Molecular dynamics simulation and linear interaction energy study of d-Glu-based inhibitors of the MurD ligase
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The biosynthetic pathway of the bacterial peptidoglycan, where MurD is an enzyme involved at the intracellular stage of its construction, represents a collection of highly selective macromolecular targets for novel antibacterial drug design. In this study as part of our investigation of the MurD bacterial target two recently discovered classes of the MurD ligase inhibitors were investigated resulting from the lead optimization phases of the N-sulfonamide d-Glu MurD inhibitors. Molecular dynamics simulations, based on novel structural data, in conjunction with the linear interaction energy (LIE) method suggested the transferability of our previously obtained LIE coefficients to further d-Glu based classes of MurD inhibitors. Analysis of the observed dynamical behavior of these compounds in the MurD active site was supported by static drug design techniques. These results complement the current knowledge of the MurD inhibitory mechanism and provide valuable support for the d-Glu paradigm of the inhibitor design.
KeywordsMolecular dynamics (MD) simulations Linear interaction energy (LIE) method Structure-based pharmacophore models MurD ligase Antibacterial agents Drug design
This work was supported by the postdoctoral grant of the Ministry of Higher Education, Science and Technology of the Republic of Slovenia (Grant Number: Z1-4111).The authors would like thank Dr. Jernej Zidar and Barbara Pogorelčnik from the National institute of Chemistry, Slovenia, for their helpful technical assistance and Dr. Yasmin Aristei from Molecular Discovery Ltd. for GRID map calculations. Dr. Urban Bren from the National Institute of Chemistry, Ljubljana is acknowledged for introducing us to LIE methodology in our previous binding study of MurD inhibitors.
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- 8.Perdih A, Hodoscek M, Solmajer T (2009) MurD ligase from E. coli: Tetrahedral intermediate formation study by hybrid quantum mechanical/molecular mechanical replica path method. Proteins: Struct Funct Bioinf 74:744–759Google Scholar
- 10.Perdih A, Kotnik M, Hodoscek M, Solmajer T (2007) Targeted molecular dynamics simulation studies of binding and conformational changes in E. Coli MurD. Proteins: Struct Funct Bioinf 68:243–254Google Scholar
- 14.Kotnik M, Humljan J, Contreras-Martel C, Oblak M, Kristan K, Hervé M, Blanot D, Urleb U, Gobec S, Dessen A, Solmajer T (2007) Structural and functional characterization of enantiomeric glutamic acid derivatives as potential transition state analogue inhibitors of MurD ligase. J Mol Biol 370:107–115CrossRefGoogle Scholar
- 16.Zidar N, Tomasic T, Sink R, Rupnik V, Kovac A, Turk S, Patin D, Blanot D, Contreras Martel C, Dessen A, Müller Premru M, Zega A, Gobec S, Peterlin Masic L, Kikelj D (2010) Discovery of novel 5-benzylidenerhodanine and 5-benzylidenethiazolidine-2,4-dione inhibitors of MurD ligase. J Med Chem 53:6584–6594CrossRefGoogle Scholar
- 17.Tomašić T, Zidar N, Šink R, Kovač A, Blanot D, Contreras-Martel C, Dessen A, Müller-Premru M, Zega A, Gobec S, Kikelj D, Peterlin Mašič L (2011) Structure-based design of a new series of d-glutamic acid based inhibitors of bacterial UDP-N-acetylmuramoyl-l-alanine:d-glutamate ligase (MurD). J Med Chem 54:4600–4610Google Scholar
- 18.Sosič I, Barreteau H, Simčič M, Sink R, Cesar J, Zega A, Grdadolnik SG, Contreras-Martel C, Dessen A, Amoroso A, Joris B, Blanot D, Gobec S (2011) Second-generation sulphonamide inhibitors of d-glutamic acid-adding enzyme: activity optimisation with conformationally rigid analogues of d-glutamic acid. Eur J Med Chem 46:2880–2894CrossRefGoogle Scholar
- 22.Marelius J, Kolmodin K, Feierberg I, Åqvist J (1998) A molecular dynamics program for free energy calculations and empirical valence bond simulations in biomolecular systems. J Mol Graph Model 16:213–225Google Scholar
- 24.Gaussian 09, Revision A.1, Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, 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 JA Jr, 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 JM, 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, Gaussian, Inc., Wallingford CT, 2009Google Scholar
- 31.Christ CD, Mark AE, van Gunsteren WF (2010) Basic ingredients of free energy calculations: a review. J Comput Chem 31:1569–1582Google Scholar