581
Views
26
CrossRef citations to date
0
Altmetric
Research Article

Toward novel inhibitors against KdsB: a highly specific and selective broad-spectrum bacterial enzyme

, , , &
Pages 1326-1345 | Received 30 Oct 2017, Accepted 16 Mar 2018, Published online: 18 Apr 2018

References

  • Abbasi, S., Raza, S., Azam, S. S., Liedl, K. R., & Fuchs, J. E. (2016). Interaction mechanisms of a melatonergic inhibitor in the melatonin synthesis pathway. Journal of Molecular Liquids, 221, 507–517. doi:10.1016/j.molliq.2016.06.034
  • Abro, A., & Azam, S. S. (2016). Binding free energy based analysis of arsenic (+ 3 oxidation state) methyltransferase with S-adenosylmethionine. Journal of Molecular Liquids, 220, 375–382. doi:10.1016/j.molliq.2016.04.109
  • Ahmad, S., Raza, S., Uddin, R., & Azam, S. S. (2017). Binding mode analysis, dynamic simulation and binding free energy calculations of the MurF ligase from Acinetobacter baumannii. Journal of Molecular Graphics and Modelling, 77, 72–85. doi:10.1016/j.jmgm.2017.07.024
  • Alavijeh, M. S., Chishty, M., Qaiser, M. Z., & Palmer, A. M. (2005). Drug metabolism and pharmacokinetics, the blood-brain barrier, and central nervous system drug discovery. NeuroRx, 2(4), 554–571. doi:10.1602/neurorx.2.4.554
  • Andersen, H. C. (1980). Molecular dynamics simulations at constant pressure and/or temperature. The Journal of Chemical Physics, 72(4), 2384–2393. doi:10.1063/1.439486
  • Andleeb, S., Rauf, M. K., Azam, S. S., Badshah, A., Sadaf, H., Raheel, A., … others. (2016). A one-pot multicomponent facile synthesis of dihydropyrimidin-2 (1 H)-thione derivatives using triphenylgermane as a catalyst and its binding pattern validation. RSC Advances, 6(83), 79651–79661. doi:10.1039/C6RA19162B
  • Baell, J. B., & Holloway, G. A. (2010). New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. Journal of Medicinal Chemistry, 53(7), 2719–2740. doi:10.1021/jm901137j
  • Baseer, S., Ahmad, S., Ranaghan, K. E., & Azam, S. S. (2017). Towards a peptide-based vaccine against Shigella sonnei: A subtractive reverse vaccinology based approach. Biologicals, 50, 87–99. doi:10.1016/j.biologicals.2017.08.004
  • Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., … Bourne, P. E. (2006). The protein data bank, 1999–. In International tables for crystallography volume F: Crystallography of biological macromolecules (pp. 675–684). Berlin: Springer. doi:10.1107/9780955360206000072210.1107/97809553602060000001
  • Case, D. A., Babin, V., Berryman, J., Betz, R. M., Cai, Q., Cerutti, D. S., … others. (2014). Amber 14. doi:10.13140/RG.2.2.17892.37766
  • Cavasotto, C. N., Orry, W., & Andrew, J. (2007). Ligand docking and structure-based virtual screening in drug discovery. Current Topics in Medicinal Chemistry, 7(10), 1006–1014. doi:10.2174/156802607780906753
  • Cipolla, L., Polissi, A., Airoldi, C., Galliani, P., Sperandeo, P., & Nicotra, F. (2009). The Kdo biosynthetic pathway toward OM biogenesis as target in antibacterial drug design and development. Current Drug Discovery Technologies, 6(1), 19–33. doi:10.2174/157016309787581093
  • Clark, M., Cramer, R. D., & Van Opdenbosch, N. (1989). Validation of the general purpose tripos 5.2 force field. Journal of Computational Chemistry, 10(8), 982–1012. doi:10.1002/jcc.540100804
  • Copeland, R. A. (2013). Evaluation of enzyme inhibitors in drug discovery: A guide for medicinal chemists and pharmacologists. Hoboken, NJ: Wiley. doi:10.1002/9781118540398
  • Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 3(7), 42717. doi:10.1038/srep42717
  • Donohue, J. (1954). Radial distribution functions of some structures of the polypeptide chain. Proceedings of the National Academy of Sciences, 40(6), 377–381.10.1073/pnas.40.6.377
  • Elengoe, A., Naser, M. A., & Hamdan, S. (2014). Modeling and docking studies on novel mutants (K71L and T204V) of the ATPase domain of human heat shock 70 kDa protein 1. International Journal of Molecular Sciences, 15(4), 6797–6814. doi:10.3390/ijms15046797
  • Flockhart, D. A., & Oesterheld, J. R. (2000). Cytochrome P450-mediated drug interactions. Child and Adolescent Psychiatric Clinics of North America, 9(1), 43–76.
  • Genheden, S., & Ryde, U. (2015). The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opinion on Drug Discovery, 10(5), 449–461. doi:10.1517/17460441.2015.1032936
  • Green, D. V. S. (2008). Virtual screening of chemical libraries for drug discovery. Expert Opinion on Drug Discovery, 3(9), 1011–1026. doi:10.1517/17460441.3.9.1011
  • Gupta, R., Pradhan, D., Jain, A. K., & Rai, C. S. (2017). TiD: Standalone software for mining putative drug targets from bacterial proteome. Genomics, 109(1), 51–57. doi:10.1016/j.ygeno.2016
  • Halgren, T. A. (1996). Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry, 17(5–6), 490–519. doi:10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P
  • Hamelberg, D., & McCammon, J. A. (2004). Standard free energy of releasing a localized water molecule from the binding pockets of proteins: Double-decoupling method. Journal of the American Chemical Society, 126(24), 7683–7689. doi:10.1021/ja0377908
  • Haq, F. U., Abro, A., Raza, S., Liedl, K. R., & Azam, S. S. (2017). Molecular dynamics simulation studies of novel β-lactamase inhibitor. Journal of Molecular Graphics and Modelling, 74, 143–152. doi:10.1016/j.jmgm.2017.03.002
  • Hemmer, M. C., Steinhauer, V., & Gasteiger, J. (1999). Deriving the 3D structure of organic molecules from their infrared spectra. Vibrational Spectroscopy, 19(1), 151–164. doi:10.1016/S0924-2031(99)00014-4
  • Hevener, K. E., Zhao, W., Ball, D. M., Babaoglu, K., Qi, J., White, S. W., & Lee, R. E. (2009). Validation of molecular docking programs for virtual screening against dihydropteroate synthase. Journal of Chemical Information and Modeling, 49(2), 444–460. doi:10.1021/ci800293n
  • Heyes, D. J., Levy, C., Lafite, P., Roberts, I. S., Goldrick, M., Stachulski, A. V., … others. (2009). Structure-based mechanism of CMP-2-keto-3-deoxymanno-octulonic acid synthetase convergent evolution of a sugar-activating enzyme with dna/rna polymerases. Journal of Biological Chemistry, 284(51), 35514–35523. doi:10.1074/jbc.M109.056630
  • Hospital, A., Goñi, J. R., Orozco, M., & Gelpli, J. L. (2015). Molecular dynamics simulations: Advances and applications. Advances and Applications in Bioinformatics and Chemistry: AABC, 8, 37. doi:10.2147/AABC.S70333
  • Hsu, L.-Y., Apisarnthanarak, A., Khan, E., Suwantarat, N., Ghafur, A., & Tambyah, P. A. (2017). Carbapenem-resistant acinetobacter baumannii and enterobacteriaceae in South and Southeast Asia. Clinical Microbiology Reviews, 30(1), 1–22. doi:10.1128/CMR.00042-16
  • Huang, B. (2009). MetaPocket: A meta approach to improve protein ligand binding site prediction. OMICS A Journal of Integrative Biology, 13(4), 325–330. doi:10.1089/omi.2009.0045
  • Hubbard, R. E., & Kamran Haider, M. (2010). Hydrogen bonds in proteins: Role and strength. eLS. doi:10.1002/9780470015902.a0003011.pub2
  • Iqbal, S., Shamim, A., Azam, S. S., & Wadood, A. (2016). Identification of potent inhibitors for chromodomain-helicase-DNA-binding protein 1-like through moleculardocking studies. Medicinal Chemistry Research, 25(12), 2924–2939.
  • John, A., Sivashanmugam, M., Umashankar, V., & Natarajan, S. K. (2017). Virtual screening, molecular dynamics, and binding free energy calculations on human carbonic anhydrase IX catalytic domain for deciphering potential leads. Journal of Biomolecular Structure and Dynamics, 35(10), 2155–2168. doi:10.1080/07391102.2017.1341337
  • Jones, G., Willett, P., Glen, R. C., Leach, A. R., & Taylor, R. (1997). Development and validation of a genetic algorithm for flexible docking. Journal of Molecular Biology, 267(3), 727–748. doi:10.1006/jmbi.1996.0897
  • Kadam, R. U., & Roy, N. (2007). Recent trends in drug-likeness prediction: A comprehensive review of in silico methods. Indian Journal of Pharmaceutical Sciences, 69(5), 609. doi:10.4103/0250-474X.38464
  • Kräutler, V., van Gunsteren, W. F., & Hünenberger, P. H. (2001). A fast SHAKE algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations. Journal of Computational Chemistry, 22(5), 501–508. doi:10.1002/1096-987X(20010415)22:5<501::AID-JCC1021>3.0.CO;2-V
  • Kumar, A., Srivastava, G., Negi, A. S., & Sharma, A. (2018). Docking, molecular dynamics, binding energy-MM-PBSA studies of naphthofuran derivatives to identify potential dual inhibitors against BACE-1 and GSK-3β. Journal of Biomolecular Structure and Dynamics, 1–37. doi:10.1080/07391102.2018.1426043
  • Lee, S. K., Chang, G. S., Lee, I. H., Chung, J. E., Sung, K. Y., & No, K. T. (2004). The PreADME: Pc-based program for batch prediction of adme properties. EuroQSAR, 2004, 5–9.
  • Leeson, P. (2012). Drug discovery: Chemical beauty contest. Nature, 481(7382), 455–456. doi:10.1038/481455a
  • Lionta, E., Spyrou, G., Vassilatis, D. K., Cournia, Z. (2014). Structure-based virtual screening for drug discovery: Principles, applications and recent advances. Current Topics in Medicinal Chemistry, 14(16), 1923–1938. doi:10.2174/1568026614666140929124445
  • Lipinski, C. A. (2004). Lead-and drug-like compounds: The rule-of-five revolution. Drug Discovery Today: Technologies, 1(4), 337–341. doi:10.1016/j.ddtec.2004.11.007
  • Ma, X., Idle, J. R., & Gonzalez, F. J. (2008). The pregnane X receptor: From bench to bedside. Expert Opinion on Drug Metabolism & Toxicology, 4(7), 895–908. doi:10.1517/17425255.4.7.895
  • Massova, I., & Kollman, P. A. (2000). Combined molecular mechanical and continuum solvent approach (MM-PBSA/GBSA) to predict ligand binding. Perspectives in Drug Discovery and Design, 18(1), 113–135.
  • Miesel, L., Greene, J., & Black, T. A. (2003). Genetic strategies for antibacterial drug discovery. Nature Reviews. Genetics, 4(6), 442. doi:10.1038/nrg1086
  • Naz, S., Farooq, U., Ali, S., Sarwar, R., Khan, S., & Abagyan, R. (2018). Identification of new benzamide inhibitor against α -subunit of tryptophan synthase from Mycobacterium tuberculosis through structure-based virtual screening, anti-tuberculosis activity and molecular dynamics simulations. Journal of Biomolecular Structure and Dynamics, 1–24. doi:10.1080/07391102.2018.144830310.1080/07391102.2018.1448303
  • Osborn, M. J. (1979). Biosynthesis and assembly of the lipopolysaccharide of the outer membrane. Bacterial Outer Membranes, 15–34, doi:10.1038/nrmicro.2016.25
  • Panman, W., Nutho, B., Chamni, S., Dokmaisrijan, S., Kungwan, N., & Rungrotmongkol, T. (2017). Computational screening of fatty acid synthase inhibitors against thioesterase domain. Journal of Biomolecular Structure and Dynamics, 1–12. doi:10.1080/07391102.2017.140849610.1080/07391102.2017.1408496
  • Paterlini, M. G., & Ferguson, D. M. (1998). Constant temperature simulations using the Langevin equation with velocity Verlet integration. Chemical Physics, 236(1), 243–252. doi:10.1016/S0301-0104(98)00214-6
  • Patil, R., Das, S., Stanley, A., Yadav, L., Sudhakar, A., & Varma, A. K. (2010). Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing. PLoS ONE, 5(8), e12029. doi:10.1371/journal.pone.0012029
  • Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF chimera – A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. doi:10.1002/jcc.20084
  • Raj, U., Kumar, H., & Varadwaj, P. K. (2017). Molecular docking and dynamics simulation study of flavonoids as BET bromodomain inhibitors. Journal of Biomolecular Structure and Dynamics, 35(11), 2351–2362. doi:10.1080/07391102.2016.1217276
  • Raza, S., Sanober, G., Rungrotmongkol, T., & Azam, S. S. (2017). The vitality of swivel domain motion in performance of enzyme i of phosphotransferase system; A comprehensive molecular dynamic study. Journal of Molecular Liquids, 242, 1184–1198. doi:10.1016/j.molliq.2017.07.086
  • Roe, D. R., & Cheatham, T. E., III (2013). PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data. Journal of Chemical Theory and Computation, 9(7), 3084–3095. doi:10.1021/ct400341p
  • Rutkowska, E., Pajak, K., & Jóźwiak, K. (2013). Lipophilicity–methods of determination and its role in medicinal chemistry. Acta Poloniae Pharmaceutica, 70(1), 3–18.
  • Shoichet, B. K. (2004). Virtual screening of chemical libraries. Nature, 432(7019), 862. doi:10.1038/nature03197
  • Shyu, C., & Ytreberg, F. M. (2009). Reducing the bias and uncertainty of free energy estimates by using regression to fit thermodynamic integration data. Journal of Computational Chemistry, 30(14), 2297–2304. doi:10.1002/jcc.21231
  • Sikander Azam, S., Wajid Abbasi, S., & Tahir, S. (2014). Investigation of novel chemical inhibitors of human lysosomal acid lipase: Virtual screening and molecular docking studies. Combinatorial Chemistry & High Throughput Screening, 17(5), 473–482. doi:10.2174/1386207317666140314093403
  • Slynko, I., Schmidtkunz, K., Rumpf, T., Klaeger, S., Heinzlmeir, S., Najar, A., … others. (2016). Identification of highly potent protein kinase C-related kinase 1 inhibitors by virtual screening, binding free energy rescoring, and in vitro testing. ChemMedChem, 11(18), 2084–2094. doi:10.1002/cmdc.201600284
  • Smyth, K. M., & Marchant, A. (2013). Conservation of the 2-keto-3-deoxymanno-octulosonic acid (Kdo) biosynthesis pathway between plants and bacteria. Carbohydrate Research, 380, 70–75. doi:10.1016/j.carres.2013.07.006
  • Todar, K. (2002). Mechanisms of bacterial pathogenicity: Endotoxins. Todar’s Online Textbook of Bacteriology.
  • Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. doi:10.1002/jcc.21334
  • Tyka, M. D., Sessions, R. B., & Clarke, A. R. (2007). Absolute free-energy calculations of liquids using a harmonic reference state. The Journal of Physical Chemistry B, 111(32), 9571–9580. doi:10.1021/jp072357w
  • Valvano, M. A., Furlong, S. E., & Patel, K. B. (2011). Genetics, biosynthesis and assembly of O-antigen. In Bacterial lipopolysaccharides (pp. 275–310). Vienna: Springer.10.1007/978-3-7091-0733-1
  • Verma, P., Tiwari, M., & Tiwari, V. (2017). In silico high-throughput virtual screening and molecular dynamics simulation study to identify inhibitor for AdeABC efflux pump of Acinetobacter baumannii. Journal of Biomolecular Structure and Dynamics, 1–13. doi:10.1080/07391102.2017.131702510.1080/07391102.2017.1418680
  • Vistoli, G., Pedretti, A., & Testa, B. (2008). Assessing drug-likeness – What are we missing? Drug Discovery Today, 13(7), 285–294. doi:10.1016/j.drudis.2007
  • Volkamer, A., Kuhn, D., Rippmann, F., & Rarey, M. (2012). DoGSiteScorer: A web server for automatic binding site prediction, analysis and druggability assessment. Bioinformatics, 28(15), 2074–2075. doi:10.1093/bioinformatics/bts310
  • Vukić, V., Hrnjez, D., Milanović, S., Iličić, M., Kanurić, K., & Petri, E. (2015). Comparative molecular modeling and docking analysis of β-galactosidase enzymes from commercially important starter cultures used in the dairy industry. Food Biotechnology, 29(3), 248–262. doi:10.1080/08905436.2015.1059766
  • Vyas, V., Jain, A., Jain, A., & Gupta, A. (2008). Virtual screening: A fast tool for drug design. Scientia Pharmaceutica, 76(3), 333–360. doi:10.3797/scipharm.0803-03
  • WHO, & others. (2017). Global priority list of antibiotic-resistant bacteria to guide research, discovery, and development of new antibiotics. Geneva: World Health Organization.
  • Wadood, A., Ghufran, M., Hassan, S. F., Khan, H., Azam, S. S., & Rashid, U. (2017). In silico identification of promiscuous scaffolds as potential inhibitors of 1-deoxy-d-xylulose 5-phosphate reductoisomerase for treatment of Falciparum malaria. Pharmaceutical Biology, 55(1), 19–32. doi:10.1080/13880209.2016.1225778
  • Weiner, P. K., & Kollman, P. A. (1981). AMBER: Assisted model building with energy refinement. A general program for modeling molecules and their interactions. Journal of Computational Chemistry, 2(3), 287–303. doi:10.1002/jcc.540020311
  • Whitfield, C., & Trent, M. S. (2014). Biosynthesis and export of bacterial lipopolysaccharides. Annual Review of Biochemistry, 83, 99–128. doi:10.1146/annurev-biochem-060713-035600
  • Willyard, C. (2017). The drug-resistant bacteria that pose the greatest health threats. Nature News, 543(7643), 15. doi:10.1038/nature.2017.21550
  • Wolber, G., & Langer, T. (2005). LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. Journal of Chemical Information and Modeling, 45(1), 160–169. doi:10.1021/ci049885e
  • Woods, C. J., Malaisree, M., Hannongbua, S., & Mulholland, A. J. (2011). A water-swap reaction coordinate for the calculation of absolute protein–ligand binding free energies. The Journal of Chemical Physics, 134(5), 02B611. doi:10.1063/1.3519057
  • Woods, C. J., Malaisree, M., Long, B., McIntosh-Smith, S., & Mulholland, A. J. (2013). Computational assay of H7N9 influenza neuraminidase reveals R292K mutation reduces drug binding affinity. Scientific Reports, 3, 3561. doi:10.1038/srep03561
  • Woods, C. J., Malaisree, M., Michel, J., Long, B., McIntosh-Smith, S., & Mulholland, A. J. (2014). Rapid decomposition and visualisation of protein–ligand binding free energies by residue and by water. Faraday Discussions, 169, 477–499. doi:10.1039/C3FD00125C
  • Yi, L. (2009). Studies of 3-deoxy-D-manno-octulosonate 8-phosphate phosphatase: Mechanistic insights and a gene fusion example. Arbor: University of Michigan.
  • Yu, H., Zou, B., Wang, X., & Li, M. (2016). Investigation of miscellaneous hERG inhibition in large diverse compound collection using automated patch-clamp assay. Acta Pharmacologica Sinica, 37(1), 111. doi:10.1038/aps.2015.143
  • Zvelebil, M. J., Barton, G. J., Taylor, W. R., & Sternberg, M. J. E. (1987). Prediction of protein secondary structure and active sites using the alignment of homologous sequences. Journal of Molecular Biology, 195(4), 957–961. doi:10.1016/0022-2836(87)90501-8

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.