Generic placeholder image

Letters in Drug Design & Discovery

Editor-in-Chief

ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Research Article

In silico Identification of Putative Drug Targets in Mycobacterium ulcerans Virulence Proteins

Author(s): Taruna Mohinani, Aditya Saxena*, Shoor Vir Singh and Amita Pathak

Volume 20, Issue 12, 2023

Published on: 13 December, 2022

Page: [2003 - 2017] Pages: 15

DOI: 10.2174/1570180820666221124122659

Price: $65

Abstract

Background: Buruli ulcer (BU), caused by Mycobacterium ulcerans is a neglected tropical disease characterized by necrotic skin lesions. Antibiotic therapy and excision of the lesions are the treatments for this chronic disease. During the management of the disease, the emergence of drug resistance in these bacilli is a major challenge. Therefore, there is a need to identify new drug targets against this important pathogen.

Objective: The study aimed to investigate novel drug targets exploring virulence factors of M. ulcerans by in silico analysis.

Methods: Virulence proteins encoded by the chromosome of Mycobacterium ulcerans strain Agy99 were retrieved and analyzed for their cellular localization, human non-homology and essentiality. Further, proteins were analyzed for their physio-chemical characterization, drug resistance analysis, protein interaction analysis, metabolic pathway prediction, and druggability prediction by various databases and online software to find their suitability as drug targets. The structure of the predicted drug targets was also modeled and validated. Among three predicted drug targets, MUL_4536 was subjected to molecular docking with some known inhibitor compounds also. Receptor-ligand complex with the highest binding energy was selected for molecular dynamic (MD) simulation to determine the structural stability of the complex.

Results: Three virulence proteins MUL_4536, MUL_3640, and MUL_2329 encoding enzymes iso-citrate lyase, lysine-N-oxygenase, pup-protein ligase, respectively were predicted as a drug target against M. ulcerans. Isocitrate lyase has been identified as a potential drug target in many other mycobacterial and non-mycobacterial diseases. Lysine-N-oxygenase is the enzyme of mycobactin biosynthesis pathway and pup-protein ligase is associated with the pup-proteasome system. Proteins of these pathways have been studied as attractive drug targets in previous research works, which further support our predictions.

Conclusion: Our computational analysis predicted new drug targets, which could be used to design drugs against M. ulcerans. However, these predicted proteins require further experimental validation for their potential use as drug targets.

Keywords: Mycobacterium ulcerans, virulence protein, drug target, in silico analysis, molecular dynamic (MD).

Graphical Abstract
[1]
Johnson, P.D.R.; Stinear, T.; Small, P.L.C.; Pluschke, G.; Merritt, R.W.; Portaels, F.; Huygen, K.; Hayman, J.A.; Asiedu, K. Buruli ulcer (M. ulcerans infection): New insights, new hope for disease control. PLoS Med., 2005, 2(4), e108.
[http://dx.doi.org/10.1371/journal.pmed.0020108] [PMID: 15839744]
[2]
Simpson, H.; Deribe, K.; Tabah, E.N.; Peters, A.; Maman, I.; Frimpong, M.; Ampadu, E.; Phillips, R.; Saunderson, P.; Pullan, R.L.; Cano, J. Mapping the global distribution of Buruli ulcer: A systematic review with evidence consensus. Lancet Glob. Health, 2019, 7(7), e912-e922.
[http://dx.doi.org/10.1016/S2214-109X(19)30171-8] [PMID: 31200890]
[3]
Amofah, G.; Bonsu, F.; Tetteh, C.; Okrah, J.; Asamoa, K.; Asiedu, K.; Addy, J. Buruli ulcer in Ghana: Results of a national case search. Emerg. Infect. Dis., 2002, 8(2), 167-170.
[http://dx.doi.org/10.3201/eid0802.010119] [PMID: 11897068]
[4]
Loftus, M.J.; Tay, E.L.; Globan, M.; Lavender, C.J.; Crouch, S.R.; Johnson, P.D.R.; Fyfe, J.A.M. Epidemiology of Buruli ulcer infections, Victoria, Australia, 2011-2016. Emerg. Infect. Dis., 2018, 24(11), 1988-1997.
[http://dx.doi.org/10.3201/eid2411.171593] [PMID: 30334704]
[5]
Omansen, T.F.; Erbowor-Becksen, A.; Yotsu, R.; van der Werf, T.S.; Tiendrebeogo, A.; Grout, L.; Asiedu, K. Global epidemiology of buruli ulcer, 2010–2017, and analysis of 2014 WHO programmatic targets. Emerg. Infect. Dis., 2019, 25(12), 2183-2190.
[http://dx.doi.org/10.3201/eid2512.190427] [PMID: 31742506]
[6]
Vincent, Q.B.; Ardant, M.F.; Adeye, A.; Goundote, A.; Saint-André, J.P.; Cottin, J.; Kempf, M.; Agossadou, D.; Johnson, C.; Abel, L.; Marsollier, L.; Chauty, A.; Alcaïs, A. Clinical epidemiology of laboratory-confirmed Buruli ulcer in Benin: A cohort study. Lancet Glob. Health, 2014, 2(7), e422-e430.
[http://dx.doi.org/10.1016/S2214-109X(14)70223-2] [PMID: 25103396]
[7]
Tai, A.Y.C.; Athan, E.; Friedman, N.D.; Hughes, A.; Walton, A.; O’Brien, D.P. Increased severity and spread of Mycobacterium ulcerans, southeastern Australia. Emerg. Infect. Dis., 2018, 24(1), 58-64.
[http://dx.doi.org/10.3201/eid2401.171070] [PMID: 28980523]
[8]
Pluschke, G.; Röltgen, K. Epidemiology and disease burden of Buruli ulcer: A review. Res. Rep. Trop. Med., 2015, 2015(6), 59-73.
[http://dx.doi.org/10.2147/RRTM.S62026]
[9]
Combe, M.; Velvin, C.J.; Morris, A. Global and local environmental changes as drivers of Buruli ulcer emergence. Emerg. Microbes Infect., 2017, 6(1), 1-11.
[10]
Doig, K.D.; Holt, K.E.; Fyfe, J.A.M.; Lavender, C.J.; Eddyani, M.; Portaels, F.; Yeboah-Manu, D.; Pluschke, G.; Seemann, T.; Stinear, T.P. On the origin of Mycobacterium ulcerans, the causative agent of Buruli ulcer. BMC Genomics, 2012, 13(1), 258.
[http://dx.doi.org/10.1186/1471-2164-13-258] [PMID: 22712622]
[11]
O’Brien, D.P.; Jenkin, G.; Buntine, J.; Steffen, C.M.; McDonald, A.; Horne, S.; Friedman, N.D.; Athan, E.; Hughes, A.; Callan, P.P.; Johnson, P.D.R. Treatment and prevention of Mycobacterium ulcerans infection (Buruli ulcer) in Australia: Guideline update. Med. J. Aust., 2014, 200(5), 267-270.
[http://dx.doi.org/10.5694/mja13.11331] [PMID: 24641151]
[12]
Yotsu, R.R.; Richardson, M.; Ishii, N. Drugs for treating Buruli ulcer (Mycobacterium ulcerans disease). Cochrane Libr., 2018, 2018(8), CD012118.
[http://dx.doi.org/10.1002/14651858.CD012118.pub2] [PMID: 30136733]
[13]
Jansson, M.; Beissner, M.; Phillips, R.O.; Badziklou, K.; Piten, E.; Maman, I.; Sarfo, F.S.; Huber, K.L.; Rhomberg, A.; Symank, D.; Wagner, M.; Wiedemann, F.; Nitschke, J.; Banla Kere, A.; Herbinger, K.H.; Adjei, O.; Löscher, T.; Bretzel, G. Comparison of two assays for molecular determination of rifampin resistance in clinical samples from patients with Buruli ulcer disease. J. Clin. Microbiol., 2014, 52(4), 1246-1249.
[http://dx.doi.org/10.1128/JCM.03119-13] [PMID: 24478404]
[14]
Forrellad, M.A.; Klepp, L.I.; Gioffré, A.; Sabio y García, J.; Morbidoni, H.R.; Santangelo, M.P.; Cataldi, A.A.; Bigi, F. Virulence factors of the Mycobacterium tuberculosis complex. Virulence, 2013, 4(1), 3-66.
[http://dx.doi.org/10.4161/viru.22329] [PMID: 23076359]
[15]
Heras, B.; Scanlon, M.J.; Martin, J.L. Targeting virulence not viability in the search for future antibacterials. Br. J. Clin. Pharmacol., 2015, 79(2), 208-215.
[http://dx.doi.org/10.1111/bcp.12356] [PMID: 24552512]
[16]
Ogawara, H. Possible drugs for the treatment of bacterial infections in the future: Anti-virulence drugs. J. Antibiot. (Tokyo), 2021, 74(1), 24-41.
[http://dx.doi.org/10.1038/s41429-020-0344-z] [PMID: 32647212]
[17]
Gupta, R.; Verma, R.; Pradhan, D.; Jain, A.K.; Umamaheswari, A.; Rai, C.S. An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira. PLoS One, 2019, 14(8), e0221446.
[http://dx.doi.org/10.1371/journal.pone.0221446] [PMID: 31430340]
[18]
Ibrahim, K.A.; Helmy, O.M.; Kashef, M.T.; Elkhamissy, T.R.; Ramadan, M.A. Identification of potential drug targets in Helicobacter pylori using in silico subtractive proteomics approaches and their possible inhibition through drug repurposing. Pathogens, 2020, 9(9), 747.
[http://dx.doi.org/10.3390/pathogens9090747] [PMID: 32932580]
[19]
Uddin, R.; Masood, F.; Azam, S.S.; Wadood, A. Identification of putative non-host essential genes and novel drug targets against Acinetobacter baumannii by in silico comparative genome analysis. Microb. Pathog., 2019, 128, 28-35.
[http://dx.doi.org/10.1016/j.micpath.2018.12.015] [PMID: 30550846]
[20]
Pranavathiyani, G.; Prava, J.; Rajeev, A.C.; Pan, A. Novel target exploration from hypothetical proteins of Klebsiella pneumoniae MGH 78578 reveals a protein involved in host-pathogen interaction. Front. Cell. Infect. Microbiol., 2020, 10, 109.
[http://dx.doi.org/10.3389/fcimb.2020.00109] [PMID: 32318354]
[21]
Liu, B.; Zheng, D.; Jin, Q.; Chen, L.; Yang, J. VFDB 2019: A comparative pathogenomic platform with an interactive web interface. Nucleic Acids Res., 2019, 47(D1), D687-D692.
[http://dx.doi.org/10.1093/nar/gky1080] [PMID: 30395255]
[22]
Barh, D.; Tiwari, S.; Jain, N.; Ali, A.; Santos, A.R.; Misra, A.N.; Azevedo, V.; Kumar, A. In silico subtractive genomics for target identification in human bacterial pathogens. Drug Dev. Res., 2011, 72(2), 162-177.
[http://dx.doi.org/10.1002/ddr.20413]
[23]
Yu, C.S.; Chen, Y.C.; Lu, C.H.; Hwang, J.K. Prediction of protein subcellular localization. Proteins, 2006, 64(3), 643-651.
[http://dx.doi.org/10.1002/prot.21018] [PMID: 16752418]
[24]
Krogh, A.; Larsson, B.; von Heijne, G.; Sonnhammer, E.L.L. Predicting transmembrane protein topology with a hidden markov model: Application to complete genomes11Ed., by F. Cohen. J. Mol. Biol., 2001, 305(3), 567-580.
[http://dx.doi.org/10.1006/jmbi.2000.4315] [PMID: 11152613]
[25]
Luo, H.; Lin, Y.; Gao, F.; Zhang, C.T.; Zhang, R. DEG 10, an update of the database of essential genes that includes both protein-coding genes and noncoding genomic elements. Nucleic Acids Res., 2014, 42(D1), D574-D580.
[http://dx.doi.org/10.1093/nar/gkt1131] [PMID: 24243843]
[26]
Gasteiger, E.; Hoogland, C.; Gattiker, A. Protein identification and analysis tools on the ExPASy server. In: The Proteomics Protocols Handbook; John, M.W., Ed.; Humana Press: Totowa, NJ, 2005; pp. 571-607.
[http://dx.doi.org/10.1385/1-59259-890-0:571]
[27]
Chawley, P.; Samal, H.B.; Prava, J.; Suar, M.; Mahapatra, R.K. Comparative genomics study for identification of drug and vaccine targets in Vibrio cholerae: MurA ligase as a case study. Genomics, 2014, 103(1), 83-93.
[http://dx.doi.org/10.1016/j.ygeno.2013.12.002] [PMID: 24368230]
[28]
Azam, S.S.; Shamim, A. An insight into the exploration of druggable genome of Streptococcus gordonii for the identification of novel therapeutic candidates. Genomics, 2014, 104(3), 203-214.
[http://dx.doi.org/10.1016/j.ygeno.2014.07.007] [PMID: 25068724]
[29]
Alcock, B.P.; Raphenya, A.R.; Lau, T.T.Y.; Tsang, K.K.; Bouchard, M.; Edalatmand, A.; Huynh, W.; Nguyen, A.V.; Cheng, A.A.; Liu, S.; Min, S.Y.; Miroshnichenko, A.; Tran, H.K.; Werfalli, R.E.; Nasir, J.A.; Oloni, M.; Speicher, D.J.; Florescu, A.; Singh, B.; Faltyn, M.; Hernandez-Koutoucheva, A.; Sharma, A.N.; Bordeleau, E.; Pawlowski, A.C.; Zubyk, H.L.; Dooley, D.; Griffiths, E.; Maguire, F.; Winsor, G.L.; Beiko, R.G.; Brinkman, F.S.L.; Hsiao, W.W.L.; Domselaar, G.V.; McArthur, A.G. CARD 2020: Antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res., 2020, 48(D1), D517-D525.
[PMID: 31665441]
[30]
Szklarczyk, D.; Gable, A.L.; Lyon, D.; Junge, A.; Wyder, S.; Huerta-Cepas, J.; Simonovic, M.; Doncheva, N.T.; Morris, J.H.; Bork, P.; Jensen, L.J.; Mering, C. STRING v11: Protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res., 2019, 47(D1), D607-D613.
[http://dx.doi.org/10.1093/nar/gky1131] [PMID: 30476243]
[31]
Kanehisa, M.; Furumichi, M.; Sato, Y.; Ishiguro-Watanabe, M.; Tanabe, M. KEGG: Integrating viruses and cellular organisms. Nucleic Acids Res., 2021, 49(D1), D545-D551.
[http://dx.doi.org/10.1093/nar/gkaa970] [PMID: 33125081]
[32]
Kelley, L.A.; Mezulis, S.; Yates, C.M.; Wass, M.N.; Sternberg, M.J.E. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc., 2015, 10(6), 845-858.
[http://dx.doi.org/10.1038/nprot.2015.053] [PMID: 25950237]
[33]
Heo, L.; Park, H.; Seok, C. GalaxyRefine: Protein structure refinement driven by side-chain repacking. Nucleic Acids Res., 2013, 41(W1), W384-W388.
[http://dx.doi.org/10.1093/nar/gkt458] [PMID: 23737448]
[34]
Wiederstein, M; Sippl, MJ ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res., 2007, 35(Web Server), W407-W410.
[http://dx.doi.org/10.1093/nar/gkm290]
[35]
Wishart, D.S.; Feunang, Y.D.; Guo, A.C.; Lo, E.J.; Marcu, A.; Grant, J.R.; Sajed, T.; Johnson, D.; Li, C.; Sayeeda, Z.; Assempour, N.; Iynkkaran, I.; Liu, Y.; Maciejewski, A.; Gale, N.; Wilson, A.; Chin, L.; Cummings, R.; Le, D.; Pon, A.; Knox, C.; Wilson, M. DrugBank 5.0: A major update to the DrugBank database for 2018. Nucleic Acids Res., 2018, 46(D1), D1074-D1082.
[http://dx.doi.org/10.1093/nar/gkx1037] [PMID: 29126136]
[36]
Tian, W.; Chen, C.; Lei, X.; Zhao, J.; Liang, J. CASTp 3.0: Computed atlas of surface topography of proteins. Nucleic Acids Res., 2018, 46(W1), W363-W367.
[http://dx.doi.org/10.1093/nar/gky473] [PMID: 29860391]
[37]
Kim, S.; Chen, J.; Cheng, T.; Gindulyte, A.; He, J.; He, S.; Li, Q.; Shoemaker, B.A.; Thiessen, P.A.; Yu, B.; Zaslavsky, L.; Zhang, J.; Bolton, E.E. PubChem in 2021: New data content and improved web interfaces. Nucleic Acids Res., 2021, 49(D1), D1388-D1395.
[http://dx.doi.org/10.1093/nar/gkaa971] [PMID: 33151290]
[38]
O’Boyle, N.M.; Banck, M.; James, C.A.; Morley, C.; Vandermeersch, T.; Hutchison, G.R. Open Babel: An open chemical toolbox. J. Cheminform., 2011, 3(1), 33.
[http://dx.doi.org/10.1186/1758-2946-3-33] [PMID: 21982300]
[39]
Lipinski, C.A. Lead- and drug-like compounds: The rule-of-five revolution. Drug Discov. Today. Technol., 2004, 1(4), 337-341.
[http://dx.doi.org/10.1016/j.ddtec.2004.11.007] [PMID: 24981612]
[40]
Morris, G.M.; Huey, R.; Lindstrom, W.; Sanner, M.F.; Belew, R.K.; Goodsell, D.S.; Olson, A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem., 2009, 30(16), 2785-2791.
[http://dx.doi.org/10.1002/jcc.21256] [PMID: 19399780]
[41]
Salentin, S.; Schreiber, S.; Haupt, V.J.; Adasme, M.F.; Schroeder, M. PLIP: Fully automated protein–ligand interaction profiler. Nucleic Acids Res., 2015, 43(W1), W443-W447.
[http://dx.doi.org/10.1093/nar/gkv315] [PMID: 25873628]
[42]
BIOVIA DS. Discovery Studio Visualizer; Dassault Systèmes: San Diego, CA, USA, 2021. Available from: https://discover.3ds.com/discovery-studio-visualizer-download
[43]
Case, D.A.; Ben-Shalom, I.Y.; Brozell, S.R.; Cerutti, D.S.; Cheatham, T.E.; Cruzeiro, V.W.D. AMBER; University of California: San Francisco, 2018.
[44]
Jakalian, A.; Jack, D.B.; Bayly, C.I. Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J. Comput. Chem., 2002, 23(16), 1623-1641.
[http://dx.doi.org/10.1002/jcc.10128] [PMID: 12395429]
[45]
Maier, J.A.; Martinez, C.; Kasavajhala, K.; Wickstrom, L.; Hauser, K.E.; Simmerling, C. ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB. J. Chem. Theory Comput., 2015, 11(8), 3696-3713.
[http://dx.doi.org/10.1021/acs.jctc.5b00255] [PMID: 26574453]
[46]
Wang, J.; Wolf, R.M.; Caldwell, J.W.; Kollman, P.A.; Case, D.A. Development and testing of a general amber force field. J. Comput. Chem., 2004, 25(9), 1157-1174.
[http://dx.doi.org/10.1002/jcc.20035] [PMID: 15116359]
[47]
Jorgensen, W.L.; Chandrasekhar, J.; Madura, J.D.; Impey, R.W.; Klein, M.L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys., 1983, 79(2), 926-935.
[http://dx.doi.org/10.1063/1.445869]
[48]
Darden, T.; York, D.; Pedersen, L. Particle mesh Ewald: An N ⋅log(N) method for Ewald sums in large systems. J. Chem. Phys., 1993, 98(12), 10089-10092.
[http://dx.doi.org/10.1063/1.464397]
[49]
Berendsen, H.J.C.; Postma, J.P.M.; van Gunsteren, W.F.; DiNola, A.; Haak, J.R. Molecular dynamics with coupling to an external bath. J. Chem. Phys., 1984, 81(8), 3684-3690.
[http://dx.doi.org/10.1063/1.448118]
[50]
Ryckaert, J.P.; Ciccotti, G.; Berendsen, H.J.C. Numerical integration of the cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes. J. Comput. Phys., 1977, 23(3), 327-341.
[http://dx.doi.org/10.1016/0021-9991(77)90098-5]
[51]
Srinivasan, J.; Miller, J.; Kollman, P.A.; Case, D.A. Continuum solvent studies of the stability of RNA hairpin loops and helices. J. Biomol. Struct. Dyn., 1998, 16(3), 671-682.
[http://dx.doi.org/10.1080/07391102.1998.10508279] [PMID: 10052623]
[52]
Lee, Y.V.; Wahab, H.A.; Choong, Y.S. Potential inhibitors for isocitrate lyase of Mycobacterium tuberculosis and non-M. tuberculosis: A summary. BioMed Res. Int., 2015, 2015, 895453.
[PMID: 25649791]
[53]
Lee, Y.V.; Choi, S.B.; Wahab, H.A.; Lim, T.S.; Choong, Y.S. Applications of ensemble docking in potential inhibitor screening for Mycobacterium tuberculosis isocitrate lyase using a local plant database. J. Chem. Inf. Model., 2019, 59(5), 2487-2495.
[http://dx.doi.org/10.1021/acs.jcim.8b00963] [PMID: 30840452]
[54]
Etuaful, S.; Carbonnelle, B.; Grosset, J.; Lucas, S.; Horsfield, C.; Phillips, R.; Evans, M.; Ofori-Adjei, D.; Klustse, E.; Owusu-Boateng, J.; Amedofu, G.K.; Awuah, P.; Ampadu, E.; Amofah, G.; Asiedu, K.; Wansbrough-Jones, M. Efficacy of the combination rifampin-streptomycin in preventing growth of Mycobacterium ulcerans in early lesions of Buruli ulcer in humans. Antimicrob. Agents Chemother., 2005, 49(8), 3182-3186.
[http://dx.doi.org/10.1128/AAC.49.8.3182-3186.2005] [PMID: 16048922]
[55]
Klis, S.; Stienstra, Y.; Phillips, R.O.; Abass, K.M.; Tuah, W.; van der Werf, T.S. Long term streptomycin toxicity in the treatment of Buruli Ulcer: Follow-up of participants in the BURULICO drug trial. PLoS Negl. Trop. Dis., 2014, 8(3), e2739.
[http://dx.doi.org/10.1371/journal.pntd.0002739] [PMID: 24625583]
[56]
O’Brien, D.P.; McDonald, A.; Callan, P.; Robson, M.; Friedman, N.D.; Hughes, A.; Holten, I.; Walton, A.; Athan, E. Successful outcomes with oral fluoroquinolones combined with rifampicin in the treatment of Mycobacterium ulcerans: An observational cohort study. PLoS Negl. Trop. Dis., 2012, 6(1), e1473.
[http://dx.doi.org/10.1371/journal.pntd.0001473] [PMID: 22272368]
[57]
Sugawara, M.; Ishii, N.; Nakanaga, K.; Suzuki, K.; Umebayashi, Y.; Makigami, K.; Aihara, M. Exploration of a standard treatment for Buruli ulcer through a comprehensive analysis of all cases diagnosed in Japan. J. Dermatol., 2015, 42(6), 588-595.
[http://dx.doi.org/10.1111/1346-8138.12851] [PMID: 25809502]
[58]
Marsollier, L.; Honoré, N.; Legras, P.; Manceau, A.L.; Kouakou, H.; Carbonnelle, B.; Cole, S.T. Isolation of three Mycobacterium ulcerans strains resistant to rifampin after experimental chemotherapy of mice. Antimicrob. Agents Chemother., 2003, 47(4), 1228-1232.
[http://dx.doi.org/10.1128/AAC.47.4.1228-1232.2003] [PMID: 12654651]
[59]
Butt, A.M.; Nasrullah, I.; Tahir, S.; Tong, Y. Comparative genomics analysis of Mycobacterium ulcerans for the identification of putative essential genes and therapeutic candidates. PLoS One, 2012, 7(8), e43080.
[http://dx.doi.org/10.1371/journal.pone.0043080] [PMID: 22912793]
[60]
Bhattacharya, S.; Ghosh, P.; Banerjee, D.; Banerjee, A.; Ray, S. In silico drug target discovery through Proteome Mining from M. tuberculosis: An insight into antivirulent therapy. Comb. Chem. High Throughput Screen., 2020, 23(3), 253-268.
[http://dx.doi.org/10.2174/1386207323666200219120903] [PMID: 32072892]
[61]
Jamal, S.B.; Hassan, S.S.; Tiwari, S.; Viana, M.V.; Benevides, L.J.; Ullah, A.; Turjanski, A.G.; Barh, D.; Ghosh, P.; Costa, D.A.; Silva, A.; Röttger, R.; Baumbach, J.; Azevedo, V.A.C. An integrative in-silico approach for therapeutic target identification in the human pathogen Corynebacterium diphtheriae. PLoS One, 2017, 12(10), e0186401.
[http://dx.doi.org/10.1371/journal.pone.0186401] [PMID: 29049350]
[62]
Ribet, D.; Cossart, P. How bacterial pathogens colonize their hosts and invade deeper tissues. Microbes Infect., 2015, 17(3), 173-183.
[http://dx.doi.org/10.1016/j.micinf.2015.01.004] [PMID: 25637951]
[63]
Dunn, M.F.; Ramírez-Trujillo, J.A.; Hernández-Lucas, I. Major roles of isocitrate lyase and malate synthase in bacterial and fungal pathogenesis. Microbiology (Reading), 2009, 155(10), 3166-3175.
[http://dx.doi.org/10.1099/mic.0.030858-0] [PMID: 19684068]
[64]
Cheah, H.L.; Lim, V.; Sandai, D. Inhibitors of the glyoxylate cycle enzyme ICL1 in Candida albicans for potential use as antifungal agents. PLoS One, 2014, 9(4), e95951.
[http://dx.doi.org/10.1371/journal.pone.0095951] [PMID: 24781056]
[65]
Sharma, R.; Das, O.; Damle, S.G.; Sharma, A.K. Isocitrate lyase: A potential target for anti-tubercular drugs. Recent Pat. Inflamm. Allergy Drug Discov., 2013, 7(2), 114-123.
[http://dx.doi.org/10.2174/1872213X11307020003] [PMID: 23506018]
[66]
Kwofie, S.; Dankwa, B.; Odame, E.; Agamah, F.; Doe, L.; Teye, J.; Agyapong, O.; Miller, W., III; Mosi, L.; Wilson, M. In silico screening of isocitrate lyase for novel anti-Buruli ulcer natural products originating from Africa. Molecules, 2018, 23(7), 1550.
[http://dx.doi.org/10.3390/molecules23071550] [PMID: 29954088]
[67]
De Voss, J.J.; Rutter, K.; Schroeder, B.G.; Su, H.; Zhu, Y.; Barry, C.E., III The salicylate-derived mycobactin siderophores of Mycobacterium tuberculosis are essential for growth in macrophages. Proc. Natl. Acad. Sci. USA, 2000, 97(3), 1252-1257.
[http://dx.doi.org/10.1073/pnas.97.3.1252] [PMID: 10655517]
[68]
Krithika, R.; Marathe, U.; Saxena, P.; Ansari, M.Z.; Mohanty, D.; Gokhale, R.S. A genetic locus required for iron acquisition in Mycobacterium tuberculosis. Proc. Natl. Acad. Sci. USA, 2006, 103(7), 2069-2074.
[http://dx.doi.org/10.1073/pnas.0507924103] [PMID: 16461464]
[69]
He, J.; Xie, J. Advances in mycobacterium siderophore-based drug discovery. Acta Pharm. Sin. B, 2011, 1(1), 8-13.
[http://dx.doi.org/10.1016/j.apsb.2011.04.008]
[70]
Hameed, S.; Pal, R.; Fatima, Z. Iron acquisition mechanisms: Promising target against Mycobacterium tuberculosis. Open Microbiol. J., 2015, 9(1), 91-97.
[http://dx.doi.org/10.2174/1874285801509010091] [PMID: 26464608]
[71]
Striebel, F.; Imkamp, F.; Sutter, M.; Steiner, M.; Mamedov, A.; Weber-Ban, E. Bacterial ubiquitin-like modifier Pup is deamidated and conjugated to substrates by distinct but homologous enzymes. Nat. Struct. Mol. Biol., 2009, 16(6), 647-651.
[http://dx.doi.org/10.1038/nsmb.1597] [PMID: 19448618]
[72]
Zhang, S.; Burns-Huang, K.E.; Janssen, G.V.; Li, H.; Ovaa, H.; Hedstrom, L.; Darwin, K.H. Mycobacterium tuberculosis Proteasome Accessory Factor A (PafA) can transfer prokaryotic ubiquitin-like protein (Pup) between substrates. MBio, 2017, 8(1), e00122-e17.
[http://dx.doi.org/10.1128/mBio.00122-17] [PMID: 28223451]
[73]
Elharar, Y.; Roth, Z.; Hermelin, I.; Moon, A.; Peretz, G.; Shenkerman, Y.; Vishkautzan, M.; Khalaila, I.; Gur, E. Survival of mycobacteria depends on proteasome‐mediated amino acid recycling under nutrient limitation. EMBO J., 2014, 33(16), 1802-1814.
[http://dx.doi.org/10.15252/embj.201387076] [PMID: 24986881]
[74]
Darwin, K.H.; Ehrt, S.; Gutierrez-Ramos, J.C.; Weich, N.; Nathan, C.F. The proteasome of Mycobacterium tuberculosis is required for resistance to nitric oxide. Science, 2003, 302(5652), 1963-1966.
[http://dx.doi.org/10.1126/science.1091176] [PMID: 14671303]
[75]
Darwin, K.H. Prokaryotic ubiquitin-like protein (Pup), proteasomes and pathogenesis. Nat. Rev. Microbiol., 2009, 7(7), 485-491.
[http://dx.doi.org/10.1038/nrmicro2148] [PMID: 19483713]
[76]
Gupta, I.; Aggarwal, S.; Singh, K.; Yadav, A.; Khan, S. Ubiquitin Proteasome pathway proteins as potential drug targets in parasite Trypanosoma cruzi. Sci. Rep., 2018, 8(1), 8399.
[http://dx.doi.org/10.1038/s41598-018-26532-z] [PMID: 29849031]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy