New Imidazole Inhibitors of Mycobacterial FtsZ: the Way from High-Throughput Molecular Screening in Grid up to in vitro Verification
DOI:
https://doi.org/10.15407/scin12.03.044Keywords:
bioinformatics, high-throughput screening (HTS), in vitro, structural biology, tuberculosisAbstract
In the framework of UNG virtual organization CSLabGrid, high-throughput molecular screening was performed for new anti-TB compounds. Using program FlexX installed on IFBG Claster and models of four perspective ligand binding sites on the surface of FtsZ of Mycobacterium tuberculosis, virtual screening was performed for database containing 2886 compounds synthesized in the Institute of Organic Chemistry of NAS of Ukraine. Based on LE and ΔG score, docking scores of CCDC Gold, and results of molecular dynamics, we selected a group of perspective FtsZ inhibitors. In vitro validation have revealed 6 compounds with the highest inhibition of GTPase activity of FtsZ. Also, based on in vitro experiment, we have selected three compounds exhibiting both - strong inhibition of FtsZ polymerization and inhibition of GTPase activity.
References
World Health Organization. Global tuberculosis report. Kyiv, 2012. http://apps.who.int/iris/bitstream/10665/ 75938/1/9789241564502_eng.pdf.
Kumar K., Awasthi D., Berger W.T., Tonge P.J., Slayden R.A., Ojima I. Discovery of anti-TB agents that target the cell-division protein FtsZ. Future Med Chem. 2010, 2(8): 1305-1323. https://doi.org/10.4155/fmc.10.220
Osnovni zasady organizacii' medychnoi' dopomogy hvorym na tuberkul'oz (posibnyk z organizacijno-meto dych noi' roboty). Ju. I. Feshhenko, V. M. Mel'nyk, V. G. Ma tu sevych, I.O. Novozhylova, V.O. Juhymec', M.I. Lyn nyk. Za red. Ju. I. Feshhenka, V. M. Mel'nyka. Elektron. dani. Kyiv, 2012. http://www.ifp.kiev.ua/ftp1/original/2012/ feschenko2012-1.pdf [in Ukrainian].
Levyc'ka N.A., Bazhora Ju.I., Nikolajevs'kyj V.V., Asmolov O.K. Medykamentozna rezystentnist' miko bakterij tuberkul'ozu, shho buly vydileni vid hvoryh v mykolai'vs'kij oblasti Ukrai'ny protjagom 2000-2002. Ukrai'ns'kyj pul'monologichnyj zhurnal. 2003, 4: 17-20 [in Ukrainian].
Cheren'ko C. Tuberkul'oz - hvoroba social'na. UNIAN. Zdorov'ja. 2008, 77: 9-18 [in Ukrainian].
de Colombani P., Veen J. (Ed.) Review of the National Tuberculosis Programme in Ukraine. 10-22 October 2010, WHO Regional Office for Europe. World Health Organization: 2011.
Musser J.M., Amin A., Ramaswamy S. Negligible genetic diversity of mycobacterium tuberculosis host immune system protein targets: evidence of limited selective pressure. Genetics. 2000, 155(1): 7-16. https://doi.org/10.1093/genetics/155.1.7
Hudson A., Imamura T., Gutteridge W., Kanyok T., Nunn P. The current anti-TB drugre search and development pipeline. TDR/PRD/TB/03.1W. 2003: http:// www.who.int/tdr/publications/documents/anti-tbdrug.pdf.
Tripathi R.P., Tewari N., Dwivedi N., Tiwari V.K. Fighting tuberculosis: an old disease with new challenges. Med Res Rev. 2005, 25(1): 93-131. https://doi.org/10.1002/med.20017
Pavan F.R., Sato D.N., Higuchi C.T., Santos A.C.B., Vilegas W., Leite, C.Q.F. In vitro anti-Mycobacterium tu berculosis activity of some Brazilian "Cerrado" plants. Revista Brasileira de Farmacognosia. 2009, 19: 204-206. https://doi.org/10.1590/S0102-695X2009000200004
Mani N., Gross C.H., Parsons J.D., Hanzelka B., Müh U., Mullin S., Liao Y., Grillot A.L., Stamos D., Charifson P.S., Grossman T.H. In vitro characterization of the anti bacterial spectrum of novel bacterial type II topoisomerase inhibitors of the aminobenzimidazole class. Antimicrob Agents Chemother. 2006, 50(4): 1228-1237. https://doi.org/10.1128/AAC.50.4.1228-1237.2006
Grossman T.H., Bartels D.J., Mullin S., Gross C.H., Parsons J.D., Liao Y., Grillot A.L., Stamos D., Olson E.R., Charifson P.S., Mani N. Dual targeting of GyrB and ParE by a novel aminobenzimidazole class of antibacterial compounds. Antimicrob Agents Chemother. 2007, 51(2): 657-666. https://doi.org/10.1128/AAC.00596-06
Brycun V.N., Karpov P.A., Emec A.I., Lozinskij M.O., Bljum Ja.B. Protivotuberkuleznye svojstva proizvod nyh imidazola i benzimidazola. Zhurnal org. ta farm. himii. 2011, 9(3, 35): 3-14 [in Russian].
Koch A., Mizrahi V., Warner D.F. The impact of drug resistance on Mycobacterium tuberculosis physiology: what can we learn from rifampicin? Emerging Microbes & Infections. 2014, 3(e17): doi:10.1038/emi.2014.17. https://doi.org/10.1038/emi.2014.17
Loose M., Mitchison T.J. The bacterial cell division proteins FtsA and FtsZ self-organize into dynamic cy toskeletal patterns. Nature Cell Biology. 2014, 16: 38-46. https://doi.org/10.1038/ncb2885
Chen Y., Anderson D.E., Rajagopalan M., Erickson H.P. Assembly dynamics of Mycobacterium tuberculosis FtsZ. J Biol Chem. 2007, 282(38): 27736-27743. https://doi.org/10.1074/jbc.M703788200
White E.L., Ross L.J., Reynolds R.C., Seitz L.E., Moore G.D., Borhani D.W. Slow polymerization of Mycobacterium tuberculosis FtsZ. J Bac te riol. 2000, 182(14): 4028-4034. https://doi.org/10.1128/JB.182.14.4028-4034.2000
Kapoor S., Panda D. Targeting FtsZ for antibacterial therapy: a promising avenue. Expert Opin Ther Targets. 2009, 13(9): 1037-1051. https://doi.org/10.1517/14728220903173257
MacDonald L.M., Armson A., Thompson A.R., Rey noldson J.A. Characterisation of benzimidazole binding with recombinant tubulin from Giardia duodenalis, Ence phalitozoon intestinalis, and Cryptosporidium parvum. Mol Biochem Parasitol. 2004, 138(1): 89-96. https://doi.org/10.1016/j.molbiopara.2004.08.001
Robinson M.W., McFerran N., Trudgett A., Hoey L., Fairweather I. A possible model of benzimidazole binding to beta-tubulin disclosed by invoking an inter-domain movement. J. Mol. Graph. Model. 2004, 23(3): 275-284. https://doi.org/10.1016/j.jmgm.2004.08.001
Sambanthamoorthy K., Gokhale A.A., Lao W., Pa rashar V., Neiditch M.B., Semmelhack M.F., Lee I., Waters C.M. Identification of a novel benzimidazole that in hibits bacterial biofilm formation in a broad-spectrum manner. Antimicrob Agents Chemother. 2011, 55(9): 4369-4378. https://doi.org/10.1128/AAC.00583-11
Küçükbay H., Durmaz R., Okuyucu N., Günal S., Kazaz C. Synthesis and antibacterial activities of new bis-ben zimidazoles. Arzneimittelforschung. 2004, 54(1): 64-68. https://doi.org/10.1055/s-0031-1296938
Karpov P.A., Demchuyk O.M., Blume Ya.B., Britsun V.M., Volochnyk D.M. Discovery of new anti-TB compounds that target Mycobacterial FtsZ: highthroughput screening and molecular docking. Moscow Conference on Computational Molecular Biology (MCCMB'13). Moscow, Russia July 25-28. 2013: 223-224.
Adams D.W., Errington J. Bacterial cell division: as sembly, maintenance and disassembly of the Z ring. Nat. Rev. Microbiol. 2009, 7: 642-653. https://doi.org/10.1038/nrmicro2198
Blaauwen T.D.E.N., Buddelmeijer N., Hameete C.O.R.M., Nanninga N. Timing of FtsZ Assembly in Escherichia coli. Journal of bacreriology. 1999, 181: 5167-5175. https://doi.org/10.1128/JB.181.17.5167-5175.1999
Goehring N.W., Beckwith J. Diverse Paths to Midcell: Assembly of the Bacterial Cell Division Machinery. Current Biology. 2005, 15(13): R514-R526. https://doi.org/10.1016/j.cub.2005.06.038
Hong W., Deng W., Xie J. The Structure, Function, and Regulation of Mycobacterium FtsZ. Cell Biochem Biophys. 2013, 65(2): 97-105. https://doi.org/10.1007/s12013-012-9415-5
Król E., Scheffers D. FtsZ Polymerization Assays : Simple Protocols and Considerations. Journal of Visualized Experiments. 2013, 81: 1-13. https://doi.org/10.3791/50844
Pydiura N., Karpov P., Blume Ya. Design of specific cytoskeleton related biological database and data ma nagement environment for bioinformatical cytoskeleton in ves tigation and collaboration within virtual Grid-orga ni sa tion. Proceedings of the International Moscow Con fe ren ce on Computational Molecular Biology (MCCMB'11). July 21-24, 2011, Moscow, Rossia: 297-298.
Pydiura N., Karpov P., Blume Ya. Hardware environment for CSLabGrid: Reaching maximum efficacy of computations in structural biology and bioinformatics. Second International Conference "Cluster Computing" CC 2013 (Ukraine, Lviv, June 3-5, 2013), Ukraine, Lviv; 06/2013: 191-194.
Pydiura N., Karpov P., Blume Ya. On the Efficiency of CPU and Hybrid CPU-GPU Systems in Computational Biology Tasks. Computer Science and Applications (Ethan Publishing Company). 2014, 1(1): 48-59.
Karpov P.A., Bryrsun V.M., Rayevsky A.V., Demchuk O.M., Pydiura N.O., Ozheredov S.P., Samofalova D.A., Spivak S.I., Yemets A.I., Kalchenko V.I., Blume Ya.B. Highthroughput screening of new antimitotic compounds based on potential of Virtual Organization CSLabGrid. Nauka i innovacii (Science and Innovation). 2015, 11(1): 92-100 [in Ukrainian]. https://doi.org/10.15407/scin11.01.092
Cole S.T., Brosch R., Parkhill J., Garnier T., Churcher C.M., Harris D.E., Gordon S.V., Eiglmeier K., Gas S., Barry C.E. III, Tekaia F., Badcock K., Basham D., Brown D., Chil lingworth T., Connor R., Davies R.M., Devlin K., Barrell B.G. Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature. 1998, 393: 537-544. https://doi.org/10.1038/31159
Fleischmann R.D., Alland D., Eisen J.A., Carpenter L., White O., Peterson J.D., DeBoy R.T., Dodson R.J., Gwinn M.L., Haft D.H., Hickey E.K., Kolonay J.F., Nelson W.C., Umayam L.A., Ermolaeva M.D., Salzberg S.L., Delcher A., Utterback T.R., Fraser C.M. Whole-genome comparison of Mycobacterium tuberculosis clinical and laboratory strains J. Bacteriol. 2002, 184: 5479-5490.
https://doi.org/10.1128/JB.184.19.5479-5490.2002
The UniProt Consortium. The Universal Protein Re source (UniProt). Nucl. Acids Res. 2008, 36: 190-195. https://doi.org/10.1093/nar/gkm895
Guex N., Peitsch M.C. SWISS-MODEL and the SwissPdbViewer: An environment for comparative protein modeling. Electrophoresis. 1997, 18(15): 2714-2723. https://doi.org/10.1002/elps.1150181505
Eswar N., Marti-Renom M.A., Webb B., Madhusudhan M.S., Eramian D., Shen M.Y., Pieper U., Sali A. Comparative Protein Structure Modeling With MODELLER. Cur Prot in Bioinform, John Wiley & Sons, Inc. 2006. Sup.15: 5.6.1-5.6.30. https://doi.org/10.1002/0471250953.bi0506s15
Roy A., Kucukural A., Zhang Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nature Protocols. 2010, 5: 725-738. https://doi.org/10.1038/nprot.2010.5
Roy A., Yang J., Zhang Y. COFACTOR: An accurate com parative algorithm for structure-based protein function annotation. Nucl. Acids Res. 2012, 40: W471- W477. https://doi.org/10.1093/nar/gks372
Kuntal B.K., Aparoy P., Reddanna P. EasyModeller: A gra phical interface to MODELLER. BMC Res Notes. 2010, 3(226). doi: 10.1186/1756-0500-3-226. https://doi.org/10.1186/1756-0500-3-226
Melo F., Feytmans E. Assessing protein structures with a non-local atomic interaction energy. J. Mol. Biol. 1998, 277: 1141-1152. https://doi.org/10.1006/jmbi.1998.1665
Laskowski R.A., MacArthur M.W., Moss D.S., Thornton J.M. PROCHECK: a program to check the stereochemical quality of protein structures. J. Appl. Cryst. 1993, 26: 283-291. https://doi.org/10.1107/S0021889892009944
Chen V.B., Arendall W.B., Headd J.J., Keedy D.A., Immormino R.M., Kapral G.J., Murray L.W., Richardson J.S., Richardson D.C. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr. D. Biol. Crystallogr. 2010, 66(Pt.1): 12-21. https://doi.org/10.1107/S0907444909042073
Eisenberg D., Lüthy R., Bowie J.U. VERIFY3D: as sessment of protein models with three-dimensional profiles. Methods Enzymol. 1997, 277: 396-404. https://doi.org/10.1016/S0076-6879(97)77022-8
Zoete V., Cuendet M.A., Grosdidier A., Michielin O. SwissParam: a fast force field generation tool for small organic molecules. J. Comput. Chem. 2011, 32(11): 2359-2368. https://doi.org/10.1002/jcc.21816
Verdonk M.L., Cole J.C., Hartshorn M.J., Murray C.W., Taylor R.D. Improved protein-ligand docking using GOLD. Proteins. 2003, 52(4): 609-623. https://doi.org/10.1002/prot.10465
Hartshorn M.J., Verdonk M.L., Chessari G., Brewerton S.C., Mooij W.T., Mortenson P.N., Murray C.W. Diverse, HighQuality Test Set for the Validation of Protein-Ligand Docking Performance. J. Med. Chem. 2007, 50: 726-741. https://doi.org/10.1021/jm061277y
Huang S.-Y., Zou X. Advances and Challenges in Protein-Ligand Docking. Int. J. Mol. Sci. 2010, 11: 3016- 3034. https://doi.org/10.3390/ijms11083016
Schneider N., Lange G., Hindle S., Klein R., Rarey M. A consistent description of HYdrogen bond and DEhyd ration energies in protein-ligand complexes: methods behind the HYDE scoring function. J. Comput. Aided. Mol. Des. 2013, 27(1): 15-29. https://doi.org/10.1007/s10822-012-9626-2
Schneider N., Hindle S., Lange G., Klein R., Albrecht J., Briem H., Beyer K., Claußen H., Gastreich M., Lemmen C., Rarey R. Substantial improvements in large-scale redock ing and screening using the novel HYDE scoring function. J. Comput. Aided. Mol. Des. 2012b. 26: 701-723. https://doi.org/10.1007/s10822-011-9531-0
Hess B., Kutzner C., van der Spoel D., Lindahl E. GROMACS 4: algorithms for highly efficient, loadbalanced, and scalable molecular simulation. J. Chem. Theory Comput. 2008, 4(3): 435-447. https://doi.org/10.1021/ct700301q
Pronk S., Páll S., Schulz R., Larsson P., Bjelkmar P., Apos tolov R., Shirts M.R., Smith J.C., Kasson P.M., van der Spoel D., Hess B., Lindahl E. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics. 2013, 29(7): 845-854. https://doi.org/10.1093/bioinformatics/btt055
Vanommeslaeghe K., Hatcher E., Acharya C., Kundu S., Zhong S., Shim J., Darian E., Guvench O., Lopes P., Vorobyov I., Mackerell A.D.Jr. CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J. Comput. Chem. 2009, 31(4): 671-690. https://doi.org/10.1002/jcc.21367
Essmann U., Perera L., Berkowitz M.L., Darden T., Lee H, Pedersen L.G. A smooth particle-mesh Ewald potential. J. Chem. Phys. 1995, 103(19): 8577-8592. https://doi.org/10.1063/1.470117
Hess B., Bekker H., Berendsen H.J.C., Fraaije J.G.E.M. LINCS: a linear constraint solver for molecular simulations. J. Comput. Phys. 1997, 18: 1463-1472.
https://doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H
Almlöf M., Brandsdal B.O., Aqvist J. Binding affinity prediction with different force fields: examination of the linear interaction energy method. J. Comput. Chem. 2004, 25(10): 1242-1254. https://doi.org/10.1002/jcc.20047
Stacklies W., Seifert C., Graeter F. Implementation of force distribution analysis for molecular dynamics simulations. BMC Bioinformatics. 2011, 12(101): 1-5. https://doi.org/10.1186/1471-2105-12-101
