PDF complex. Moreover, acarbose showed in vitro antibacterial activity.

Conclusion: Acarbose forms conformational and thermodynamically stable interaction with the E. coli peptide deformylase catalytic site. Results of the present work necessitate in-depth antimicrobial potential studies on the effect of acarbose on drug resistance and nonresistant bacteria.

Keywords: Natural compound, anti-bacterial, acarbose, FDA-approved, computational study, in vitro, drug resistance.

[1]
Gao J, Liang L, Zhu Y, Qiu S, Wang T, Zhang L. Ligand and structure-based approaches for the identification of peptide deformylase inhibitors as antibacterial drugs. Int J Mol Sci 2016; 17(7): 1141.
[http://dx.doi.org/10.3390/ijms17071141] [PMID: 27428963]
[2]
Fair RJ, Tor Y. Antibiotics and bacterial resistance in the 21st century. Perspect Medicin Chem 2014; 6: PMC.S14459.
[http://dx.doi.org/10.4137/PMC.S1445] [PMID: 25232278]
[3]
Prestinaci F, Pezzotti P, Pantosti A. Antimicrobial resistance: A global multifaceted phenomenon. Pathog Glob Health 2015; 109(7): 309-18.
[http://dx.doi.org/10.1179/2047773215Y.0000000030] [PMID: 26343252]
[4]
C Reygaert W. An overview of the antimicrobial resistance mechanisms of bacteria. AIMS Microbiol 2018; 4(3): 482-501.
[http://dx.doi.org/10.3934/microbiol.2018.3.482] [PMID: 31294229]
[5]
Rakhi M, Shankar MP, Rupa M, Avijit M, Anurag C. Computational docking technique for drug discovery: A review. Res J Pharm Technol 2021; 14: 5558-62.
[6]
Singh AK, Shuaib M, Kushwaha PP, Prajapati KS, Sharma R, Kumar S. In silico updates on lead identification for obesity and cancer. In: Obesity and Cancer. Singapore: Springer 2021; pp. 257-77.
[http://dx.doi.org/10.1007/978-981-16-1846-8_13]
[7]
Ogodo AC, Narayana MS, Vardhan PS, et al. Principles of applied microbiology and biotechnology: Technique for the screening of antimicrobial herbs. In: Egbuna C, Mishra AP, Goyal MR, Eds. Preparation of Phytopharmaceuticals for the Management of Disorders. Academic Press: Washington, DC 2021; pp. 185-214.
[8]
Laursen BS, Sørensen HP, Mortensen KK, Sperling-Petersen HU. Initiation of protein synthesis in bacteria. Microbiol Mol Biol Rev 2005; 69(1): 101-23.
[http://dx.doi.org/10.1128/MMBR.69.1.101-123.2005] [PMID: 15755955]
[9]
Singh AK, Prajapati KS, Shuaib M, Kushwaha PP, Kumar S. Microbial proteins: A potential source of protein. In: Egbuna C, Tupas GD, Eds. Functional foods and nutraceuticals. Springer: NY 2020; pp. 139-47.
[http://dx.doi.org/10.1007/978-3-030-42319-3_8]
[10]
Giglione C, Serero A, Pierre M, Boisson B, Meinnel T. Identification of eukaryotic peptide deformylases reveals universality of N-terminal protein processing mechanisms. EMBO J 2000; 19(21): 5916-29.
[http://dx.doi.org/10.1093/emboj/19.21.5916] [PMID: 11060042]
[11]
Yin L, Ma H, Nakayasu ES, Payne SH, Morris DR, Harwood CS. Bacterial longevity requires protein synthesis and a stringent response. MBio 2019; 10(5): e02189-19.
[http://dx.doi.org/10.1128/mBio.02189-19] [PMID: 31615958]
[12]
Sangshetti J, Khan FA, Shinde D. Peptide deformylase: A new target in antibacterial, antimalarial and anticancer drug discovery. Curr Med Chem 2014; 22(2): 214-36.
[http://dx.doi.org/10.2174/0929867321666140826115734] [PMID: 25174923]
[13]
Guilloteau JP, Mathieu M, Giglione C, et al. The crystal structures of four peptide deformylases bound to the antibiotic actinonin reveal two distinct types: A platform for the structure-based design of antibacterial agents. J Mol Biol 2002; 320(5): 951-62.
[http://dx.doi.org/10.1016/S0022-2836(02)00549-1] [PMID: 12126617]
[14]
Guay DR. Drug forecast - the peptide deformylase inhibitors as antibacterial agents. Ther Clin Risk Manag 2007; 3(4): 513-25.
[PMID: 18472972]
[15]
Lee MD, Antczak C, Li Y, Sirotnak FM, Bornmann WG, Scheinberg DA. A new human peptide deformylase inhibitable by actinonin. Biochem Biophys Res Commun 2003; 312(2): 309-15.
[http://dx.doi.org/10.1016/j.bbrc.2003.10.123] [PMID: 14637138]
[16]
DiNicolantonio JJ, Bhutani J, O’Keefe JH. Acarbose: Safe and effective for lowering postprandial hyperglycaemia and improving cardiovascular outcomes. Open Heart 2015; 2(1): e000327.
[http://dx.doi.org/10.1136/openhrt-2015-000327] [PMID: 26512331]
[17]
Zhang M, Feng R, Yang M, et al. Effects of metformin, acarbose, and sitagliptin monotherapy on gut microbiota in Zucker diabetic fatty rats. BMJ Open Diabetes Res Care 2019; 7(1): e000717.
[http://dx.doi.org/10.1136/bmjdrc-2019-000717] [PMID: 31641523]
[18]
Baxter NT, Lesniak NA, Sinani H, Schloss PD, Koropatkin NM. The glucoamylase inhibitor acarbose has a diet-dependent and reversible effect on the murine gut microbiome. MSphere 2019; 4: 1-12.
[19]
Hanefeld M. Cardiovascular benefits and safety profile of acarbose therapy in prediabetes and established type 2 diabetes. Cardiovasc Diabetol 2007; 6(1): 20.
[http://dx.doi.org/10.1186/1475-2840-6-20] [PMID: 17697384]
[20]
Wishart DS, Feunang YD, Guo AC, et al. DrugBank 5.0: A major update to the DrugBank database for 2018. Nucleic Acids Res 2018; 46(D1): D1074-82.
[http://dx.doi.org/10.1093/nar/gkx1037] [PMID: 29126136]
[21]
Zhou Y, Zhang Y, Lian X, et al. Therapeutic target database update 2022: Facilitating drug discovery with enriched comparative data of targeted agents. Nucleic Acids Res 2022; 50(D1): D1398-407.
[http://dx.doi.org/10.1093/nar/gkab953] [PMID: 34718717]
[22]
Kushwaha PP, Prajapati SK, Pothabathula SV, et al. Prenylated flavonoids as a promising drug discovery candidate: A pharmacological update. In: Egbuna C, Kumar S, Ifemeje JC, Ezzat SM, Kaliyaperumal S, Eds. Phytochemicals as Lead Compounds for New Drug Discovery. Elsevier: Amsterdam 2020; pp. 347-55.
[http://dx.doi.org/10.1016/B978-0-12-817890-4.00023-8]
[23]
Ezebuo FC, Kushwaha PP, Singh AK, Kumar S, Singh P. In-silico methods of drug design: Molecular simulations and free energy calculations. In: Kumar S, Egbuna C, Eds. Phytochemistry: An in-silico and in-vitro Update. Singapor: Springer 2019; pp. 521-33.
[http://dx.doi.org/10.1007/978-981-13-6920-9_28]
[24]
Kushwaha PP, Malik R, Rawat SG, Singh AK, Kumar S. Drug development: In silico, in vivo and system biology approach. In: Kumar S, Ed. Clinical Biochemistry and Drug Development. Apple Academic Press: Washington, DC 2020; pp. 145-60.
[http://dx.doi.org/10.1201/9780367821470-11]
[25]
Santos LHS, Ferreira RS, Caffarena ER. Integrating molecular docking and molecular dynamics simulations. Methods Mol Biol 2019; 2053: 13-34.
[http://dx.doi.org/10.1007/978-1-4939-9752-7_2] [PMID: 31452096]
[26]
Berman HM, Westbrook J, Feng Z, et al. The protein data bank. Nucleic Acids Res 2000; 28(1): 235-42.
[http://dx.doi.org/10.1093/nar/28.1.235] [PMID: 10592235]
[27]
Kim S, Chen J, Cheng T, et al. PubChem in 2021: New data content and improved web interfaces. Nucleic Acids Res 2021; 49(D1): D1388-95.
[http://dx.doi.org/10.1093/nar/gkaa971] [PMID: 33151290]
[28]
Shivakumar D, Williams J, Wu Y, Damm W, Shelley J, Sherman W. Prediction of absolute solvation free energies using molecular dynamics free energy perturbation and the opls force field. J Chem Theory Comput 2010; 6(5): 1509-19.
[http://dx.doi.org/10.1021/ct900587b] [PMID: 26615687]
[29]
Senapati S, Kumar S, Singh AK, Banerjee P, Bhagavatula S. Assessment of risk conferred by coding and regulatory variations of TMPRSS2 and CD26 in susceptibility to SARS-CoV-2 infection in human. J Genet 2020; 99(1): 53.
[http://dx.doi.org/10.1007/s12041-020-01217-7] [PMID: 32661206]
[30]
Kumar S, Singh AK, Kushwaha PP, et al. Identification of compounds from curcuma longa with in silico binding potential against SARS-CoV-2 and human host proteins involve in virus entry and pathogenesis. Indian J Pharm Sci 2021; 83: 1181-95.
[31]
Rajkumar M, Maalmarugan J, Flora G, et al. Growth, characterizations, and the structural elucidation of diethyl-2-(3-oxoiso-1,3-dihydrobenzofuran-1-ylidene)malonate crystalline specimen for dielectric and electronic filters, thermal, optical, mechanical, and biomedical applications using conventional experimental and theoretical practices. J Mater Sci Mater Electron 2021; 32(18): 22822-39.
[http://dx.doi.org/10.1007/s10854-021-06761-1]
[32]
El Khatabi K, Aanouz I, El-MERNISSI R, et al. Integrated 3D-QSAR, molecular docking, and molecular dynamics simulation studies on 1,2,3-triazole based derivatives for designing new acetylcholinesterase inhibitors. Turk J Chem 2021; 45(3): 647-60.
[http://dx.doi.org/10.3906/kim-2010-34] [PMID: 34385858]
[33]
Kushwaha PP, Maurya SK, Singh A, et al. Bulbine frutescens phytochemicals as novel ABC-transporter inhibitor: A molecular docking and molecular dynamics simulation study. J Cancer Metastasis Treat 2021; 7: 1-13.
[34]
Abraham MJ, Murtola T, Schulz R, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015; 1-2: 19-25.
[http://dx.doi.org/10.1016/j.softx.2015.06.001]
[35]
Schüttelkopf AW, van Aalten DMF. PRODRG: A tool for high-throughput crystallography of protein–ligand complexes. Acta Crystallogr D Biol Crystallogr 2004; 60(8): 1355-63.
[http://dx.doi.org/10.1107/S0907444904011679] [PMID: 15272157]
[36]
Berendsen HJC, Postma JPM, van Gunsteren WF, DiNola A, Haak JR. Molecular dynamics with coupling to an external bath. J Chem Phys 1984; 81(8): 3684-90.
[http://dx.doi.org/10.1063/1.448118]
[37]
Parrinello M, Rahman A. Polymorphic transitions in single crystals: A new molecular dynamics method. J Appl Phys 1981; 52(12): 7182-90.
[http://dx.doi.org/10.1063/1.328693]
[38]
Hess B, Bekker H, Berendsen HJC, Fraaije JGEM. LINCS: A linear constraint solver for molecular simulations. J Comput Chem 1997; 18(12): 1463-72.
[http://dx.doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463:AID-JCC4>3.0.CO;2-H]
[39]
DeLano WL. PyMOL: An open-source molecular graphics tool. CCP4 Newsletter on protein crystallography 2002; 40: 82-92. Available from: http://legacy.ccp4.ac.uk/newsletters/newsletter40.pdf
[40]
Humphrey W, Dalke A, Schulten K. VMD: Visual molecular dynamics. J Mol Graph 1996; 14(1): 33-8. 27-28.
[http://dx.doi.org/10.1016/0263-7855(96)00018-5] [PMID: 8744570]
[41]
Wolf A, Kirschner KN. Principal component and clustering analysis on molecular dynamics data of the ribosomal L11•23S subdomain. J Mol Model 2013; 19(2): 539-49.
[http://dx.doi.org/10.1007/s00894-012-1563-4] [PMID: 22961589]
[42]
Kushwaha PP, Singh AK, Prajapati KS, Shuaib M, Gupta S, Kumar S. Phytochemicals present in Indian ginseng possess potential to inhibit SARS-CoV-2 virulence: A molecular docking and MD simulation study. Microb Pathog 2021; 157: 104954.
[http://dx.doi.org/10.1016/j.micpath.2021.104954] [PMID: 34033891]
[43]
Singh AK, Kushwaha PP, Prajapati KS, Shuaib M, Gupta S, Kumar S. Identification of FDA approved drugs and nucleoside analogues as potential SARS-CoV-2 A1pp domain inhibitor: An in silico study. Comput Biol Med 2021; 130: 104185.
[http://dx.doi.org/10.1016/j.compbiomed.2020.104185] [PMID: 33352458]
[44]
Kushwaha PP, Singh AK, Bansal T, et al. Identification of natural inhibitors against SARS-CoV-2 drugable targets using molecular docking, molecular dynamics simulation, and MM-PBSA Approach. Front Cell Infect Microbiol 2021; 11: 730288.
[http://dx.doi.org/10.3389/fcimb.2021.730288] [PMID: 34458164]
[45]
Gupta S, Singh AK, Kushwaha PP, et al. Identification of potential natural inhibitors of SARS-CoV2 main protease by molecular docking and simulation studies. J Biomol Struct Dyn 2021; 39(12): 4334-45.
[http://dx.doi.org/10.1080/07391102.2020.1776157] [PMID: 32476576]
[46]
Kumari R, Kumar R, Lynn A. g_mmpbsa-A GROMACS tool for high-throughput MM-PBSA calculations. J Chem Inf Model 2014; 54(7): 1951-62.
[http://dx.doi.org/10.1021/ci500020m] [PMID: 24850022]
[47]
Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA. Electrostatics of nanosystems: Application to microtubules and the ribosome. Proc Natl Acad Sci USA 2001; 98(18): 10037-41.
[http://dx.doi.org/10.1073/pnas.181342398] [PMID: 11517324]
[48]
Bauer AW, Kirby WMM, Sherris JC, Turck M. Antibiotic susceptibility testing by a standardized single disk method. Am J Clin Pathol 1966; 45(4_ts): 493-6.
[http://dx.doi.org/10.1093/ajcp/45.4_ts.493] [PMID: 5325707]
[49]
Banjare L, Singh Y, Verma SK, et al. Multifaceted 3D-QSAR analysis for the identification of pharmacophoric features of biphenyl analogues as aromatase inhibitors. J Biomol Struct Dyn 2021; 1-20.
[http://dx.doi.org/10.1080/07391102.2021.2019122] [PMID: 34963408]
[50]
Joshi T, Joshi T, Sharma P, Chandra S, Pande V. Molecular docking and molecular dynamics simulation approach to screen natural compounds for inhibition of Xanthomonas oryzae pv. Oryzae by targeting peptide deformylase. J Biomol Struct Dyn 2021; 39: 823-40.
[51]
Joshi T, Pandey SC, Maiti P, et al. Antimicrobial activity of methanolic extracts of Vernonia cinerea against Xanthomonas oryzae and identification of their compounds using in silico techniques. PLoS One 2021; 16: e0252759.
[http://dx.doi.org/10.1371/journal.pone.0252759] [PMID: 34125862]
[52]
Mishra A, Sharma AK, Kumar S, Saxena AK, Pandey AK. Bauhinia variegata leaf extracts exhibit considerable antibacterial, antioxidant, and anticancer activities. BioMed Res Intern 2013; pp. 1-10.
[53]
Kumar S, Kumar R, Dwivedi A, Pandey AK. In vitro antioxidant, antibacterial, and cytotoxic activity and in vivo effect of Syngonium podophyllum and Eichhornia crassipes leaf extracts on isoniazid induced oxidative stress and hepatic markers. In: BioMed Res Intern. 2014; pp. 1-11.
[54]
Kumar S, Pandey S, Pandey AK. In vitro antibacterial, antioxidant, and cytotoxic activities of Parthenium hysterophorus and characterization of extracts by LC-MS analysis. BioMed Res Intern 2014; pp. 1-11.