Generic placeholder image

Current Computer-Aided Drug Design

Author(s): Hanane Boucherit*, Abdelouahab Chikhi, Abderrahmane Bensegueni, Amina Merzoug and Jean-Michel Bolla

DOI: 10.2174/1573409915666190617165643

DownloadDownload PDF Flyer Cite As
The Research of New Inhibitors of Bacterial Methionine Aminopeptidase by Structure Based Virtual Screening Approach of ZINC DATABASE and In Vitro Validation

Page: [389 - 401] Pages: 13

  • * (Excluding Mailing and Handling)

Abstract

Background: The great emergence of multi-resistant bacterial strains and the low renewal of antibiotics molecules are leading human and veterinary medicine to certain therapeutic impasses. Therefore, there is an urgent need to find new therapeutic alternatives including new molecules in the current treatments of infectious diseases. Methionine aminopeptidase (MetAP) is a promising target for developing new antibiotics because it is essential for bacterial survival.

Objective: To screen for potential MetAP inhibitors by in silico virtual screening of the ZINC database and evaluate the best potential lead molecules by in vitro studies.

Methods: We have considered 200,000 compounds from the ZINC database for virtual screening with FlexX software to identify potential inhibitors against bacterial MetAP. Nine chemical compounds of the top hits predicted were purchased and evaluated in vitro. The antimicrobial activity of each inhibitor of MetAP was tested by the disc-diffusion assay against one Gram-positive (Staphylococcus aureus) and two Gram-negative (Escherichia coli & Pseudomonas aeruginosa) bacteria. Among the studied compounds, compounds ZINC04785369 and ZINC03307916 showed promising antibacterial activity. To further characterize their efficacy, the minimum inhibitory concentration was determined for each compound by the microdilution method which showed significant results.

Results: These results suggest compounds ZINC04785369 and ZINC03307916 as promising molecules for developing MetAP inhibitors.

Conclusion: Furthermore, they could therefore serve as lead molecules for further chemical modifications to obtain clinically useful antibacterial agents.

Keywords: Methionine aminopeptidase, antibacterial agents, zinc database, screening assistant, virtual screening, Flex X.

Graphical Abstract

[1]
van Duin, D.; Paterson, D.L. Multidrug-resistant bacteria in the community: trends and lessons learned. Infect. Dis. Clin. North Am., 2016, 30(2), 377-390.
[http://dx.doi.org/10.1016/j.idc.2016.02.004] [PMID: 27208764]
[2]
Jyoti, T.; Shrayanee, D.; Zeeshan, F.; Saif, H. Multidrug resistance: an emerging crisis. interdisciplinary perspectives on infectious diseases interdisciplinary perspectives on infectious diseases,, 2014, 1-7.
[3]
Colombo, A.L.; Júnior, J.N.A.; Guinea, J. Emerging multidrug-resistant Candida species. Curr. Opin. Infect. Dis., 2017, 30(6), 528-538.
[http://dx.doi.org/10.1097/QCO.0000000000000411] [PMID: 29095200]
[4]
Mitra, S.; Job, K.M.; Meng, L.; Bennett, B.; Holz, R.C. Analyzing the catalytic role of Asp97 in the methionine aminopeptidase from Escherichia coli. FEBS J., 2008, 275(24), 6248-6259.
[http://dx.doi.org/10.1111/j.1742-4658.2008.06749.x] [PMID: 19019076]
[5]
Olaleye, O.; Raghunand, T.R.; Bhat, S.; He, J.; Tyagi, S.; Lamichhane, G.; Gu, P.; Zhou, J.; Zhang, Y.; Grosset, J.; Bishai, W.R.; Liu, J.O. Methionine aminopeptidases from Mycobacterium tuberculosis as novel antimycobacterial targets. Chem. Biol., 2010, 17(1), 86-97.
[http://dx.doi.org/10.1016/j.chembiol.2009.12.014] [PMID: 20142044]
[6]
Giglione, C.; Boularot, A.; Meinnel, T. Protein N-terminal methionine excision. Cell. Mol. Life Sci., 2004, 61(12), 1455-1474.
[http://dx.doi.org/10.1007/s00018-004-3466-8] [PMID: 15197470]
[7]
Chang, S.Y.; McGary, E.C.; Chang, S. Methionine aminopeptidase gene of Escherichia coli is essential for cell growth. J. Bacteriol., 1989, 171(7), 4071-4072.
[http://dx.doi.org/10.1128/JB.171.7.4071-4072.1989] [PMID: 2544569]
[8]
Li, X.; Chang, Y.H. Amino-terminal protein processing in Saccharomyces cerevisiae is an essential function that requires two distinct methionine aminopeptidases. Proc. Natl. Acad. Sci. USA, 1995, 92(26), 12357-12361.
[http://dx.doi.org/10.1073/pnas.92.26.12357] [PMID: 8618900]
[9]
Miller, C.G.; Kukral, A.M.; Miller, J.L.; Movva, N.R. pepM is an essential gene in Salmonella typhimurium. J. Bacteriol., 1989, 171(9), 5215-5217.
[http://dx.doi.org/10.1128/JB.171.9.5215-5217.1989] [PMID: 2670909]
[10]
Irwin, J.J.; Raushel, F.M.; Shoichet, B.K. Virtual screening against metalloenzymes for inhibitors and substrates. Biochemistry, 2005, 44(37), 12316-12328.
[http://dx.doi.org/10.1021/bi050801k] [PMID: 16156645]
[11]
Kumar, V.; Krishna, S.; Siddiqi, M.I. Virtual screening strategies: recent advances in the identification and design of anti-cancer agents. Methods, 2015, 71, 64-70.
[http://dx.doi.org/10.1016/j.ymeth.2014.08.010] [PMID: 25171960]
[12]
Luciani, R.; Saxena, P.; Surade, S.; Santucci, M.; Venturelli, A.; Borsari, C.; Marverti, G.; Ponterini, G.; Ferrari, S.; Blundell, T.L.; Costi, M.P. Virtual screening and x-ray crystallography identify non-substrate analog inhibitors of flavin-dependent thymidylate synthase. J. Med. Chem., 2016, 59(19), 9269-9275.
[http://dx.doi.org/10.1021/acs.jmedchem.6b00977] [PMID: 27589670]
[13]
Xu, Y.; Tong, X.; Sun, P.; Bi, L.; Lin, K. Virtual screening and biological evaluation of biofilm inhibitors on dual targets in quorum sensing system. Future Med. Chem., 2017, 9(17), 1983-1994.
[http://dx.doi.org/10.4155/fmc-2017-0127] [PMID: 29076756]
[14]
Spyrakis, F.; Celenza, G.; Marcoccia, F.; Santucci, M.; Cross, S.; Bellio, P.; Cendron, L.; Perilli, M.; Tondi, D. Structure-Based virtual screening for the discovery of novel inhibitors of new delhi metallo-β-lactamase-1. ACS Med. Chem. Lett., 2017, 9(1), 45-50.
[http://dx.doi.org/10.1021/acsmedchemlett.7b00428] [PMID: 29348810]
[15]
Walters, W.P.; Stahl, M.T.; Murcko, M.A. A virtual screening: an overview. Drug Discov. Today, 1998, 3, 160-178.
[http://dx.doi.org/10.1016/S1359-6446(97)01163-X]
[16]
Shoichet, B.K. Virtual screening of chemical libraries. Nature, 2004, 432(7019), 862-865.
[http://dx.doi.org/10.1038/nature03197] [PMID: 15602552]
[17]
Ren, J.X.; Qian, H.L.; Huang, Y.X.; Zhu, N.Y.; Si, S.Y.; Xie, Y. Virtual screening for the identification of novel inhibitors of Mycobacterium tuberculosis cell wall synthesis: inhibitors targeting RmlB and RmlC. Comput. Biol. Med., 2015, 58, 110-117.
[http://dx.doi.org/10.1016/j.compbiomed.2014.12.020] [PMID: 25637777]
[18]
Gupta, P.K.P.; Sahu, B. Identification of natural compound inhibitors against. peptide deformylase using virtual screening and molecular docking techniques. Bull.Env. Pharmacol. Life Sci., 2015, 4, 70-80.
[19]
Khan, A.U.; Ali, A. Danishuddin; Srivastava, G.; Sharma, A. Potential inhibitors designed against NDM-1 type metallo-β-lactamases: an attempt to enhance efficacies of antibiotics against multi-drug-resistant bacteria. Sci. Rep., 2017, 7(1), 9207.
[http://dx.doi.org/10.1038/s41598-017-09588-1] [PMID: 28835636]
[20]
Mansuri, R.; Kumar, A.; Rana, S.; Panthi, B.; Ansari, M.Y.; Das, S.; Dikhit, M.R.; Sahoo, G.C.; Das, P. In vitro evaluation of antileishmanial activity of computationally screened compounds against ascorbate peroxidase to combat amphotericin b drug resistance. Antimicrob. Agents Chemother., 2017, 61(7), 1-25.
[http://dx.doi.org/10.1128/AAC.02429-16] [PMID: 28461317]
[21]
Cvijetić, I.N.; Verbić, T.Ž.; Ernesto de Resende, P.; Stapleton, P.; Gibbons, S.; Juranić, I.O.; Drakulić, B.J.; Zloh, M. Design, synthesis and biological evaluation of novel aryldiketo acids with enhanced antibacterial activity against multidrug resistant bacterial strains. Eur. J. Med. Chem., 2018, 143, 1474-1488.
[http://dx.doi.org/10.1016/j.ejmech.2017.10.045] [PMID: 29133041]
[22]
Fer, M.J.; Corre, L.L.; Pietrancosta, N.; Evrard-Todeschi, N.; Olatunji, S.; Bouhss, A.; Calvet-Vitale, S.; Gravier-Pelletier, C. Bacterial Transferase MraY, a Source of Inspiration towards New Antibiotics. Curr. Med. Chem., 2018, 25(42), 6013-6029.
[http://dx.doi.org/10.2174/0929867325666180330095154] [PMID: 29600753]
[23]
Hrast, M.; Jukič, M.; Patin, D.; Tod, J.; Dowson, C.G.; Roper, D.I.; Barreteau, H.; Gobec, S. In silico identification, synthesis and biological evaluation of novel tetrazole inhibitors of MurB. Chem. Biol. Drug Des., 2018, 91(6), 1101-1112.
[http://dx.doi.org/10.1111/cbdd.13172] [PMID: 29363274]
[24]
Foik, I.P.; Tuszynska, I.; Feder, M.; Purta, E.; Stefaniak, F.; Bujnicki, J.M. Novel inhibitors of the rRNA ErmC′ methyltransferase to block resistance to macrolides, lincosamides, streptogramine B antibiotics. Eur. J. Med. Chem., 2018, 146, 60-67.
[http://dx.doi.org/10.1016/j.ejmech.2017.11.032] [PMID: 29396363]
[25]
Sin, N.; Meng, L.; Wang, M.Q.; Wen, J.J.; Bornmann, W.G.; Crews, C.M. The anti-angiogenic agent fumagillin covalently binds and inhibits the methionine aminopeptidase, MetAP-2. Proc. Natl. Acad. Sci. USA, 1997, 94(12), 6099-6103.
[http://dx.doi.org/10.1073/pnas.94.12.6099] [PMID: 9177176]
[26]
Vaughan, M.D.; Sampson, P.B.; Honek, J.F. Methionine in and out of proteins: targets for drug design. Curr. Med. Chem., 2002, 9(3), 385-409.
[http://dx.doi.org/10.2174/0929867023371102] [PMID: 11860363]
[27]
Ye, Q.Z.; Xie, S.X.; Huang, M.; Huang, W.J.; Lu, J.P.; Ma, Z.Q. Metalloform-selective inhibitors of escherichia coli methionine aminopeptidase and X-ray structure of a Mn(II)-form enzyme complexed with an inhibitor. J. Am. Chem. Soc., 2004, 126(43), 13940-13941.
[http://dx.doi.org/10.1021/ja045864p] [PMID: 15506752]
[28]
Douangamath, A.; Dale, G.E.; D’Arcy, A.; Almstetter, M.; Eckl, R.; Frutos-Hoener, A.; Henkel, B.; Illgen, K.; Nerdinger, S.; Schulz, H.; Mac Sweeney, A.; Thormann, M.; Treml, A.; Pierau, S.; Wadman, S.; Oefner, C. Crystal structures of Staphylococcus aureus methionine aminopeptidase complexed with keto heterocycle and aminoketone inhibitors reveal the formation of a tetrahedral intermediate. J. Med. Chem., 2004, 47(6), 1325-1328.
[http://dx.doi.org/10.1021/jm034188j] [PMID: 14998322]
[29]
Lu, J.P.; Ye, Q. Z. Methionine excision captured by the structures of a methionine aminopeptidase, 2013.
[30]
Hubbard, R.E. 3D structure and the drug-discovery process. Mol. Biosyst., 2005, 1, 391-406.
[31]
Irwin, J.J.; Shoichet, B.K. ZINC-a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model., 2005, 45(1), 177-182.
[http://dx.doi.org/10.1021/ci049714+] [PMID: 15667143]
[32]
Monge, A. Création et utilisation de chimiothèques optimisées pour la recherche “ in silico ” de nouveaux composés bioactifs, PhD thesis, University of Orleans: France. 2007.
[33]
Guilloux, V.L.; Arrault, A.; Colliandre, L.; Bourg, S.; Vayer, P.; Morin-Allory, L. Mining collections of compounds with Screening Assistant 2. J. Cheminform., 2012, 4(1), 20.
[http://dx.doi.org/10.1186/1758-2946-4-20] [PMID: 23327565]
[34]
Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Assessing energy functions for flexible docking. J. Comput. Chem., 1998, 19, 1612-1622.
[http://dx.doi.org/10.1002/(SICI)1096-987X(19981115)19:14<1612:AID-JCC7>3.0.CO;2-M]
[35]
Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev., 2001, 46(1-3), 3-26.
[http://dx.doi.org/10.1016/S0169-409X(00)00129-0] [PMID: 11259830]
[36]
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]
[37]
Chikhi, A. Calculs et modélisations des interactions peptide déformylase substances antibactériennes à l’aide de techniques de ‘’docking’’ (arrimage) moléculaire, PhD thesis, University of Mentouri Constantine: Algeria. 2007.
[38]
Spencer, R.W. Diversity Analysis in high throughput screening. J. Biomol. Screen., 1997, 2, 69-70.
[http://dx.doi.org/10.1177/108705719700200203]
[39]
Natarajan, R.; Nirdosh, I.; Basak, S.C.; Mills, D.R. QSAR modeling of flotation collectors using principal components extracted from topological indices. J. Chem. Inf. Comput. Sci., 2002, 42(6), 1425-1430.
[http://dx.doi.org/10.1021/ci025513z] [PMID: 12444740]
[40]
Xue, L.; Godden, J.; Gao, H.; Bajorath, J. Identification of a preferred set of molecular descriptors for compound classification based on principal component analysis. J. Chem. Inf. Comput. Sci., 1999, 39, 699-704.
[http://dx.doi.org/10.1021/ci980231d]
[41]
Rarey, M.; Wefing, S.; Lengauer, T. Placement of medium-sized molecular fragments into active sites of proteins. J. Comput. Aided Mol. Des., 1996, 10(1), 41-54.
[http://dx.doi.org/10.1007/BF00124464] [PMID: 8786414]
[42]
Böhm, H.J. The computer program LUDI: a new method for the de novo design of enzyme inhibitors. J. Comput. Aided Mol. Des., 1992, 6(1), 61-78.
[http://dx.doi.org/10.1007/BF00124387] [PMID: 1583540]
[43]
Bessadok, M.A. La multiplicité de transport de la P-glycoprotéine: Etudes de modélisation comparative et de docking au sein de la famille des protéines ABC, Ph D Thesis, Pierre and Marie Curie University: France. 2012.
[44]
Huang, S.Y.; Zou, X. Advances and challenges in protein-ligand docking. Int. J. Mol. Sci., 2010, 11(8), 3016-3034.
[http://dx.doi.org/10.3390/ijms11083016] [PMID: 21152288]
[45]
Comité de l’antibiogramme (CA-SFM). Société Française de Microbiologie 2017.
[46]
Pommier, Y.; Leo, E.; Zhang, H.; Marchand, C. DNA topoisomerases and their poisoning by anticancer and antibacterial drugs. Chem. Biol., 2010, 17(5), 421-433.
[http://dx.doi.org/10.1016/j.chembiol.2010.04.012] [PMID: 20534341]
[47]
Vogelman, B.; Craig, W.A. Kinetics of antimicrobial activity. J. Pediatr., 1986, 108(5 Pt 2), 835-840.
[http://dx.doi.org/10.1016/S0022-3476(86)80754-5] [PMID: 3701535]
[48]
Standardisation de l’antibiogramme à l’échelle nationale (médecine humaine et vétérinaire) 2011.http://www.sante.dz/aarn
[49]
Archambaud, M. Les Antibiotiques. Mode d’action; Mécanismes de Résistance; Laboratoire Bactériologie-Hygiène CHU Rangueil Toulouse, 2009.
[50]
Mérens, A.; Delacour, H.; Plésiat, P.; Cavallo, G.D.; Jeanno, K. Pseudomonas aeruginosa et résistance aux antibiotiques Pseudomonas aeruginosa and antibiotic resistance. Revue Francophone des Laboratoires., 2011, 41(435), 49-62.
[http://dx.doi.org/10.1016/S1773-035X(11)71102-9]
[51]
Vaara, M. Agents that increase the permeability of the outer membrane. Microbiol. Rev., 1992, 56(3), 395-411.
[http://dx.doi.org/10.1128/MMBR.56.3.395-411.1992] [PMID: 1406489]
[52]
Masi, M.; Réfregiers, M.; Pos, K.M.; Pagès, J.M. Mechanisms of envelope permeability and antibiotic influx and efflux in Gram-negative bacteria. Nat. Microbiol., 2017, 2(3), 17001.
[http://dx.doi.org/10.1038/nmicrobiol.2017.1] [PMID: 28224989]
[53]
Domalaon, R.; Idowu, T.; Zhanel, G.G.; Schweizer, F. Antibiotic hybrids: the next generation of agents and adjuvants against gram-negative pathogens? Clin. Microbiol. Rev., 2018, 31(2), 1-45.
[http://dx.doi.org/10.1128/CMR.00077-17] [PMID: 29540434]
[54]
Jantová, S.; Stankovský, S.; Špirková, K. In vitro antibacterial activity of ten series of substituted quinazolines. Biologia (Bratisl.), 2004, 59(6), 741-752.
[55]
Khodarahmi, G.; Jafari, E.; Hakimelahi, G.; Abedi, D.; Rahmani Khajouei, M.; Hassanzadeh, F. Synthesis of some new quinazolinone derivatives and evaluation of their antimicrobial activities. Iran. J. Pharm. Res., 2012, 11(3), 789-797.
[PMID: 24250506]
[56]
F., Zayed M.; H Hassan, M. Synthesis and biological evaluation studies of novel quinazolinone derivatives as antibacterial and anti-inflammatory agents. Saudi Pharm. J., 2014, 22(2), 157-162.
[http://dx.doi.org/10.1016/j.jsps.2013.03.004] [PMID: 24648828]
[57]
Mishra, R.C.; Kumari, R.; Yadav, S.; Yadav, J.P. Target based virtual screening of new leads inhibitor against bacterial cell division protein ftsz for the discovery of antibacterial agents. Med. Chem., 2020, 16(2), 169-175.
[http://dx.doi.org/10.2174/1573406415666190206233448] [PMID: 30727908]
[58]
Nastasă, C.; Vodnar, D.C.; Ionuţ, I.; Stana, A.; Benedec, D.; Tamaian, R.; Oniga, O.; Tiperciuc, B. Antibacterial evaluation and virtual screening of new thiazolyl-triazole schiff bases as potential dna-gyrase inhibitors. Int. J. Mol. Sci., 2018, 19(1), 1-18.
[http://dx.doi.org/10.3390/ijms19010222] [PMID: 29324679]
[59]
Helgren, T.R.; Chen, C.; Wangtrakuldee, P.; Edwards, T.E.; Staker, B.L.; Abendroth, J.; Sankaran, B.; Housley, N.A.; Myler, P.J.; Audia, J.P.; Horn, J.R.; Hagen, T.J. Rickettsia prowazekii methionine aminopeptidase as a promising target for the development of antibacterial agents. Bioorg. Med. Chem., 2017, 25(3), 813-824.
[http://dx.doi.org/10.1016/j.bmc.2016.11.013] [PMID: 28089350]
[60]
Kokkonen, P.; Kokkola, T.; Suuronen, T.; Poso, A.; Jarho, E.; Lahtela-Kakkonen, M. Virtual screening approach of sirtuin inhibitors results in two new scaffolds. Eur. J. Pharm. Sci., 2015, 76, 27-32.
[http://dx.doi.org/10.1016/j.ejps.2015.04.025] [PMID: 25936698]
[61]
Petersen, G.O.; Saxena, S.; Renuka, J.; Soni, V.; Yogeeswari, P.; Santos, D.S.; Bizarro, C.V.; Sriram, D. Structure-based virtual screening as a tool for the identification of novel inhibitors against Mycobacterium tuberculosis 3-dehydroquinate dehydratase. J. Mol. Graph. Model., 2015, 60, 124-131.
[http://dx.doi.org/10.1016/j.jmgm.2015.05.001] [PMID: 26043661]
[62]
Samal, H.B.; Das, J.K.; Mahapatra, R.K.; Suar, M. Molecular modeling, simulation and virtual screening of MurD ligase protein from Salmonella typhimurium LT2. J. Pharmacol. Toxicol. Methods, 2015, 73, 34-41.
[http://dx.doi.org/10.1016/j.vascn.2015.03.005] [PMID: 25841669]
[63]
Stahl, M. Structure-based library design.Virtual Screening for Bioactive Molecules; Wiley-VCH, 2000, pp. 229-264.
[http://dx.doi.org/10.1002/9783527613083.ch11]
[64]
Schneider, G.; Böhm, H-J. Virtual screening and fast automated docking methods. Drug Discov. Today, 2002, 7(1), 64-70.
[http://dx.doi.org/10.1016/S1359-6446(01)02091-8] [PMID: 11790605]