Login Register Cart 0
Generic placeholder image

Combinatorial Chemistry & High Throughput Screening

Editor-in-Chief

ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

In Silico Drug Target Discovery Through Proteome Mining from M. tuberculosis: An Insight into Antivirulent Therapy

Author(s): Shreya Bhattacharya, Puja Ghosh, Debasmita Banerjee, Arundhati Banerjee and Sujay Ray*

Volume 23, Issue 3, 2020

Page: [253 - 268] Pages: 16

DOI: 10.2174/1386207323666200219120903

Price: $65

Abstract

Aim and Objective: One of the challenges to conventional therapies against Mycobacterium tuberculosis is the development of multi-drug resistant pathogenic strains. This study was undertaken to explore new therapeutic targets for the revolutionary antivirulence therapy utilizing the pathogen’s essential hypothetical proteins, serving as virulence factors, which is the essential first step in novel drug designing.

Methods: Functional annotations of essential hypothetical proteins from Mycobacterium tuberculosis (H37Rv strain) were performed through domain annotation, Gene Ontology analysis, physicochemical characterization and prediction of subcellular localization. Virulence factors among the essential hypothetical proteins were predicted, among which pathogen-specific drug target candidates, non-homologous to human and gut microbiota, were identified. This was followed by druggability and spectrum analysis of the identified targets.

Results and Conclusion: The study successfully assigned functions of 83 essential hypothetical proteins of Mycobacterium tuberculosis, among which 25 were identified as virulence factors. Out of 25, 12 virulence factors were observed as potential pathogen-specific drug target candidates. Nine potential targets had druggable properties and rest three were considered as novel targets. Exploration of these targets will provide new insights into future drug development. Characterization of subcellular localizations revealed that most of the predicted targets were cytoplasmic which could be ideal for intracellular drugs, while two drug targets were membranebound, ideal for vaccines. Spectrum analysis identified one broad-spectrum and 11 narrowspectrum targets. This study would, therefore, instigate designing novel therapeutics for antivirulence therapy, which have the potential to serve as revolutionary treatment instead of conventional antibiotic therapies to overcome the lethality of antibiotic-resistant strains.

Keywords: Mycobacterium tuberculosis, essential hypothetical proteins, domain characterization, gene ontology, subcellular localization prediction, therapeutic target identification, druggability analysis, spectrum analysis.

« Previous
[1]
Gordon, S.V.; Parish, T. Microbe Profile: Mycobacterium tuberculosis: Humanity’s deadly microbial foe. Microbiology, 2018, 164(4), 437-439.
[http://dx.doi.org/10.1099/mic.0.000601] [PMID: 29465344]
[2]
Dye, C. Global epidemiology of tuberculosis. Lancet, 2006, 367(9514), 938-940.
[http://dx.doi.org/10.1016/S0140-6736(06)68384-0] [PMID: 16546542]
[3]
Global tuberculosis report. 2018.https://www.who.int/tb/publications/global_report/en/ [accessed May 16, 2019]
[4]
Almeida Da Silva, P.E.; Palomino, J.C. Molecular basis and mechanisms of drug resistance in Mycobacterium tuberculosis: classical and new drugs. J. Antimicrob. Chemother., 2011, 66(7), 1417-1430.
[http://dx.doi.org/10.1093/jac/dkr173] [PMID: 21558086]
[5]
Pinto, L.; Menzies, D. Treatment of drug-resistant tuberculosis. Infect. Drug Resist., 2011, 4, 129-135.
[PMID: 21904458]
[6]
What is multidrug-resistant tuberculosis (MDR-TB) and how do we control it? Available at . https://www.who.int/features/qa/79/en/ (accessed on May 16, 2019).
[7]
Goldman, R.C.; Plumley, K.V.; Laughon, B.E. The evolution of extensively drug resistant tuberculosis (XDR-TB): history, status and issues for global control. Infect. Disord. Drug Targets, 2007, 7(2), 73-91.
[http://dx.doi.org/10.2174/187152607781001844] [PMID: 17970220]
[8]
Velayati, A.A.; Masjedi, M.R.; Farnia, P.; Tabarsi, P.; Ghanavi, J.; ZiaZarifi, A.H.; Hoffner, S.E. Emergence of new forms of totally drug-resistant tuberculosis bacilli: super extensively drug-resistant tuberculosis or totally drug-resistant strains in iran. Chest, 2009, 136(2), 420-425.
[http://dx.doi.org/10.1378/chest.08-2427] [PMID: 19349380]
[9]
Bakheet, T.M.; Doig, A.J. Properties and identification of human protein drug targets. Bioinformatics, 2009, 25(4), 451-457.
[http://dx.doi.org/10.1093/bioinformatics/btp002] [PMID: 19164304]
[10]
Gazi, M.A.; Kibria, M.G.; Mahfuz, M.; Islam, M.R.; Ghosh, P.; Afsar, M.N.A.; Khan, M.A.; Ahmed, T. Functional, structural and epitopic prediction of hypothetical proteins of Mycobacterium tuberculosis H37Rv: An in silico approach for prioritizing the targets. Gene, 2016, 591(2), 442-455.
[http://dx.doi.org/10.1016/j.gene.2016.06.057] [PMID: 27374154]
[11]
Bifani, P.; Moghazeh, S.; Shopsin, B.; Driscoll, J.; Ravikovitch, A.; Kreiswirth, B.N. Molecular characterization of Mycobacterium tuberculosis H37Rv/Ra variants: distinguishing the mycobacterial laboratory strain. J. Clin. Microbiol., 2000, 38(9), 3200-3204.
[http://dx.doi.org/10.1128/JCM.38.9.3200-3204.2000] [PMID: 10970357]
[12]
Cole, S.T.; Brosch, R.; Parkhill, J.; Garnier, T.; Churcher, C.; Harris, D.; Gordon, S.V.; Eiglmeier, K.; Gas, S.; Barry, C.E., III; Tekaia, F.; Badcock, K.; Basham, D.; Brown, D.; Chillingworth, T.; Connor, R.; Davies, R.; Devlin, K.; Feltwell, T.; Gentles, S.; Hamlin, N.; Holroyd, S.; Hornsby, T.; Jagels, K.; Krogh, A.; McLean, J.; Moule, S.; Murphy, L.; Oliver, K.; Osborne, J.; Quail, M.A.; Rajandream, M-A.; Rogers, J.; Rutter, S.; Seeger, K.; Skelton, J.; Squares, R.; Squares, S.; Sulston, J.E.; Taylor, K.; Whitehead, S.; Barrell, B.G. Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature, 1998, 393(6685), 537-544.
[http://dx.doi.org/10.1038/31159] [PMID: 9634230]
[13]
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(Database issue), D574-D580.
[http://dx.doi.org/10.1093/nar/gkt1131] [PMID: 24243843]
[14]
Shahbaaz, M.; Bisetty, K.; Ahmad, F.; Hassan, M.I. Current Advances in the Identification and Characterization of Putative Drug and Vaccine Targets in the Bacterial Genomes. Curr. Top. Med. Chem., 2016, 16(9), 1040-1069.
[http://dx.doi.org/10.2174/1568026615666150825143307] [PMID: 26303422]
[15]
Cegelski, L.; Marshall, G.R.; Eldridge, G.R.; Hultgren, S.J. The biology and future prospects of antivirulence therapies. Nat. Rev. Microbiol., 2008, 6(1), 17-27.
[http://dx.doi.org/10.1038/nrmicro1818] [PMID: 18079741]
[16]
Garland, M.; Loscher, S.; Bogyo, M. Chemical Strategies To Target Bacterial Virulence. Chem. Rev., 2017, 117(5), 4422-4461.
[http://dx.doi.org/10.1021/acs.chemrev.6b00676] [PMID: 28234447]
[17]
Imperi, F.; Massai, F.; Facchini, M.; Frangipani, E.; Visaggio, D.; Leoni, L.; Bragonzi, A.; Visca, P. Repurposing the antimycotic drug flucytosine for suppression of Pseudomonas aeruginosa pathogenicity. Proc. Natl. Acad. Sci. USA, 2013, 110(18), 7458-7463.
[http://dx.doi.org/10.1073/pnas.1222706110] [PMID: 23569238]
[18]
Branden, C.; Tooze, J. Introduction to Protein Structure; Garland: New York, 1998.
[19]
Finn, R.D.; Coggill, P.; Eberhardt, R.Y.; Eddy, S.R.; Mistry, J.; Mitchell, A.L.; Potter, S.C.; Punta, M.; Qureshi, M.; Sangrador-Vegas, A.; Salazar, G.A.; Tate, J.; Bateman, A. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res., 2016, 44(D1), D279-D285.
[http://dx.doi.org/10.1093/nar/gkv1344] [PMID: 26673716]
[20]
Mitchell, A.L.; Attwood, T.K.; Babbitt, P.C.; Blum, M.; Bork, P.; Bridge, A.; Brown, S.D.; Chang, H-Y.; El-Gebali, S.; Fraser, M.I.; Gough, J.; Haft, D.R.; Huang, H.; Letunic, I.; Lopez, R.; Luciani, A.; Madeira, F.; Marchler-Bauer, A.; Mi, H.; Natale, D.A.; Necci, M.; Nuka, G.; Orengo, C.; Pandurangan, A.P.; Paysan-Lafosse, T.; Pesseat, S.; Potter, S.C.; Qureshi, M.A.; Rawlings, N.D.; Redaschi, N.; Richardson, L.J.; Rivoire, C.; Salazar, G.A.; Sangrador-Vegas, A.; Sigrist, C.J.A.; Sillitoe, I.; Sutton, G.G.; Thanki, N.; Thomas, P.D.; Tosatto, S.C.E.; Yong, S-Y.; Finn, R.D. InterPro in 2019: improving coverage, classification and access to protein sequence annotations. Nucleic Acids Res., 2019, 47(D1), D351-D360.
[http://dx.doi.org/10.1093/nar/gky1100] [PMID: 30398656]
[21]
Koskinen, P.; Törönen, P.; Nokso-Koivisto, J.; Holm, L. PANNZER: high-throughput functional annotation of uncharacterized proteins in an error-prone environment. Bioinformatics, 2015, 31(10), 1544-1552.
[http://dx.doi.org/10.1093/bioinformatics/btu851] [PMID: 25653249]
[22]
Schomburg, I.; Chang, A.; Schomburg, D. BRENDA, enzyme data and metabolic information. Nucleic Acids Res., 2002, 30(1), 47-49.
[http://dx.doi.org/10.1093/nar/30.1.47] [PMID: 11752250]
[23]
Gasteiger, E.; Hoogland, C.; Gattiker, A.; Duvaud, S.; Wilkins, M.R.; Appel, R.D.; Bairoch, A. Protein Identification and Analysis Tools on the ExPASy Server. In: The Proteomics Protocols Handbook; Humana Press, 2005; pp. 571-607.
[http://dx.doi.org/10.1385/1-59259-890-0:571]
[24]
Kyte, J.; Doolittle, R.F. A simple method for displaying the hydropathic character of a protein. J. Mol. Biol., 1982, 157(1), 105-132.
[http://dx.doi.org/10.1016/0022-2836(82)90515-0] [PMID: 7108955]
[25]
Yu, N.Y.; Wagner, J.R.; Laird, M.R.; Melli, G.; Rey, S.; Lo, R.; Dao, P.; Sahinalp, S.C.; Ester, M.; Foster, L.J.; Brinkman, F.S.L. PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes. Bioinformatics, 2010, 26(13), 1608-1615.
[http://dx.doi.org/10.1093/bioinformatics/btq249] [PMID: 20472543]
[26]
Hirokawa, T.; Boon-Chieng, S.; Mitaku, S. SOSUI: classification and secondary structure prediction system for membrane proteins. Bioinformatics, 1998, 14(4), 378-379.
[http://dx.doi.org/10.1093/bioinformatics/14.4.378] [PMID: 9632836]
[27]
Garg, A.; Gupta, D. VirulentPred: a SVM based prediction method for virulent proteins in bacterial pathogens. BMC Bioinformatics, 2008, 9, 62.
[http://dx.doi.org/10.1186/1471-2105-9-62] [PMID: 18226234]
[28]
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]
[29]
Lin, L.; Zhang, J. Role of intestinal microbiota and metabolites on gut homeostasis and human diseases. BMC Immunol., 2017, 18(1), 2.
[http://dx.doi.org/10.1186/s12865-016-0187-3] [PMID: 28061847]
[30]
Shende, G.; Haldankar, H.; Barai, R.S.; Bharmal, M.H.; Shetty, V.; Idicula-Thomas, S. PBIT: Pipeline Builder for Identification of drug Targets for infectious diseases. Bioinformatics, 2017, 33(6), 929-931.
[PMID: 28039165]
[31]
Bento, A.P.; Gaulton, A.; Hersey, A.; Bellis, L.J.; Chambers, J.; Davies, M.; Krüger, F.A.; Light, Y.; Mak, L.; McGlinchey, S.; Nowotka, M.; Papadatos, G.; Santos, R.; Overington, J.P. The ChEMBL bioactivity database: an update. Nucleic Acids Res., 2014, 42(Database issue), D1083-D1090.
[http://dx.doi.org/10.1093/nar/gkt1031] [PMID: 24214965]
[32]
Crowther, G.J.; Shanmugam, D.; Carmona, S.J.; Doyle, M.A.; Hertz-Fowler, C.; Berriman, M.; Nwaka, S.; Ralph, S.A.; Roos, D.S.; Van Voorhis, W.C.; Agüero, F. Identification of attractive drug targets in neglected-disease pathogens using an in silico approach. PLoS Negl. Trop. Dis., 2010, 4(8) e804
[http://dx.doi.org/10.1371/journal.pntd.0000804] [PMID: 20808766]
[33]
McGuffin, L.J.; Bryson, K.; Jones, D.T. The PSIPRED protein structure prediction server. Bioinformatics, 2000, 16(4), 404-405.
[http://dx.doi.org/10.1093/bioinformatics/16.4.404] [PMID: 10869041]
[34]
Erzberger, J.P.; Berger, J.M. Evolutionary relationships and structural mechanisms of AAA+ proteins. Annu. Rev. Biophys. Biomol. Struct., 2006, 35, 93-114.
[http://dx.doi.org/10.1146/annurev.biophys.35.040405.101933] [PMID: 16689629]
[35]
Blackwood, J.K.; Rzechorzek, N.J.; Abrams, A.S.; Maman, J.D.; Pellegrini, L.; Robinson, N.P. Structural and functional insights into DNA-end processing by the archaeal HerA helicase-NurA nuclease complex. Nucleic Acids Res., 2012, 40(7), 3183-3196.
[http://dx.doi.org/10.1093/nar/gkr1157] [PMID: 22135300]
[36]
Brennan, R.G. The winged-helix DNA-binding motif: another helix-turn-helix takeoff. Cell, 1993, 74(5), 773-776.
[http://dx.doi.org/10.1016/0092-8674(93)90456-Z] [PMID: 8374950]
[37]
Kang, C-M.; Nyayapathy, S.; Lee, J-Y.; Suh, J-W.; Husson, R.N. Wag31, a homologue of the cell division protein DivIVA, regulates growth, morphology and polar cell wall synthesis in mycobacteria. Microbiology, 2008, 154(Pt 3), 725-735.
[http://dx.doi.org/10.1099/mic.0.2007/014076-0] [PMID: 18310019]
[38]
Korotkova, N.; Freire, D.; Phan, T.H.; Ummels, R.; Creekmore, C.C.; Evans, T.J.; Wilmanns, M.; Bitter, W.; Parret, A.H.A.; Houben, E.N.G.; Korotkov, K.V. Structure of the Mycobacterium tuberculosis type VII secretion system chaperone EspG5 in complex with PE25-PPE41 dimer. Mol. Microbiol., 2014, 94(2), 367-382.
[http://dx.doi.org/10.1111/mmi.12770] [PMID: 25155747]
[39]
Deochand, D.K.; Grove, A.; Mar, R. MarR family transcription factors: dynamic variations on a common scaffold. Crit. Rev. Biochem. Mol. Biol., 2017, 52(6), 595-613.
[http://dx.doi.org/10.1080/10409238.2017.1344612] [PMID: 28670937]
[40]
Serafini, A.; Pisu, D.; Palù, G.; Rodriguez, G.M.; Manganelli, R. The ESX-3 secretion system is necessary for iron and zinc homeostasis in Mycobacterium tuberculosis. PLoS One, 2013, 8(10) e78351
[http://dx.doi.org/10.1371/journal.pone.0078351] [PMID: 24155985]
[41]
Chevalier, B.S.; Stoddard, B.L. Homing endonucleases: structural and functional insight into the catalysts of intron/intein mobility. Nucleic Acids Res., 2001, 29(18), 3757-3774.
[http://dx.doi.org/10.1093/nar/29.18.3757] [PMID: 11557808]
[42]
Wei, W.; Zhang, S.; Fleming, J.; Chen, Y.; Li, Z.; Fan, S.; Liu, Y.; Wang, W.; Wang, T.; Liu, Y.; Ren, B.; Wang, M.; Jiao, J.; Chen, Y.; Zhou, Y.; Zhou, Y.; Gu, S.; Zhang, X.; Wan, L.; Chen, T.; Zhou, L.; Chen, Y.; Zhang, X-E.; Li, C.; Zhang, H.; Bi, L. Mycobacterium tuberculosis type III-A CRISPR/Cas system crRNA and its maturation have atypical features. FASEB J., 2019, 33(1), 1496-1509.
[http://dx.doi.org/10.1096/fj.201800557RR] [PMID: 29979631]
[43]
Keasling, J.D.; Bertsch, L.; Kornberg, A. Guanosine pentaphosphate phosphohydrolase of Escherichia coli is a long-chain exopolyphosphatase. Proc. Natl. Acad. Sci. USA, 1993, 90(15), 7029-7033.
[http://dx.doi.org/10.1073/pnas.90.15.7029] [PMID: 8394006]
[44]
Miallau, L.; Faller, M.; Chiang, J.; Arbing, M.; Guo, F.; Cascio, D.; Eisenberg, D. Structure and proposed activity of a member of the VapBC family of toxin-antitoxin systems. VapBC-5 from Mycobacterium tuberculosis. J. Biol. Chem., 2009, 284(1), 276-283.
[http://dx.doi.org/10.1074/jbc.M805061200] [PMID: 18952600]
[45]
Akoh, C.C.; Lee, G-C.; Liaw, Y.C.; Huang, T.H.; Shaw, J-F. GDSL family of serine esterases/lipases. Prog. Lipid Res., 2004, 43(6), 534-552.
[http://dx.doi.org/10.1016/j.plipres.2004.09.002] [PMID: 15522763]
[46]
Choe, L.H.; Chen, W.; Lee, K.H. Proteome analysis of factor for inversion stimulation (Fis) overproduction in Escherichia coli. Electrophoresis, 1999, 20(4-5), 798-805.
[http://dx.doi.org/10.1002/(SICI)1522-2683(19990101)20:4/5<798:AID-ELPS798>3.0.CO;2-F] [PMID: 10344250]
[47]
Marrakchi, H.; Zhang, Y-M.; Rock, C.O. Mechanistic diversity and regulation of Type II fatty acid synthesis. Biochem. Soc. Trans., 2002, 30(Pt 6), 1050-1055.
[http://dx.doi.org/10.1042/bst0301050] [PMID: 12440970]
[48]
Pearce, M.J.; Mintseris, J.; Ferreyra, J.; Gygi, S.P.; Darwin, K.H. Ubiquitin-like protein involved in the proteasome pathway of Mycobacterium tuberculosis. Science, 2008, 322(5904), 1104-1107.
[http://dx.doi.org/10.1126/science.1163885] [PMID: 18832610]
[49]
Hamma, T.; Ferré-D’Amaré, A.R. Pseudouridine synthases. Chem. Biol., 2006, 13(11), 1125-1135.
[http://dx.doi.org/10.1016/j.chembiol.2006.09.009] [PMID: 17113994]
[50]
Scopes, R.K. Protein Purification: Principles and Practice; Springer-Verlag New York, 1982.
[51]
Marra, A. Can virulence factors be viable antibacterial targets? Expert Rev. Anti Infect. Ther., 2004, 2(1), 61-72.
[http://dx.doi.org/10.1586/14787210.2.1.61] [PMID: 15482172]
[52]
Bieler, S.; Soto, C. β-sheet breakers for Alzheimer’s disease therapy. Curr. Drug Targets, 2004, 5(6), 553-558.
[http://dx.doi.org/10.2174/1389450043345290] [PMID: 15270201]
[53]
Rivas, A.; Vidal, R.L.; Hetz, C. Targeting the unfolded protein response for disease intervention. Expert Opin. Ther. Targets, 2015, 19(9), 1203-1218.
[http://dx.doi.org/10.1517/14728222.2015.1053869] [PMID: 26166159]
[54]
Kremer, L.; Gurcha, S.S.; Bifani, P.; Hitchen, P.G.; Baulard, A.; Morris, H.R.; Dell, A.; Brennan, P.J.; Besra, G.S. Characterization of a putative α-mannosyltransferase involved in phosphatidylinositol trimannoside biosynthesis in Mycobacterium tuberculosis. Biochem. J., 2002, 363(Pt 3), 437-447.
[http://dx.doi.org/10.1042/bj3630437] [PMID: 11964144]
[55]
Jankute, M.; Cox, J.A.; Harrison, J.; Besra, G.S. Assembly of the mycobacterial cell wall. Annu. Rev. Microbiol., 2015, 69, 405-423.
[http://dx.doi.org/10.1146/annurev-micro-091014-104121] [PMID: 26488279]
[56]
Lea-Smith, D.J.; Martin, K.L.; Pyke, J.S.; Tull, D.; McConville, M.J.; Coppel, R.L.; Crellin, P.K. Analysis of a new mannosyltransferase required for the synthesis of phosphatidylinositol mannosides and lipoarbinomannan reveals two lipomannan pools in corynebacterineae. J. Biol. Chem., 2008, 283(11), 6773-6782.
[http://dx.doi.org/10.1074/jbc.M707139200] [PMID: 18178556]
[57]
Melander, R.J.; Melander, C. The challenge of overcoming antibiotic resistance: an adjuvant approach? ACS Infect. Dis., 2017, 3(8), 559-563.
[http://dx.doi.org/10.1021/acsinfecdis.7b00071] [PMID: 28548487]
[58]
Phan, T.H.; van Leeuwen, L.M.; Kuijl, C.; Ummels, R.; van Stempvoort, G.; Rubio-Canalejas, A.; Piersma, S.R.; Jiménez, C.R.; van der Sar, A.M.; Houben, E.N.G.; Bitter, W.; Esp, H. EspH is a hypervirulence factor for Mycobacterium marinum and essential for the secretion of the ESX-1 substrates EspE and EspF. PLoS Pathog., 2018, 14(8) e1007247
[http://dx.doi.org/10.1371/journal.ppat.1007247] [PMID: 30102741]
[59]
Abbehausen, C. Zinc finger domains as therapeutic targets for metal-based compounds - an update. Metallomics, 2019, 11(1), 15-28.
[http://dx.doi.org/10.1039/C8MT00262B] [PMID: 30303505]
[60]
Masamba, P.; Adenowo, A.F.; Oyinloye, B.E.; Kappo, A.P. Universal stress proteins as new targets for environmental and therapeutic interventions of schistosomiasis. Int. J. Environ. Res. Public Health, 2016, 13(10), 972.
[http://dx.doi.org/10.3390/ijerph13100972] [PMID: 27706050]
[61]
Waack, U.; Johnson, T.L.; Chedid, K.; Xi, C.; Simmons, L.A.; Mobley, H.L.T.; Sandkvist, M. Targeting the type II secretion system: development, optimization, and validation of a high-throughput screen for the identification of small molecule inhibitors. Front. Cell. Infect. Microbiol., 2017, 7, 380.
[http://dx.doi.org/10.3389/fcimb.2017.00380] [PMID: 28894700]
[62]
Yang, J.; Suzuki, M.; McCarty, D.R. Essential role of conserved DUF177A protein in plastid 23S rRNA accumulation and plant embryogenesis. J. Exp. Bot., 2016, 67(18), 5447-5460.
[http://dx.doi.org/10.1093/jxb/erw311] [PMID: 27574185]
[63]
Lambert, M.; Jambon, S.; Depauw, S.; David-Cordonnier, M-H. Targeting transcription factors for cancer treatment. Molecules, 2018, 23(6), 1479.
[http://dx.doi.org/10.3390/molecules23061479] [PMID: 29921764]
[64]
Grainger, D.C.; Busby, S.J. Global regulators of transcription in Escherichia coli: mechanisms of action and methods for study. Adv. Appl. Microbiol., 2008, 65, 93-113.
[http://dx.doi.org/10.1016/S0065-2164(08)00604-7] [PMID: 19026863]
[65]
Golkar, Z.; Rochelle, L. Crisprs/Cas9 may provide new method for drug discovery and development. J. Mol. Biomark. Diagn., 2016, 7(280), 10-4172.
[http://dx.doi.org/10.4172/2155-9929.1000280]
[66]
Louwen, R.; Staals, R.H.J.; Endtz, H.P.; van Baarlen, P.; van der Oost, J. The role of CRISPR-Cas systems in virulence of pathogenic bacteria. Microbiol. Mol. Biol. Rev., 2014, 78(1), 74-88.
[http://dx.doi.org/10.1128/MMBR.00039-13] [PMID: 24600041]

Rights & Permissions Print Cite
Article Metrics
6
© 2024 Bentham Science Publishers | Privacy Policy