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Theoretical characterization of the shikimate 5-dehydrogenase reaction from Mycobacterium tuberculosis by hybrid QC/MM simulations and quantum chemical descriptors

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Abstract

In this study, we have investigated the enzyme shikimate 5-dehydrogenase from the causative agent of tuberculosis, Mycobacterium tuberculosis. We have employed a mixture of computational techniques, including molecular dynamics, hybrid quantum chemical/molecular mechanical potentials, relaxed surface scans, quantum chemical descriptors and free-energy simulations, to elucidate the enzyme’s reaction pathway. Overall, we find a two-step mechanism, with a single transition state, that proceeds by an energetically uphill hydride transfer, followed by an energetically downhill proton transfer. Our mechanism and calculated free energy barrier for the reaction, 64.9 kJ mol− 1, are in good agreement with those predicted from experiment. An analysis of quantum chemical descriptors along the reaction pathway indicated a possibly important, yet currently unreported, role of the active site threonine residue, Thr65.

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References

  1. Aleksandrov A, Field M (2012) A hybrid elastic band string algorithm for studies of enzymatic reactions. Phys Chem Chem Phys 14(36):12,544–12,553

    CAS  Google Scholar 

  2. Alturki MS, Fuanta NR, Jarrard MA, Hobrath JV, Goodwin DC, Rants’o TA, Calderón AI (2018) A multifaceted approach to identify non-specific enzyme inhibition: application to mycobacterium tuberculosis shikimate kinase. Bioorg Med Chem Lett 28(4):802–808

    CAS  PubMed  Google Scholar 

  3. Bachega JFR, Timmers LFS, Assirati L, Bachega LR, Field MJ, Wymore T (2013) Gtkdynamo: a pymol plug-in for qc/mm hybrid potential simulations. J Comput Chem 34(25):2190–2196

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Becke AD (1993) Density-functional thermochemistry. iii. the role of exact exchange. J Chem Phys 98(7):5648–5652. https://doi.org/10.1063/1.464913

    Article  CAS  Google Scholar 

  5. Berendsen HJ, Jv Postma, Van Gunsteren WF, DiNola A, Haak JR (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 81(8):3684–3690

    CAS  Google Scholar 

  6. Bussi G, Donadio D, Parrinello M (2007) Canonical sampling through velocity rescaling. J Chem Phys 126(1):014–101

    Google Scholar 

  7. Da Silva AWS, Vranken WF (2012) Acpype-antechamber python parser interface. BMC Res Notes 5(1):367

    Google Scholar 

  8. DeLano WL, et al. (2002) Pymol: an open-source molecular graphics tool. CCP4 Newslett Prot Crystallograp 40(1):82–92

    Google Scholar 

  9. Dewar MJ, Zoebisch EG, Healy EF, Stewart JJ (1985) Development and use of quantum mechanical molecular models. 76. am1: a new general purpose quantum mechanical molecular model. J Am Chem Soc 107(13):3902–3909

    CAS  Google Scholar 

  10. Field MJ (2007) A practical introduction to the simulation of molecular systems. Cambridge University Press, Cambridge

    Google Scholar 

  11. Field MJ (2008) The pdynamo program for molecular simulations using hybrid quantum chemical and molecular mechanical potentials. J Chem Theory Comput 4(7):1151–1161

    CAS  PubMed  Google Scholar 

  12. Fonseca IO, Silva RG, Fernandes CL, de Souza ON, Basso LA, Santos DS (2007) Kinetic and chemical mechanisms of shikimate dehydrogenase from mycobacterium tuberculosis. Arch Biochem Biophys 457(2):123–133

    CAS  PubMed  Google Scholar 

  13. Fukushima K, Wada M, Sakurai M (2008) An insight into the general relationship between the three dimensional structures of enzymes and their electronic wave functions: Implication for the prediction of functional sites of enzymes. Proteins: Struct Func 71(4):1940–1954. https://doi.org/10.1002/prot.21865

    Article  CAS  Google Scholar 

  14. Gan J, Wu Y, Prabakaran P, Gu Y, Li Y, Andrykovitch M, Liu H, Gong Y, Yan H, Ji X (2007) Structural and biochemical analyses of shikimate dehydrogenase aroe from aquifex aeolicus: implications for the catalytic mechanism. Biochemistry 46(33):9513–9522

    CAS  PubMed  Google Scholar 

  15. Geerlings P, De Proft F, Langenaeker W (2003) Conceptual density functional theory. Chem Rev 103(5):1793–1874

    CAS  PubMed  Google Scholar 

  16. Grillo IB, Urquiza-Carvalho G, Bachega JFR, Rocha GB (2020a) Elucidating enzymatic catalysis using fast quantum chemical descriptors. J Chem Theory Comput

  17. Grillo IB, Urquiza-Carvalho GA, Chaves EJF, Rocha GB (2020b) Semiempirical methods do fukui functions: unlocking a modeling framework for biosystems. J Comput Chem 41(9):862–873

    CAS  PubMed  Google Scholar 

  18. Hanwell MD, Curtis DE, Lonie DC, Vandermeersch T, Zurek E, Hutchison GR (2012) Avogadro: an advanced semantic chemical editor, visualization, and analysis platform. J Cheminformatics 4(1):17

    CAS  Google Scholar 

  19. Herrmann KM, Weaver LM (1999) The shikimate pathway. Annu Rev Plant Biol 50(1):473–503

    CAS  Google Scholar 

  20. Hess B, Bekker H, Berendsen HJ, Fraaije JG (1997) Lincs: a linear constraint solver for molecular simulations. J Comput Chem 18(12):1463–1472

    CAS  Google Scholar 

  21. Holmberg N, Ryde U, Bülow L (1999) Redesign of the coenzyme specificity in l-lactate dehydrogenase from bacillus stearothermophilus using site-directed mutagenesis and media engineering. Protein Eng 12(10):851–856

    CAS  PubMed  Google Scholar 

  22. van der Kamp MW, Mulholland AJ (2008) Computational enzymology: insight into biological catalysts from modelling. Nat Prod Rep 25(6):1001–1014

    PubMed  Google Scholar 

  23. Khandogin J, Musier-Forsyth K, York DM (2003) Insights into the regioselectivity and rna-binding affinity of hiv-1 nucleocapsid protein from linear-scaling quantum methods. J Mol Biol 330(5):993–1004

    CAS  PubMed  Google Scholar 

  24. Mehra R, Rajput VS, Gupta M, Chib R, Kumar A, Wazir P, Khan IA, Nargotra A (2016) Benzothiazole derivative as a novel mycobacterium tuberculosis shikimate kinase inhibitor: identification and elucidation of its allosteric mode of inhibition. J Chem Inf Model 56(5):930–940

    CAS  PubMed  Google Scholar 

  25. Nam K, Cui Q, Gao J, York DM (2007) Specific reaction parametrization of the am1/d hamiltonian for phosphoryl transfer reactions: h, o, and p atoms. J Chem Theory Comput 3(2):486–504

    CAS  PubMed  Google Scholar 

  26. Neese F (2012) The orca program system. Wiley Interdiscip Rev Comput Mol Sci 2(1):73–78

    CAS  Google Scholar 

  27. Olsson MH, CR Søndergaard, Rostkowski M, Jensen JH (2011) Propka3: consistent treatment of internal and surface residues in empirical p k a predictions. J Chem Theory Comput 7(2):525–537

    CAS  PubMed  Google Scholar 

  28. Organization WH, et al. (2018) Global tuberculosis report. http://www.who.int/tb/publications/global_report/en/

  29. Parish T, Stoker NG (2002) The common aromatic amino acid biosynthesis pathway is essential in mycobacterium tuberculosis. Microbiology 148(10):3069–3077

    CAS  PubMed  Google Scholar 

  30. Parr RG, Yang W (1984) Density functional approach to the frontier-electron theory of chemical reactivity. J Ame Chem Soc 106(14):4049–4050

    CAS  Google Scholar 

  31. Parr RG, Donnelly RA, Levy M, Palke WE (1978) Electronegativity: the density functional viewpoint. J Chem Phys 68(8):3801–3807

    CAS  Google Scholar 

  32. Pearson RG (1987) Recent advances in the concept of hard and soft acids and bases. J Chem Educ 64(7):561. https://doi.org/10.1021/ed064p561

    Article  CAS  Google Scholar 

  33. Peek J, Lee J, Hu S, Senisterra G, Christendat D (2011) Structural and mechanistic analysis of a novel class of shikimate dehydrogenases: evidence for a conserved catalytic mechanism in the shikimate dehydrogenase family. Biochemistry 50(40):8616–8627

    CAS  PubMed  Google Scholar 

  34. Petersen GO, Saxena S, Renuka J, Soni V, Yogeeswari P, Santos DS, Bizarro CV, Sriram D (2015) Structure-based virtual screening as a tool for the identification of novel inhibitors against mycobacterium tuberculosis 3-dehydroquinate dehydratase. J Mol Graph Model 60:124–131

    CAS  PubMed  Google Scholar 

  35. Rocha GB, Freire RO, Simas AM, Stewart JJ (2006) Rm1: a reparameterization of am1 for h, c, n, o, p, s, f, cl, br, and i. J Comput Chem 27(10):1101–1111

    CAS  PubMed  Google Scholar 

  36. Schönbrunn E, Eschenburg S, Shuttleworth WA, Schloss JV, Amrhein N, Evans JN, Kabsch W (2001) Interaction of the herbicide glyphosate with its target enzyme 5-enolpyruvylshikimate 3-phosphate synthase in atomic detail. PNAS 98(4):1376–1380

    PubMed  Google Scholar 

  37. Steinrücken H, Amrhein N (1980) The herbicide glyphosate is a potent inhibitor of 5-enolpyruvylshikimic acid-3-phosphate synthase. Biochem Bioph Res Co 94(4):1207–1212

    Google Scholar 

  38. Stewart JJ (1991) Optimization of parameters for semiempirical methods. iii extension of pm3 to be, mg, zn, ga, ge, as, se, cd, in, sn, sb, te, hg, tl, pb, and bi. J Comput Chem 12(3):320–341

    CAS  Google Scholar 

  39. Stewart JJ (2009) Application of the pm6 method to modeling proteins. J Mol Model 15 (7):765–805

    CAS  PubMed  Google Scholar 

  40. Timmers LFSM, Neto AM, Montalvão R W, Basso LA, Santos DS, de Souza ON (2017) Epsp synthase flexibility is determinant to its function: computational molecular dynamics and metadynamics studies. J Mol Model 23(7):197

    PubMed  Google Scholar 

  41. Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJ (2005) Gromacs: fast, flexible, and free. J Comput Chem 26(16):1701–1718

    PubMed  Google Scholar 

  42. Wolfenden R, Snider MJ (2001) The depth of chemical time and the power of enzymes as catalysts. CC Chem Res 34(12):938– 945

    CAS  Google Scholar 

  43. Yao J, Wang X, Luo H, Gu P (2017) Understanding the catalytic mechanism and the nature of the transition state of an attractive drug-target enzyme (shikimate kinase) by quantum mechanical/molecular mechanical (qm/mm) studies. CHEM-EUR J 23(64):16,380–16,387

    CAS  Google Scholar 

  44. Ye S, von Delft F, Brooun A, Knuth MW, Swanson RV, McRee DE (2003) The crystal structure of shikimate dehydrogenase (aroe) reveals a unique nadph binding mode. J Bacteriology 185 (14):4144–4151

    CAS  Google Scholar 

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Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior - Brasil (CAPES) - Finance Code 001. LFSMT acknowledges postdoctoral scholarship awarded by CAPES, and JFRB acknowledges postdoctoral scholarship (DOCFIX) awarded by CAPES and FAPERGS. Instituto Nacional de Ciência e Tecnologia de Nanotecnologia para Marcadores Integrados (INCT-INAMI), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), CAPES, Fundação de Apoio á Pesquisa do Estado da Paraíba (FAPESQ-PB), Programa de Apoio a Núcleos de Excelência (PRONEX-FACEPE), and Financiadora de Estudos e Projetos (FINEP). The authors also acknowledge the physical structure and computational support provided by Universidade Federal da Paraíba (UFPB) and the computer resources of Centro Nacional de Processamento de Alto Desempenho em São Paulo (CENAPAD-SP). This study was financed in part by CAPES through the research project Bioinformática Estrutural de Proteínas: Modelos, Algoritmos e Aplicações Biotecnológicas (Edital Biologia Computacional 51/2013, processo AUXPE1375/2014 da CAPES). G.B.R. acknowledges support from the Brazilian National Council for Scientific and Technological Development (CNPq grant no. 309761/2017-4).

Author information

Author notes

  1. José Fernando Ruggiero Bachega

    Present address: Departamento de Farmacociências, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Brazil

  2. José Fernando Ruggiero Bachega

    Present address: Centro de Biotecnologia da Universidade Federal do Rio Grande do Sul (CBiot/UFRGS), Programa de Pós-graduação em Biologia Celular e Molecular (PPGBCM), Av. Bento Gonçalves, 9500, Bairro Agronomia, CEP 91501-970, Porto Alegre, Rio Grande do Sul, Brazil

  3. Luis Fernando S. M. Timmers

    Present address: Programa de Pós-Graduação em Biotecnologia (PPGBiotec), Universidade do Vale do Taquari - Univates, Rua Avelino Talini, 171 - Bairro Universitário, Lajeado, RS, Brazil

Authors and Affiliations

  1. Departamento de Química, Centro de Ciências Exatas e da Natureza Universidade Federal da Paraíba, João Pessoa, Brazil

    Igor Barden Grillo & Gerd Bruno Rocha

  2. Laboratório de Bioinformática, Modelagem e Simulação de Biossistemas (LABIO), Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS) Programa de Pós-Graduação em Biologia Celular e Molecular, Av. Ipiranga 6681, Porto Alegre, RS, 90619-900, Brazil

    José Fernando Ruggiero Bachega, Luis Fernando S. M. Timmers & Osmar Norberto de Souza

  3. Departamento de Farmacociências, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Programa de Pós-Graduação em Ciências da Saúde (PPGCS) e Programa de Pós-Graduação em Biociências (PPGBio), Porto Alegre, Brazil

    Rafael A. Caceres

  4. Programa de Pós-Graduação em Biologia Celular e Molecular, Av. Ipiranga 6681, Porto Alegre, RS, 90619-900, Brazil

    Osmar Norberto de Souza

  5. Laboratoire de Chimie et Biologie des Métaux, UMR5249, Université Grenoble I, CEA, CNRS, 17 avenue des Martyrs, 38054 Cedex 9, Grenoble, France

    Martin J. Field

  6. Theory Group, Institut Laue-Langevin, 71 avenue des Martyrs CS 20156, 38042 Cedex 9, Grenoble, France

    Martin J. Field

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  1. Igor Barden Grillo
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  2. José Fernando Ruggiero Bachega
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Correspondence to Igor Barden Grillo.

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This paper belongs to Topical Collection XX-Brazilian Symposium of Theoretical Chemistry (SBQT2019)

Igor Barden Grillo and José Fernando Ruggiero Bachega are co-first authors.

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Grillo, I.B., Bachega, J.F.R., Timmers, L.F.S.M. et al. Theoretical characterization of the shikimate 5-dehydrogenase reaction from Mycobacterium tuberculosis by hybrid QC/MM simulations and quantum chemical descriptors. J Mol Model 26, 297 (2020). https://doi.org/10.1007/s00894-020-04536-9

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