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Covalent docking of selected boron-based serine beta-lactamase inhibitors

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Abstract

AmpC β-lactamase is a hydrolytic enzyme conferring resistance to β-lactam antibiotics in multiple Gram-negative bacteria. Therefore, identification of non-β-lactam compounds able to inhibit the enzyme is crucial for the development of novel antibacterial therapies. In general, AmpC inhibitors have to engage the highly solvent-exposed catalytic site of the enzyme. Therefore, understanding the implications of ligand–protein induced-fit and water-mediated interactions behind the inhibitor-enzyme recognition process is fundamental for undertaking structure-based drug design process. Here, we focus on boronic acids, a promising class of beta-lactamase covalent inhibitors. First, we optimized a docking protocol able to reproduce the experimentally determined binding mode of AmpC inhibitors bearing a boronic group. This goal was pursued (1) performing rigid and flexible docking calculations aiming to establish the role of the side chain conformations; and (2) investigating the role of specific water molecules in shaping the enzyme active site and mediating ligand protein interactions. Our calculations showed that some water molecules, conserved in the majority of the considered X-ray structures, are needed to correctly predict the binding pose of known covalent AmpC inhibitors. On this basis, we formalized our findings in a docking and scoring protocol that could be useful for the structure-based design of new boronic acid AmpC inhibitors.

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References

  1. Drawz SM, Bonomo RA (2010) Three decades of beta-lactamase inhibitors. Clin Microbiol Rev 23(20065329):160–201

    Article  CAS  Google Scholar 

  2. Drawz SM, Papp-Wallace KM, Bonomo RA (2014) New beta-lactamase inhibitors: a therapeutic renaissance in an MDR world. Antimicrob Agents Chemother 58:1835–1846

    Article  Google Scholar 

  3. Farina D, Spyrakis F, Venturelli A, Cross S, Tondi D, Costi MP (2014) The inhibition of extended spectrum β-lactamases: hits and leads. Curr Med Chem 21:1405–1434

    Article  CAS  Google Scholar 

  4. Ambler RP (1980) The structure of beta-lactamases. Philos Trans R Soc Lond B Biol Sci 289:321–331

    Article  CAS  Google Scholar 

  5. Sgrignani J, Magistrato A, Dal Peraro M, Vila AJ, Carloni P, Pierattelli R (2012) On the active site of mononuclear B1 metallo-lactamases: a computational study. J Comput Aided Mol Des 26:425–435

    Article  CAS  Google Scholar 

  6. Dal Peraro M, Carloni P (2010) Catalytic mechanism of metallo β-lactamases: insights from calculations and experiments. In: Matta F (ed) Quantum biochemistry. Wiley-VCH Verlag GmbH & Co. KGaA, New York, pp 605–622

  7. Page MI, Badarau A (2008) The mechanisms of catalysis by metallo beta-lactamases. Bioinorg Chem Appl. doi:10.1155/2008/576297

  8. Simona F, Magistrato A, Dal Peraro M, Cavalli A, Vila AJ, Carloni P (2009) Common mechanistic features among metallo-beta-lactamases: a computational study of Aeromonas hydrophila CphA enzyme. J Biol Chem 284:28164–28171

    Article  CAS  Google Scholar 

  9. Dal Peraro M, Vila AJ, Carloni P, Klein ML (2007) Role of zinc content on the catalytic efficiency of B1 metallo beta-lactamases. J Am Chem Soc 129:2808–2816

    Article  CAS  Google Scholar 

  10. Kiener PA, Waley SG (1978) Reversible inhibitors of penicillinases. Biochem J 169:197–204

    CAS  Google Scholar 

  11. Goldstein EJ, Citron DM, Tyrrell KL, Merriam CV (2013) In vitro activity of Biapenem plus RPX7009, a carbapenem combined with a serine beta-lactamase inhibitor, against anaerobic bacteria. Antimicrob Agents Chemother 57:2620–2630

    Article  CAS  Google Scholar 

  12. Warren GL, Andrews CW, Capelli A-M, Clarke B, LaLonde J, Lambert MH, Lindvall M, Nevins N, Semus SF, Senger S, Tedesco G, Wall ID, Woolven JM, Peishoff CE, Head MS (2006) A critical assessment of docking programs and scoring functions. J Med Chem 49:5912–5931

    Article  CAS  Google Scholar 

  13. Coupez B, Lewis RA (2006) Docking and scoring—theoretically easy, practically impossible? Curr Med Chem 13:2995–3003

    Article  CAS  Google Scholar 

  14. Weill N, Therrien E, Campagna-Slater V, Moitessier N (2013) Methods for docking small molecules to macromolecules: a user’s perspective. 1. Theory Curr Pharm Des 20:3338–3359

    Article  Google Scholar 

  15. Ouyang X, Zhou S, Ge Z, Li R, Kwoh CK (2013) CovalentDock Cloud: a web server for automated covalent docking. Nucl Acids Res 41(Web Server issue):W329–W332. doi:10.1093/nar/gkt406

    Article  Google Scholar 

  16. Zhu K, Borrelli KW, Greenwood JR, Day T, Abel R, Farid RS, Harder E (2014) Docking covalent inhibitors: a parameter free approach to pose prediction and scoring. J Chem Inf Model 54:1932–1940

    Article  CAS  Google Scholar 

  17. Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727–748

    Article  CAS  Google Scholar 

  18. Jones G, Willett P, Glen RC (1995) Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation. J Mol Biol 245:43–53

    Article  CAS  Google Scholar 

  19. Sgrignani J, Bonaccini C, Grazioso G, Chioccioli M, Cavalli A, Gratteri P (2009) Insights into docking and scoring neuronal alpha4beta2 nicotinic receptor agonists using molecular dynamics simulations and QM/MM calculations. J Comput Chem 30:2443–2454

    Article  CAS  Google Scholar 

  20. Lexa KW, Carlson HA (2012) Protein flexibility in docking and surface mapping. Q Rev Biophys 45:301–343

    Article  CAS  Google Scholar 

  21. Roberts BC, Mancera RL (2008) Ligand-protein docking with water molecules. J Chem Inf Model 48:397–408

    Article  CAS  Google Scholar 

  22. Kumar A, Zhang KYJ (2013) Investigation on the effect of key water molecules on docking performance in CSARdock exercise. J Chem Inf Model 53:1880–1892

    Article  CAS  Google Scholar 

  23. London N, Miller RM, Krishnan S, Uchida K, Irwin JJ, Eidam O, Gibold L, Cimermančič P, Bonnet R, Shoichet BK, Taunton J (2014) Covalent docking of large libraries for the discovery of chemical probes. Nat Chem Biol 10:1066–1072

    Article  CAS  Google Scholar 

  24. Knight JDR, Hamelberg D, McCammon JA, Kothary R (2009) The role of conserved water molecules in the catalytic domain of protein kinases. Proteins 76:527–535

    Article  CAS  Google Scholar 

  25. Powers RA, Blazquez J, Weston GS, Morosini MI, Baquero F, Shoichet BK (1999) The complexed structure and antimicrobial activity of a non-beta-lactam inhibitor of AmpC beta-lactamase. Protein Sci 8:2330–2337

    Article  CAS  Google Scholar 

  26. Caselli E, Powers RA, Blasczcak LC, Wu CY, Prati F, Shoichet BK (2001) Energetic, structural, and antimicrobial analyses of beta-lactam side chain recognition by beta-lactamases. Chem Biol 8:17–31

    Article  CAS  Google Scholar 

  27. Tondi D, Powers RA, Caselli E, Negri MC, Blázquez J, Costi MP, Shoichet BK (2001) Structure-based design and in-parallel synthesis of inhibitors of AmpC beta-lactamase. Chem Biol 8:593–611

    Article  CAS  Google Scholar 

  28. Powers RA, Caselli E, Focia PJ, Prati F, Shoichet BK (2001) Structures of ceftazidime and its transition-state analogue in complex with AmpC beta-lactamase: implications for resistance mutations and inhibitor design. Biochemistry 40:9207–9214

    Article  CAS  Google Scholar 

  29. Powers RA, Shoichet BK (2002) Structure-based approach for binding site identification on AmpC beta-lactamase. J Med Chem 45:3222–3234

    Article  CAS  Google Scholar 

  30. Chen Y, Minasov G, Roth TA, Prati F, Shoichet BK (2006) The deacylation mechanism of AmpC beta-lactamase at ultrahigh resolution. J Am Chem Soc 128:2970–2976

    Article  CAS  Google Scholar 

  31. Morandi S, Morandi F, Caselli E, Shoichet BK, Prati F (2008) Structure-based optimization of cephalothin-analogue boronic acids as beta-lactamase inhibitors. Bioorg Med Chem 16:1195–1205

    Article  CAS  Google Scholar 

  32. Tondi D, Calo S, Shoichet BK, Costi MP (2010) Structural study of phenyl boronic acid derivatives as AmpC beta-lactamase inhibitors. Bioorg Med Chem Lett 20:3416–3419

    Article  CAS  Google Scholar 

  33. Eidam O, Romagnoli C, Caselli E, Babaoglu K, Pohlhaus DT, Karpiak J, Bonnet R, Shoichet BK, Prati F (2010) Design, synthesis, crystal structures, and antimicrobial activity of sulfonamide boronic acids as beta-lactamase inhibitors. J Med Chem 53:7852–7863

    Article  CAS  Google Scholar 

  34. Eidam O, Romagnoli C, Dalmasso G, Barelier S, Caselli E, Bonnet R, Shoichet BK, Prati F (2012) Fragment-guided design of subnanomolar beta-lactamase inhibitors active in vivo. Proc Natl Acad Sci USA 109:17448–17453

    Article  CAS  Google Scholar 

  35. Frisch MJ, Trucks GW, Schlegel HB, Robb MA, Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson GA, Nakatsuji H, Caricato M, Li X, Hratchian HP, Izmaylov AF, Bloino J, Zheng G, Sonnenberg JL, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Montgomery JJA, Peralta JE, Ogliaro F, Bearpark M, Heyd JJ, Brothers E, Kudin KN, Staroverov VN, Kobayashi R, Normand J, Raghavachari K, Rendell A, Burant JC, Iyengar SS, Tomasi J, Cossi M, Rega N, Millam NJ, Klene M, Knox JE, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Martin RL, Morokuma K, Zakrzewski VG, Voth GA, Salvador P, Dannenberg JJ, Dapprich S, Daniels AD, Farkas Ö, Foresman JB, Ortiz JV, Cioslowski J, Fox DJ (2009) Gaussian 09, revision A.02. Gaussian Inc., Wallingford, CT

    Google Scholar 

  36. Becke AD (1988) Density-functional exchange-energy approximation with correct asymptotic behavior. Phys Rev A 38:3098

    Article  CAS  Google Scholar 

  37. Becke AD (1993) Density-functional thermochemistry. III. The role of exact exchange. J Chem Phys 98:5648–5652

    Article  CAS  Google Scholar 

  38. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comp Chem 30:2785–2791

    Article  CAS  Google Scholar 

  39. Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comp Chem 31:455–461

    CAS  Google Scholar 

  40. Ouyang X, Zhou S, Su CTT, Ge Z, Li R, Kwoh CK (2013) CovalentDock: automated covalent docking with parameterized covalent linkage energy estimation and molecular geometry constraints. J Comp Chem 34:326–336

    Article  CAS  Google Scholar 

  41. Hartshorn MJ, Verdonk ML, Chessari G, Brewerton SC, Mooij WTM, Mortenson PN, Murray CW (2007) Diverse, high-quality test set for the validation of protein–ligand docking performance. J Med Chem 50:726–741

    Article  CAS  Google Scholar 

  42. Clark M, Cramer RD, Van Opdenbosch N (1989) Validation of the general purpose tripos 5.2 force field. J Comp Chem 10:982–1012

    Article  CAS  Google Scholar 

  43. Verdonk ML, Chessari G, Cole JC, Hartshorn MJ, Murray CW, Nissink JW, Taylor RD, Taylor R (2005) Modeling water molecules in protein–ligand docking using GOLD. J Med Chem 48:6504–6515

    Article  CAS  Google Scholar 

  44. Case DA, Darden TA, Cheatham TEIII, Simmerling CL, Wang J, Duke RE, Luo R, Walker C, Zhang W, Merz KM, Roberts B, Hayik S, Roitberg A, Seabra G, Swails J, Goetz AW, Kolossváry I, Wong KF, Paesani F, Vanicek J, Wolf RM, Liu J, Wu X, Brozell SR, Steinbrecher T, Gohlke H, Cai Q, Ye X, Wang J, Hsieh MJ, Cui G, Roe DR, Mathews DH, Seetin MG, Salomon-Ferrer R, Sagui C, Babin V, Luchko T, Gusarov S, Kovalenko A, Kollman PA (2012) Amber 12. University of California, San Francisco

    Google Scholar 

  45. Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79:926–935

    Article  CAS  Google Scholar 

  46. For occupancy definition see http://www.ks.uiuc.edu/Research/vmd/plugins/volmapgui

  47. Essmann U, Perera L, Berkowitz ML, Darden T, Lee H, Pedersen LG (1995) A smooth particle mesh Ewald method. J Chem Phys 103:8577–8593

    Article  CAS  Google Scholar 

  48. Berendsen HJC, Postma JPM, Van Gunsteren WF, Dinola A, Haak JR (1984) J Chem Phys 81:3684

    Article  CAS  Google Scholar 

  49. de Beer SBA, Vermeulen NPE, Oostenbrink C (2010) The role of water molecules in computational drug design. Curr Top Med Chem 10:55–66

    Article  Google Scholar 

  50. De Vivo M (2011) Bridging quantum mechanics and structure-based drug design. Front Biosci 16:1619–1633

    Article  Google Scholar 

  51. Sgrignani J, Magistrato A (2013) First-principles modeling of biological systems and structure-based drug-design. Curr Comput Aided Drug Des 9:15–34

    CAS  Google Scholar 

  52. Zhu K, Borrelli KW, Greenwood JR, Day T, Abel R, Farid RS, Harder E (2014) Docking covalent inhibitors: a parameter free approach to pose prediction and scoring. J Chem Inf Mod 54:1932–1940

    Article  CAS  Google Scholar 

  53. Toledo Warshaviak D, Golan G, Borrelli KW, Zhu K, Kalid O (2014) Structure-based virtual screening approach for discovery of covalently bound ligands. J Chem Inf Mod 54:1941–1950

    Article  CAS  Google Scholar 

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Acknowledgments

We acknowledge the CINECA and the Regione Lombardia award under the LISA initiative, for the availability of high performance computing resources and support. Financial support was obtained by the Italian Ministry of Education and Research through the Flagship (PB05) “InterOmics”.

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Correspondence to Giorgio Colombo or Giovanni Grazioso.

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Sgrignani, J., Novati, B., Colombo, G. et al. Covalent docking of selected boron-based serine beta-lactamase inhibitors. J Comput Aided Mol Des 29, 441–450 (2015). https://doi.org/10.1007/s10822-015-9834-7

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