Molecular Modeling of Multidrug Properties of Resistance Nodulation Division (RND) Transporters

  • Pierpaolo Cacciotto
  • Venkata K. Ramaswamy
  • Giuliano Malloci
  • Paolo Ruggerone
  • Attilio V. VargiuEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1700)


Efflux pumps of the resistance nodulation division (RND) superfamily are among the major contributors to intrinsic and acquired multidrug resistance in Gram-negative bacteria. Structural information on AcrAB-TolC and MexAB-OprM, major efflux pumps of Escherichia coli and Pseudomonas aeruginosa respectively, boosted intensive research aimed at understanding the molecular mechanisms ruling the active extrusion processes. In particular, several studies were devoted to the understanding of the determinants behind the extraordinary broad specificity of the RND transporters AcrB and MexB. In this chapter, we discuss the ever-growing role computational methods have been playing in deciphering key structural and dynamical features of these transporters and of their interaction with substrates and inhibitors. We further discuss and illustrate examples from our lab of how molecular docking, homology modeling, all-atom molecular dynamics simulations and in silico free energy estimations can all together give precious insights into the processes of recognition and extrusion of substrates, as well as on the possible inhibition strategies.

Key words

Efflux pumps Gram-negative bacteria Membrane proteins RND transporters MD simulations Molecular docking Homology modeling Free energy calculations MM/GBSA 



The research leading to the results discussed here was partly conducted as part of the Translocation Consortium ( and has received support from the Innovative Medicines Joint Undertaking under Grant Agreement no. 115525, resources, which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution. VKR is a Marie Skłodowska-Curie fellow within the “Translocation” Network, project no. 607694.


  1. 1.
    Antimicrobial resistance: global report on surveillance (2014) World Health OrganizationGoogle Scholar
  2. 2.
    Livermore DM (2004) The need for new antibiotics. Clin Microbiol Infect 10:1–9PubMedCrossRefGoogle Scholar
  3. 3.
    Bush K, Courvalin P, Dantas G, Davies J, Eisenstein B, Huovinen P, Jacoby GA, Kishony R, Kreiswirth BN, Kutter E, Lerner SA, Levy S, Lewis K, Lomovskaya O, Miller JH, Mobashery S, Piddock LJV, Projan S, Thomas CM, Tomasz A, Tulkens PM, Walsh TR, Watson JD, Witkowski J, Witte W, Wright G, Yeh P, Zgurskaya HI (2011) Tackling antibiotic resistance. Nat Rev Microbiol 9:894–896PubMedPubMedCentralCrossRefGoogle Scholar
  4. 4.
    Bassetti M, Merelli M, Temperoni C, Astilean A (2013) New antibiotics for bad bugs: where are we? Ann Clin Microbiol Antimicrob 12:22PubMedPubMedCentralCrossRefGoogle Scholar
  5. 5.
    Rex JH, Goldberger M, Eisenstein BI, Harney C (2014) The evolution of the regulatory framework for antibacterial agents. Ann N Y Acad Sci 1323:11–21PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Taubes G (2008) The bacteria fight back. Science 321:356–361PubMedCrossRefGoogle Scholar
  7. 7.
    Pitout JDD (2010) The latest threat in the war on antimicrobial resistance. Lancet Infect Dis 10(9):578PubMedCrossRefGoogle Scholar
  8. 8.
    Poole K, Krebes K, Mcnally C, Neshat S (1993) Multiple antibiotic-resistance in pseudomonas-aeruginosa – evidence for involvement of an efflux operon. J Bacteriol 175:7363–7372PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Li XM, Zolli-Juran M, Cechetto JD, Daigle DM, Wright GD, Brown ED (2004) Multicopy suppressors for novel antibacterial compounds reveal targets and drug efflux susceptibility. Chem Biol 11:1423–1430PubMedCrossRefGoogle Scholar
  10. 10.
    Piddock LJV (2006) Clinically relevant chromosomally encoded multidrug resistance efflux pumps in bacteria. Clin Microbiol Rev 19:382–402PubMedPubMedCentralCrossRefGoogle Scholar
  11. 11.
    Nikaido H (2009) Multidrug resistance in bacteria. Annu Rev Biochem 78:119–146PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Poole K (2011) Pseudomonas aeruginosa: resistance to the max. Front Microbiol 2:65. PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    Nikaido H, Pagès J-M (2012) Broad-specificity efflux pumps and their role in multidrug resistance of Gram-negative bacteria. FEMS Microbiol Rev 36:340–363PubMedCrossRefGoogle Scholar
  14. 14.
    Schweizer HP (2012) Understanding efflux in Gram-negative bacteria: opportunities for drug discovery. Expert Opin Drug Discov 7:633–642PubMedCrossRefGoogle Scholar
  15. 15.
    Ruggerone P, Murakami S, Pos KM, Vargiu AV (2013) RND efflux pumps: structural information translated into function and inhibition mechanisms. Curr Top Med Chem 13:3079–3100PubMedCrossRefGoogle Scholar
  16. 16.
    Blair JMA, Richmond GE, Piddock LJV (2014) Multidrug efflux pumps in Gram-negative bacteria and their role in antibiotic resistance. Future Microbiol 9:1165–1177PubMedCrossRefGoogle Scholar
  17. 17.
    Li X-Z, Plésiat P, Nikaido H (2015) The challenge of efflux-mediated antibiotic resistance in Gram-negative bacteria. Clin Microbiol Rev 28:337–418PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Dinh T, Paulsen IT, Saier MH (1994) A family of extracytoplasmic proteins that allow transport of large molecules across the outer membranes of Gram-negative bacteria. J Bacteriol 176:3825–3831PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Nikaido H (1996) Multidrug efflux pumps of gram-negative bacteria. J Bacteriol 178:5853–5859PubMedPubMedCentralCrossRefGoogle Scholar
  20. 20.
    Tikhonova EB, Zgurskaya HI (2004) AcrA, AcrB, and TolC of Escherichia coli form a stable intermembrane multidrug efflux complex. J Biol Chem 279:32116–32124PubMedCrossRefGoogle Scholar
  21. 21.
    Lobedanz S, Bokma E, Symmons MF, Koronakis E, Hughes C, Koronakis V (2007) A periplasmic coiled-coil interface underlying ToIC recruitment and the assembly of bacterial drug eff lux pumps. Proc Natl Acad Sci U S A 104:4612–4617PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Symmons MF, Bokma E, Koronakis E, Hughes C, Koronakis V (2009) The assembled structure of a complete tripartite bacterial multidrug efflux pump. Proc Natl Acad Sci U S A 106:7173–7178PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Pos KM (2009) Trinity revealed: stoichiometric complex assembly of a bacterial multidrug efflux pump. Proc Natl Acad Sci U S A 106:6893–6894PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Su CC, Long F, Zimmermann MT, Rajashankar KR, Jernigan RL, Yu EW (2011) Crystal structure of the CusBA heavy-metal efflux complex of Escherichia coli. Nature 470:558–562PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Du D, Wang Z, James NR, Voss JE, Klimont E, Ohene-Agyei T, Venter H, Chiu W, Luisi BF (2014) Structure of the AcrAB-TolC multidrug efflux pump. Nature 509:512–515PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Jin-Sik K, Hyeongseop J, Saemee S, Hye-Yeon K, Kangseok L, Jaekyung H, And Nam-Chul H (2015) Structure of the tripartite multidrug efflux pump AcrAB-TolC suggests an alternative assembly mode. Mol Cells 38:180–186CrossRefGoogle Scholar
  27. 27.
    Zgurskaya HI, Weeks JW, Ntreh AT, Nickels LM, Wolloscheck D (2015) Mechanism of coupling drug transport reactions located in two different membranes. Front Microbiol 6:100PubMedPubMedCentralGoogle Scholar
  28. 28.
    Du D, Van Veen HW, Luisi BF (2015) Assembly and operation of bacterial tripartite multidrug efflux pumps. Trends Microbiol 23:311–319PubMedCrossRefGoogle Scholar
  29. 29.
    Zgurskaya HI, Nikaido H (1999) Bypassing the periplasm: reconstitution of the AcrAB multidrug efflux pump of Escherichia coli. Proc Natl Acad Sci U S A 96:7190–7195PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Murakami S, Nakashima R, Yamashita E, Yamaguchi A (2002) Crystal structure of bacterial multidrug efflux transporter AcrB. Nature 419:587–593PubMedCrossRefGoogle Scholar
  31. 31.
    Murakami S, Nakashima R, Yamashita E, Matsumoto T, Yamaguchi A (2006) Crystal structures of a multidrug transporter reveal a functionally rotating mechanism. Nature 443:173–179PubMedCrossRefGoogle Scholar
  32. 32.
    Seeger MA, Schiefner A, Eicher T, Verrey F, Diederichs K, Pos KM (2006) Structural asymmetry of AcrB trimer suggests a peristaltic pump mechanism. Science 313:1295–1298PubMedCrossRefGoogle Scholar
  33. 33.
    Sennhauser G, Amstutz P, Briand C, Storchenegger O, Grutter MG (2007) Drug export pathway of multidrug exporter AcrB revealed by DARPin inhibitors. PLoS Biol 5:106–113CrossRefGoogle Scholar
  34. 34.
    Sennhauser G, Bukowska MA, Briand C, Grutter MG (2009) Crystal structure of the multidrug exporter MexB from Pseudomonas aeruginosa. J Mol Biol 389:134–145PubMedCrossRefGoogle Scholar
  35. 35.
    Mazzariol A, Cornaglia G, Nikaido H (2000) Contributions of the AmpC beta-lactamase and the AcrAB multidrug efflux system in intrinsic resistance of Escherichia coli K-12 to beta-lactams. Antimicrob Agents Chemother 44:1387–1390PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Elkins CA, Nikaido H (2002) Substrate specificity of the RND-type multidrug efflux pumps AcrB and AcrD of Escherichia coli is determined predominately by two large periplasmic loops. J Bacteriol 184:6490–6498PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Baucheron S, Imberechts H, Chaslus-Dancla E, Cloeckaert A (2002) The AcrB multidrug transporter plays a major role in high-level fluoroquinolone resistance in salmonella enterica serovar typhimurium phage type DT204. Microb Drug Resist 8:281–289PubMedCrossRefGoogle Scholar
  38. 38.
    Middlemiss JK, Poole K (2004) Differential impact of MexB mutations on substrate selectivity of the MexAB-OprM multidrug efflux pump of Pseudomonas aeruginosa. J Bacteriol 186:1258–1269PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Kinana AD, Vargiu AV, Nikaido H (2013) Some ligands enhance the efflux of other ligands by the Escherichia coli multidrug pump AcrB. Biochemistry 52:8342–8351PubMedPubMedCentralCrossRefGoogle Scholar
  40. 40.
    Kobayashi N, Tamura N, Van Veen HW, Yamaguchi A, Murakami S (2014) β-Lactam selectivity of multidrug transporters AcrB and AcrD resides in the proximal binding pocket. J Biol Chem 289:10680–10690PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Koronakis V, Sharff A, Koronakis E, Luisi B, Hughes C (2000) Crystal structure of the bacterial membrane protein TolC central to multidrug efflux and protein export. Nature 405:914–919PubMedCrossRefGoogle Scholar
  42. 42.
    Higgins MK, Eswaran J, Edwards P, Schertler GFX, Hughes C, Koronakis V (2004) Structure of the ligand-blocked periplasmic entrance of the bacterial multidrug efflux protein TolC. J Mol Biol 342:697–702PubMedCrossRefGoogle Scholar
  43. 43.
    Phan G, Benabdelhak H, Lascombe MB, Benas P, Rety S, Picard M, Ducruix A, Etchebest C, Broutin I (2010) Structural and dynamical insights into the opening mechanism of P. aeruginosa OprM channel. Structure 18:507–517PubMedCrossRefGoogle Scholar
  44. 44.
    Akama H, Kanemaki M, Yoshimura M, Tsukihara T, Kashiwagi T, Yoneyama H, Narita S, Nakagawa A, Nakae T (2004) Crystal structure of the drug discharge outer membrane protein, OprM, of Pseudomonas aeruginosa – dual modes of membrane anchoring and occluded cavity end. J Biol Chem 279:52816–52819PubMedCrossRefGoogle Scholar
  45. 45.
    Bavro VN, Pietras Z, Furnham N, Perez-Cano L, Fernandez-Recio J, Pei XY, Misra R, Luisi B (2008) Assembly and channel opening in a bacterial drug efflux machine. Mol Cell 30:114–121PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Poole K (2001) Multidrug resistance in Gram-negative bacteria. Curr Opin Microbiol 4:500–508PubMedCrossRefGoogle Scholar
  47. 47.
    Akama H, Matsuura T, Kashiwagi S, Yoneyama H, Narita SI, Tsukihara T, Nakagawa A, Nakae T (2004) Crystal structure of the membrane fusion protein, MexA, of the multidrug transporter in Pseudomonas aeruginosa. J Biol Chem 279:25939–25942PubMedCrossRefGoogle Scholar
  48. 48.
    Higgins MK, Bokma E, Koronakis E, Hughes C, Koronakis V (2004) Structure of the periplasmic component of a bacterial drug efflux pump. Proc Natl Acad Sci U S A 101:9994–9999PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Mikolosko J, Bobyk K, Zgurskaya HI, Ghosh P (2006) Conformational flexibility in the multidrug efflux system protein AcrA. Structure 14:577–587PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Xu Y, Lee M, Moeller A, Song S, Yoon B-Y, Kim H-M, Jun S-Y, Lee K, Ha N-C (2011) Funnel-like hexameric assembly of the periplasmic adapter protein in the tripartite multidrug efflux pump in Gram-negative bacteria. J Biol Chem 286:17910–17920PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Hobbs EC, Yin X, Paul BJ, Astarita JL, Storz G (2012) Conserved small protein associates with the multidrug efflux pump AcrB and differentially affects antibiotic resistance. Proc Natl Acad Sci U S A 109:16696–16701PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Elkins CA, Nikaido H (2003) Chimeric analysis of AcrA function reveals the importance of its c-terminal domain in its interaction with the AcrB multidrug efflux pump. J Bacteriol 185:5349–5356PubMedPubMedCentralCrossRefGoogle Scholar
  53. 53.
    Elkins CA, Nikaido H (2003) 3D structure of AcrB: the archetypal multidrug efflux transporter of Escherichia coli likely captures substrates from periplasm. Drug Resist Updat 6:9–13PubMedCrossRefGoogle Scholar
  54. 54.
    Trépout S, Taveau J-C, Benabdelhak H, Granier T, Ducruix A, Frangakis AS, Lambert O (2010) Structure of reconstituted bacterial membrane efflux pump by cryo-electron tomography. BBA-Biomembranes 1798:1953–1960PubMedCrossRefGoogle Scholar
  55. 55.
    Nakashima R, Sakurai K, Yamasaki S, Nishino K, Yamaguchi A (2011) Structures of the multidrug exporter AcrB reveal a proximal multisite drug-binding pocket. Nature 480:565–569PubMedGoogle Scholar
  56. 56.
    Pei X-Y, Hinchliffe P, Symmons MF, Koronakis E, Benz R, Hughes C, Koronakis V (2011) Structures of sequential open states in a symmetrical opening transition of the TolC exit duct. Proc Natl Acad Sci U S A 108:2112–2117PubMedPubMedCentralCrossRefGoogle Scholar
  57. 57.
    Xu Y, Moeller A, Jun S-Y, Le M, Yoon B-Y, Kim J-S, Lee K, Ha N-C (2012) Assembly and channel opening of outer membrane protein in tripartite drug efflux pumps of Gram-negative bacteria. J Biol Chem 287:11740–11750PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    Hinchliffe P, Symmons MF, Hughes C, Koronakis V (2013) Structure and operation of bacterial tripartite pumps. Annu Rev Microbiol 67(67):221–242PubMedCrossRefGoogle Scholar
  59. 59.
    Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749PubMedCrossRefGoogle Scholar
  60. 60.
    Nissink JWM, Murray C, Hartshorn M, Verdonk ML, Cole JC, Taylor R (2002) A new test set for validating predictions of protein-ligand interaction. Proteins 49:457–471PubMedCrossRefGoogle Scholar
  61. 61.
    Jorgensen WL (2004) The many roles of computation in drug discovery. Science 303:1813–1818PubMedCrossRefGoogle Scholar
  62. 62.
    Van Gunsteren WF, Bakowies D, Baron R, Chandrasekhar I, Christen M, Daura X, Gee P, Geerke DP, Glattli A, Hunenberger PH, Kastenholz MA, Ostenbrink C, Schenk M, Trzesniak D, Van Der Vegt NFA, Yu HB (2006) Biomolecular modeling: goals, problems, perspectives. Angew Chem Int Ed 45:4064–4092CrossRefGoogle Scholar
  63. 63.
    Dodson GG, Lane DP, Verma CS (2008) Molecular simulations of protein dynamics: new windows on mechanisms in biology. EMBO Rep 9:144–150PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Lee EH, Hsin J, Sotomayor M, Comellas G, Schulten K (2009) Discovery through the computational microscope. Structure 17:1295–1306PubMedPubMedCentralCrossRefGoogle Scholar
  65. 65.
    Trott O, Olson AJ (2010) Autodock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461PubMedPubMedCentralGoogle Scholar
  66. 66.
    De Vries SJ, Zacharias M (2012) ATTRACT-EM: a new method for the computational assembly of large molecular machines using cryo-EM maps. PLoS One 7:e49733PubMedPubMedCentralCrossRefGoogle Scholar
  67. 67.
    Karplus M, Lavery R (2014) Significance of molecular dynamics simulations for life sciences. Isr J Chem 54:1042–1051CrossRefGoogle Scholar
  68. 68.
    Dror RO, Dirks RM, Grossman JP, Xu HF, Shaw DE (2012) Biomolecular simulation: a computational microscope for molecular biology. Annu Rev Biophys 41:429–452PubMedCrossRefGoogle Scholar
  69. 69.
    Ruiz-Carmona S, Alvarez-Garcia D, Foloppe N, Garmendia-Doval AB, Juhos S, Schmidtke P, Barril X, Hubbard RE, Morley SD (2014) rDock: a fast, versatile and open source program for docking ligands to proteins and nucleic acids. PLoS Comput Biol 10:e1003571PubMedPubMedCentralCrossRefGoogle Scholar
  70. 70.
    Gilson MK, Zhou HX (2007) Calculation of protein-ligand binding affinities. Annu Rev Biophys Biomol Struct 36:21–42PubMedCrossRefGoogle Scholar
  71. 71.
    Mortier J, Rakers C, Bermudez M, Murgueitio MS, Riniker S, Wolber G (2015) The impact of molecular dynamics on drug design: applications for the characterization of ligand-macromolecule complexes. Drug Discov Today 20:686–702PubMedCrossRefGoogle Scholar
  72. 72.
    Shaw DE, Deneroff MM, Dror RO, Kuskin JS, Larson RH, Salmon JK, Young C, Batson B, Bowers KJ, Chao JC, Eastwood MP, Gagliardo J, Grossman JP, Ho CR, Ierardi DJ, Kolossvary I, Klepeis JL, Layman T, Mcleavey C, Moraes MA, Mueller R, Priest EC, Shan YB, Spengler J, Theobald M, Towles B, Wang SC (2008) Anton, a special-purpose machine for molecular dynamics simulation. Commun ACM 51:91–97CrossRefGoogle Scholar
  73. 73.
    Anderson JA, Lorenz CD, Travesset A (2008) General purpose molecular dynamics simulations fully implemented on graphics processing units. J Comput Phys 227:5342–5359CrossRefGoogle Scholar
  74. 74.
    Harvey MJ, Giupponi G, Fabritiis GD (2009) ACEMD: accelerating biomolecular dynamics in the microsecond time scale. J Chem Theory Comput 5:1632–1639PubMedCrossRefGoogle Scholar
  75. 75.
    Le Grand S, Gotz AW, Walker RC (2013) SPFP: speed without compromise—a mixed precision model for GPU accelerated molecular dynamics simulations. Comput Phys Commun 184:374–380CrossRefGoogle Scholar
  76. 76.
    Ruggerone P, Vargiu AV, Collu F, Fischer N, Kandt C (2013) Molecular dynamics computer simulations of multidrug RND efflux pumps. Comput Struct Biotechnol J 5:e201302008PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Schulz R, Vargiu AV, Collu F, Kleinekathofer U, Ruggerone P (2010) Functional rotation of the transporter AcrB: insights into drug extrusion from simulations. PLoS Comput Biol 6:e1000806PubMedPubMedCentralCrossRefGoogle Scholar
  78. 78.
    Schulz R, Vargiu AV, Ruggerone P, Kleinekathofer U (2011) Role of water during the extrusion of substrates by the efflux transporter AcrB. J Phys Chem B 115:8278–8287PubMedCrossRefGoogle Scholar
  79. 79.
    Vargiu AV, Collu F, Schulz R, Pos KM, Zacharias M, KleinekathöFer U, Ruggerone P (2011) Effect of the F610A mutation on substrate extrusion in the AcrB transporter: explanation and rationale by molecular dynamics simulations. J Am Chem Soc 133:10704–10707PubMedCrossRefGoogle Scholar
  80. 80.
    Collu F, Vargiu AV, Dreier J, Cascella M, Ruggerone P (2012) Recognition of imipenem and meropenem by the RND-transporter MexB studied by computer simulations. J Am Chem Soc 134:19146–19158PubMedCrossRefGoogle Scholar
  81. 81.
    Vargiu AV, Nikaido H (2012) Multidrug binding properties of the AcrB efflux pump characterized by molecular dynamics simulations. Proc Natl Acad Sci U S A 109:20637–20642PubMedPubMedCentralCrossRefGoogle Scholar
  82. 82.
    Vargiu AV, Ruggerone P, Opperman TJ, Nguyen ST, Nikaido H (2014) Molecular mechanism of MBX2319 inhibition of Escherichia coli AcrB multidrug efflux pump and comparison with other inhibitors. Antimicrob Agents Chemother 58:6224–6234PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Blair JMA, Bavro VN, Ricci V, Modi N, Cacciotto P, Kleinekathoefer U, Ruggerone P, Vargiu AV, Baylay AJ, Smith HE, Brandon Y, Galloway D, Piddock LJV (2015) AcrB drug-binding pocket substitution confers clinically relevant resistance and altered substrate specificity. Proc Natl Acad Sci U S A 112:3511–3516PubMedPubMedCentralCrossRefGoogle Scholar
  84. 84.
    Schulz R, Vargiu AV, Ruggerone P, Kleinekathoefer U (2015) Computational study of correlated domain motions in the AcrB efflux transporter. Biomed Res Int 2015:487298PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Kinana AD, Vargiu AV, May T, Nikaido H (2016) Aminoacyl β-naphthylamides as substrates and modulators of AcrB multidrug efflux pump. Proc Natl Acad Sci U S A 113:1405–1410PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Sjuts H, Vargiu AV, Kwasny SM, Nguyen ST, Kim H-S, Ding X, Ornik AR, Ruggerone P, Bowlin TL, Nikaido H, Pos KM, Opperman TJ (2016) Molecular basis for inhibition of AcrB multidrug efflux pump by novel and powerful pyranopyridine derivatives. Proc Natl Acad Sci U S A 113:3509–3514PubMedPubMedCentralCrossRefGoogle Scholar
  87. 87.
    Fischer N, Kandt C (2011) Three ways in, one way out: water dynamics in the trans-membrane domains of the inner membrane translocase AcrB. Proteins 79:2871–2885PubMedCrossRefGoogle Scholar
  88. 88.
    Fischer N, Kandt C (2013) Porter domain opening and closing motions in the multi-drug efflux transporter AcrB. BBA-Biomembranes 1828:632–641PubMedCrossRefGoogle Scholar
  89. 89.
    Fischer N, Raunest M, Schmidt TH, Koch DC, Kandt C (2014) Efflux pump-mediated antibiotics resistance: insights from computational structural biology. Interdiscip Sci 6:1–12PubMedCrossRefGoogle Scholar
  90. 90.
    Koch DC, Raunest M, Harder T, Kandt C (2013) Unilateral access regulation: ground state dynamics of the Pseudomonas aeruginosa outer membrane efflux duct OprM. Biochemistry 52:178–187PubMedCrossRefGoogle Scholar
  91. 91.
    Raunest M, Kandt C (2012) Locked on one side only: ground state dynamics of the outer membrane efflux duct TolC. Biochemistry 51:1719–1729PubMedCrossRefGoogle Scholar
  92. 92.
    Yamane T, Murakami S, Ikeguchi M (2013) Functional rotation induced by alternating protonation states in the multidrug transporter AcrB: all-atom molecular dynamics simulations. Biochemistry 52:7648–7658PubMedCrossRefGoogle Scholar
  93. 93.
    Wang B, Weng J, Wang W (2015) Substrate binding accelerates the conformational transitions and substrate dissociation in multidrug efflux transporter AcrB. Front Microbiol 6:302PubMedPubMedCentralGoogle Scholar
  94. 94.
    Vaccaro L, Koronakis V, Sansom MSP (2006) Flexibility in a drug transport accessory protein: molecular dynamics simulations of MexA. Biophys J 91:558–564PubMedPubMedCentralCrossRefGoogle Scholar
  95. 95.
    Vaccaro L, Scott KA, Sansom MSP (2008) Gating at both ends and breathing in the middle: conformational dynamics of TolC. Biophys J 95:5681–5691PubMedPubMedCentralCrossRefGoogle Scholar
  96. 96.
    Wang B, Weng J, Fan K, Wang W (2012) Interdomain flexibility and pH-induced conformational changes of AcrA revealed by molecular dynamics simulations. J Phys Chem B 116:3411–3420PubMedCrossRefGoogle Scholar
  97. 97.
    Yamaguchi A, Nakashima R, Sakurai K (2015) Structural basis of RND-type multidrug exporters. Front Microbiol 6:327PubMedPubMedCentralCrossRefGoogle Scholar
  98. 98.
    Sali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234:779–815PubMedCrossRefGoogle Scholar
  99. 99.
    Bower MJ, Cohen FE, Dunbrack RL (1997) Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool. J Mol Biol 267:1268–1282PubMedCrossRefGoogle Scholar
  100. 100.
    Marti-Renom MA, Stuart AC, Fiser A, Sanchez R, Melo F, Sali A (2000) Comparative protein structure modeling of genes and genomes. Annu Rev Biophys Biomol Struct 29:291–325PubMedCrossRefGoogle Scholar
  101. 101.
    Schwede T, Kopp J, Guex N, Peitsch MC (2003) SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res 31:3381–3385PubMedPubMedCentralCrossRefGoogle Scholar
  102. 102.
    Šali A, Potterton L, Yuan F, Van Vlijmen H, Karplus M (1995) Evaluation of comparative protein modeling by MODELLER. Proteins 23:318–326PubMedCrossRefGoogle Scholar
  103. 103.
    Eswar N, Webb B, Marti-Renom MA, Madhusudhan MS, Eramian D, Shen M-Y, Pieper U, Sali A (2006) Comparative protein structure modeling using modeller. Curr Protoc Bioinformatics 15:5.6:5.6.1–5.6.30Google Scholar
  104. 104.
    Sali A, Overington JP (1994) Derivation of rules for comparative protein modeling from a database of protein structure alignments. Protein Sci 3:1582–1596PubMedPubMedCentralCrossRefGoogle Scholar
  105. 105.
    Webb B, Sali A (2014) Comparative protein structure modeling using MODELLER. Curr Protoc Bioinformatics 47:5.6:5.6.1–5.6.32Google Scholar
  106. 106.
    Sousa SF, Fernandes PA, Ramos MJ (2006) Protein-ligand docking: current status and future challenges. Proteins 65:15–26PubMedCrossRefGoogle Scholar
  107. 107.
    Rodrigues JP, Karaca E, Bonvin AM (2015) Information-driven structural modelling of protein-protein interactions. Methods Mol Biol 1215:399–424PubMedCrossRefGoogle Scholar
  108. 108.
    Chen YC (2015) Beware of docking! Trends Pharmacol Sci 36:78–95PubMedCrossRefGoogle Scholar
  109. 109.
    Amaro RE, Baron R, Mccammon JA (2008) An improved relaxed complex scheme for receptor flexibility in computer-aided drug design. J Comput Aided Mol Des 22:693–705PubMedPubMedCentralCrossRefGoogle Scholar
  110. 110.
    Huang S-Y, Zou X (2007) Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking. Proteins 66:399–421PubMedCrossRefGoogle Scholar
  111. 111.
    Takatsuka Y, Chen C, Nikaido H (2010) Mechanism of recognition of compounds of diverse structures by the multidrug efflux pump AcrB of Escherichia coli. Proc Natl Acad Sci U S A 107:6559–6565PubMedPubMedCentralCrossRefGoogle Scholar
  112. 112.
    Karplus M, Mccammon JA (2002) Molecular dynamics simulations of biomolecules. Nat Struct Biol 9:646–652PubMedCrossRefGoogle Scholar
  113. 113.
    Van Gunsteren WF, Billeter SR, Eising AA, Hunenberger PH, Kruger P, Mark AE, Scott WRP, Tironi IG (1996) Biomolecular simulation: the GROMOS96 manual and user guide. Hochschulverlag AG an der ETH, ZurichGoogle Scholar
  114. 114.
    Jorgensen WL, Tirado-Rives J (1988) The OPLS force field for proteins. Energy minimizations for crystals of cyclic peptides and crambin. J Am Chem Soc 110:1657–1666PubMedCrossRefGoogle Scholar
  115. 115.
    Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of a general amber force field. J Comput Chem 25:1157–1174PubMedCrossRefGoogle Scholar
  116. 116.
    Brooks BR, Brooks CL 3rd, Mackerell AD Jr, Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L, Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York DM, Karplus M (2009) CHARMM: the biomolecular simulation program. J Comput Chem 30:1545–1614PubMedPubMedCentralCrossRefGoogle Scholar
  117. 117.
    Ponder JW, Case DA (2003) Force fields for protein simulations. Adv Protein Chem 66:27–85PubMedCrossRefGoogle Scholar
  118. 118.
    Halgren TA, Damm W (2001) Polarizable force fields. Curr Opin Struct Biol 11:236–242PubMedCrossRefGoogle Scholar
  119. 119.
    Graen T, Hoefling M, Grubmuller H (2014) AMBER-DYES: characterization of charge fluctuations and force field parameterization of fluorescent dyes for molecular dynamics simulations. J Chem Theory Comput 10:5505–5512PubMedCrossRefGoogle Scholar
  120. 120.
    Malde AK, Zuo L, Breeze M, Stroet M, Poger D, Nair PC, Oostenbrink C, Mark AE (2011) An automated force field topology builder (ATB) and repository: version 1.0. J Chem Theory Comput 7:4026–4037PubMedCrossRefGoogle Scholar
  121. 121.
    Vanquelef E, Simon S, Marquant G, Garcia E, Klimerak G, Delepine JC, Cieplak P, Dupradeau FY (2011) R.E.D. Server: a web service for deriving RESP and ESP charges and building force field libraries for new molecules and molecular fragments. Nucleic Acids Res 39:W511–W517PubMedPubMedCentralCrossRefGoogle Scholar
  122. 122.
    Mayne CG, Saam J, Schulten K, Tajkhorshid E, Gumbart JC (2013) Rapid parameterization of small molecules using the force field toolkit. J Comput Chem 34:2757–2770PubMedCrossRefGoogle Scholar
  123. 123.
    Marvin, Marvin (2012)
  124. 124.
    Case DA, Berryman JT, Betz RM, Cerutti DS, Cheatham Iii TE, Darden TA, Duke RE, Giese TJ, Gohlke H, Goetz AW, Homeyer N, Izadi S, Janowski P, Kaus J, Kovalenko A, Lee TS, Legrand S, Li P, Luchko T, Luo R, Madej B, Merz KM, Monard G, Needham P, Nguyen H, Nguyen HT, Omelyan I, Onufriev A, Roe DR, Roitberg A, Salomon-Ferrer R, Simmerling CL, Smith W, Swails J, Walker RC, Wang J, Wolf RM, Wu X, York DM, Kollman PA (2015) AMBER 2015. University of California, San FranciscoGoogle Scholar
  125. 125.
    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 Jr, Montgomery JA, 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 (2009) Gaussian 09, Revision A.1. Gaussian, Inc., Wallingford, CTGoogle Scholar
  126. 126.
    Klauda JB, Venable RM, Freites JA, O’connor JW, Tobias DJ, Mondragon-Ramirez C, Vorobyov I, Mackerell AD Jr, Pastor RW (2010) Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. J Phys Chem B 114:7830–7843PubMedPubMedCentralCrossRefGoogle Scholar
  127. 127.
    Dickson CJ, Madej BD, Skjevik AA, Betz RM, Teigen K, Gould IR, Walker RC (2014) Lipid14: the amber lipid force field. J Chem Theory Comput 10:865–879PubMedPubMedCentralCrossRefGoogle Scholar
  128. 128.
    Poger D, Van Gunsteren WF, Mark AE (2010) A new force field for simulating phosphatidylcholine bilayers. J Comput Chem 31:1117–1125PubMedCrossRefGoogle Scholar
  129. 129.
    Hornak V, Abel R, Okur A, Strockbine B, Roitberg A, Simmerling C (2006) Comparison of multiple amber force fields and development of improved protein backbone parameters. Proteins 65:712–725PubMedPubMedCentralCrossRefGoogle Scholar
  130. 130.
    Malloci G, Vargiu A, Serra G, Bosin A, Ruggerone P, Ceccarelli M (2015) A database of force-field parameters, dynamics, and properties of antimicrobial compounds. Molecules 20:13997PubMedCrossRefGoogle Scholar
  131. 131.
    Malloci G, Serra G, Bosin A, Vargiu AV (2016) Extracting conformational ensembles of small molecules from molecular dynamics simulations: ampicillin as a test case. Computation 4:5CrossRefGoogle Scholar
  132. 132.
    Stavenger RA, Winterhalter M (2014) TRANSLOCATION project: how to get good drugs into bad bugs. Sci Transl Med 6:228ed7PubMedCrossRefGoogle Scholar
  133. 133.
    Van Meer G, Voelker DR, Feigenson GW (2008) Membrane lipids: where they are and how they behave. Nat Rev Mol Cell Biol 9:112–124PubMedPubMedCentralCrossRefGoogle Scholar
  134. 134.
    Tieleman DP, Marrink SJ, Berendsen HJ (1997) A computer perspective of membranes: molecular dynamics studies of lipid bilayer systems. Biochim Biophys Acta 1331:235–270PubMedCrossRefGoogle Scholar
  135. 135.
    Berger O, Edholm O, Jahnig F (1997) Molecular dynamics simulations of a fluid bilayer of dipalmitoylphosphatidylcholine at full hydration, constant pressure, and constant temperature. Biophys J 72:2002–2013PubMedPubMedCentralCrossRefGoogle Scholar
  136. 136.
    Marrink SJ, Risselada HJ, Yefimov S, Tieleman DP, De Vries AH (2007) The MARTINI force field: coarse grained model for biomolecular simulations. J Phys Chem B 111:7812–7824PubMedCrossRefGoogle Scholar
  137. 137.
    Orsi M, Essex JW (2011) The ELBA force field for coarse-grain modeling of lipid membranes. PLoS One 6:e28637PubMedPubMedCentralCrossRefGoogle Scholar
  138. 138.
    Marrink SJ, Tieleman DP (2013) Perspective on the Martini model. Chem Soc Rev 42:6801–6822PubMedCrossRefGoogle Scholar
  139. 139.
    Cheatham TE 3rd, Case DA (2013) Twenty-five years of nucleic acid simulations. Biopolymers 99:969–977PubMedGoogle Scholar
  140. 140.
    Vargiu AV, Magistrato A (2014) Atomistic-level portrayal of drug-DNA interplay: a history of courtships and meetings revealed by molecular simulations. ChemMedChem 9:1966–1981PubMedCrossRefGoogle Scholar
  141. 141.
    Perez A, Marchan I, Svozil D, Sponer J, Cheatham TE 3rd, Laughton CA, Orozco M (2007) Refinement of the AMBER force field for nucleic acids: improving the description of {alpha}/{gamma} conformers. Biophys J 92:3817–3829PubMedPubMedCentralCrossRefGoogle Scholar
  142. 142.
    Soares TA, Hünenberger PH, Kastenholz MA, Kräutler V, Lenz T, Lins RD, Oostenbrink C, Van Gunsteren WF (2005) An improved nucleic acid parameter set for the GROMOS force field. J Comput Chem 26:725–737PubMedCrossRefGoogle Scholar
  143. 143.
    Mackerell AD, Bashford D, Bellott M, Dunbrack RL, Evanseck JD, Field MJ, Fischer S, Gao J, Guo H, Ha S, Joseph-Mccarthy D, Kuchnir L, Kuczera K, Lau FT, Mattos C, Michnick S, Ngo T, Nguyen DT, Prodhom B, Reiher WE, Roux B, Schlenkrich M, Smith JC, Stote R, Straub J, Watanabe M, Wiorkiewicz-Kuczera J, Yin D, Karplus M (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 102:3586–3616PubMedCrossRefGoogle Scholar
  144. 144.
    Siu SWI, Vácha R, Jungwirth P, Böckmann RA (2008) Biomolecular simulations of membranes : physical properties from different force fields. J Chem Phys 128:125103PubMedCrossRefGoogle Scholar
  145. 145.
    Marrink SJ, De Vries AH, Tieleman DP (2009) Lipids on the move: simulations of membrane pores, domains, stalks and curves. Biochim Biophys Acta 1788:149–168PubMedCrossRefGoogle Scholar
  146. 146.
    Lyubartsev AP, Rabinovich AL (2011) Recent development in computer simulations of lipid bilayers. Soft Matter 7:25–39CrossRefGoogle Scholar
  147. 147.
    Leftin A, Brown MF (2011) An NMR database for simulations of membrane dynamics. Biochim Biophys Acta 1808:818–839PubMedCrossRefGoogle Scholar
  148. 148.
    Bennett WF, Tieleman DP (2013) Computer simulations of lipid membrane domains. Biochim Biophys Acta 1828:1765–1776PubMedCrossRefGoogle Scholar
  149. 149.
    Chavent M, Reddy T, Goose J, Dahl AC, Stone JE, Jobard B, Sansom MS (2014) Methodologies for the analysis of instantaneous lipid diffusion in MD simulations of large membrane systems. Faraday Discuss 169:455–475PubMedPubMedCentralCrossRefGoogle Scholar
  150. 150.
    Javanainen M (2014) Universal method for embedding proteins into complex lipid bilayers for molecular dynamics simulations. J Chem Theory Comput 10:2577–2582PubMedCrossRefGoogle Scholar
  151. 151.
    Schmidt TH, Kandt C (2012) LAMBADA and InflateGRO2: efficient membrane alignment and insertion of membrane proteins for molecular dynamics simulations. J Chem Inf Model 52:2657–2669PubMedCrossRefGoogle Scholar
  152. 152.
    Balabin IA (2010) Membrane Plug-inGoogle Scholar
  153. 153.
    Guixa-Gonzalez R, Rodriguez-Espigares I, Ramirez-Anguita JM, Carrio-Gaspar P, Martinez-Seara H, Giorgino T, Selent J (2014) MEMBPLUGIN: studying membrane complexity in VMD. Bioinformatics 30:1478–1480PubMedCrossRefGoogle Scholar
  154. 154.
    Nagle JF, Tristram-Nagle S (2000) Lipid bilayer structure. Curr Opin Struct Biol 10:474–480PubMedPubMedCentralCrossRefGoogle Scholar
  155. 155.
    Lis LJ, Mcalister M, Fuller N, Rand RP, Parsegian VA (1982) Interactions between neutral phospholipid bilayer membranes. Biophys J 37:657–665PubMedPubMedCentralGoogle Scholar
  156. 156.
    Rand RP, Parsegian VA (1989) Hydration forces between phospholipid bilayers. Biochem Biophys Acta 988:351–376Google Scholar
  157. 157.
    Zimmerberg J (1987) Molecular mechanisms of membrane fusion: steps during phospholipid and exocytotic membrane fusion. Biosci Rep 7:251–268PubMedCrossRefGoogle Scholar
  158. 158.
    Rand RP. Structural parameters of aqueous phospholipid mixtures. Available from:
  159. 159.
    Kucerka N, Katsaras J, Nagle JF (2010) Comparing membrane simulations to scattering experiments: introducing the SIMtoEXP software. J Membr Biol 235:43–50PubMedPubMedCentralCrossRefGoogle Scholar
  160. 160.
    Skjevik AA, Madej BD, Walker RC, Teigen K (2012) LIPID11: a modular framework for LIPID simulations using amber. J Phys Chem B 116(36):11124PubMedPubMedCentralCrossRefGoogle Scholar
  161. 161.
    Allen WJ, Lemkul JA, Bevan DR (2009) GridMAT-MD: a grid-based membrane analysis tool for use with molecular dynamics. J Comput Chem 30:1952–1958PubMedCrossRefGoogle Scholar
  162. 162.
    Dickson CJ, Rosso L, Betz RM, Walker RC, Gould IR (2012) GAFFlipid: a general amber force field for the accurate molecular dynamics simulation of phospholipid. Soft Matter 8:9617–9627CrossRefGoogle Scholar
  163. 163.
    Shinoda W, Okazaki S (1998) A Voronoi analysis of lipid area fluctuation in a bilayer. J Chem Phys 109:1517–1521CrossRefGoogle Scholar
  164. 164.
    Mori T, Ogushi F, Sugita Y (2012) Analysis of lipid surface area in protein-membrane systems combining Voronoi tessellation and Monte Carlo integration methods. J Comput Chem 33:286–293PubMedCrossRefGoogle Scholar
  165. 165.
    Gapsys V, De Groot BL, Briones R (2013) Computational analysis of local membrane properties. J Comput Aided Mol Des 27:845–858PubMedPubMedCentralCrossRefGoogle Scholar
  166. 166.
    Gilson MK, Given JA, Bush BL, Mccammon JA (1997) The statistical-thermodynamic basis for computation of binding affinities: a critical review. Biophys J 72:1047–1069PubMedPubMedCentralCrossRefGoogle Scholar
  167. 167.
    Woo HJ, Roux B (2005) Calculation of absolute protein-ligand binding free energy from computer simulations. Proc Natl Acad Sci U S A 102:6825–6830PubMedPubMedCentralCrossRefGoogle Scholar
  168. 168.
    Jiao D, Golubkov PA, Darden TA, Ren P (2008) Calculation of protein-ligand binding free energy by using a polarizable potential. Proc Natl Acad Sci U S A 105:6290–6295PubMedPubMedCentralCrossRefGoogle Scholar
  169. 169.
    Mitomo D, Fukunishi Y, Higo J, Nakamura H (2009) Calculation of protein-ligand binding free energy using smooth reaction path generation (SRPG) method: a comparison of the explicit water model, gb/sa model and docking score function. Genome Inform 23:85–97PubMedGoogle Scholar
  170. 170.
    Steinbrecher T, Labahn A (2010) Towards accurate free energy calculations in ligand protein-binding studies. Curr Med Chem 17:767–785PubMedCrossRefGoogle Scholar
  171. 171.
    Rathore RS, Sumakanth M, Reddy MS, Reddanna P, Rao AA, Erion MD, Reddy MR (2013) Advances in binding free energies calculations: QM/MM-based free energy perturbation method for drug design. Curr Pharm Des 19:4674–4686PubMedCrossRefGoogle Scholar
  172. 172.
    Srinivasan J, Cheatham Iii TE, Cieplak P, Kollman PA, Case DA (1998) Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate-DNA helices. J Am Chem Soc 120:9401–9409CrossRefGoogle Scholar
  173. 173.
    Kollman PA, Massova I, Reyes C, Kuhn B, Huo SH, Chong L, Lee M, Lee T, Duan Y, Wang W, Donini O, Cieplak P, Srinivasan J, Case DA, Cheatham TE (2000) Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res 33:889–897PubMedCrossRefGoogle Scholar
  174. 174.
    Fogolari F, Brigo A, Molinari H (2003) Protocol for MM/PBSA molecular dynamics simulations of proteins. Biophys J 85:159–166PubMedPubMedCentralCrossRefGoogle Scholar
  175. 175.
    Hou T, Wang J, Li Y, Wang W (2010) Assessing the performance of the MM/PBSA and MM/GBSA methods. 1. The accuracy of binding free energy calculations based on molecular dynamics simulations. J Chem Inf Model 51:69–82PubMedPubMedCentralCrossRefGoogle Scholar
  176. 176.
    Kongsted J, Ryde U (2009) An improved method to predict the entropy term with the MM/PBSA approach. J Comput Aided Mol Des 23:63–71PubMedCrossRefGoogle Scholar
  177. 177.
    Massova I, Kollman PA (1999) Computational alanine scanning to probe protein-protein interactions: a novel approach to evaluate binding free energies. J Am Chem Soc 121:8133–8143CrossRefGoogle Scholar
  178. 178.
    Fiser A, Do RKG, Sali A (2000) Modeling of loops in protein structures. Protein Sci 9:1753–1773PubMedPubMedCentralCrossRefGoogle Scholar
  179. 179.
    Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph 14:33–38PubMedCrossRefGoogle Scholar
  180. 180.
    Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410PubMedCrossRefGoogle Scholar
  181. 181.
    Gish W, States DJ (1993) Identification of protein coding regions by database similarity search. Nat Genet 3:266–272PubMedCrossRefGoogle Scholar
  182. 182.
    Madden TL, Tatusov RL, Zhang J (1996) Applications of network BLAST server. Methods Enzymol 266:131–141PubMedCrossRefGoogle Scholar
  183. 183.
    Shen MY, Sali A (2006) Statistical potential for assessment and prediction of protein structures. Protein Sci 15:2507–2524PubMedPubMedCentralCrossRefGoogle Scholar
  184. 184.
    Bolton EE, Wang Y, Thiessen PA, Bryant SH (2008) PubChem: integrated platform of small molecules and biological activities. In: Wheeler RA, Spellmeyer DC (eds) Annual reports in computational chemistry. Elsevier, Oxford, pp 217–241Google Scholar
  185. 185.
    O'boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR (2011) Open babel: an open chemical toolbox. J Cheminform 3:33PubMedPubMedCentralCrossRefGoogle Scholar
  186. 186.
    Hohenberg P, Kohn W (1964) Inhomogeneous electron gas. Phys Rev 136:B864–B871CrossRefGoogle Scholar
  187. 187.
    Kohn W, Sham L (1965) Self-consistent equations including exchange and correlation effects. Phys Rev 140:A1133–A1138CrossRefGoogle Scholar
  188. 188.
    Becke AD (1993) Density-functional thermochemistry. 3. The role of exact exchange. J Chem Phys 98:5648–5652CrossRefGoogle Scholar
  189. 189.
    Kim K, Jordan KD (1994) Comparison of density-functional and Mp2 calculations on the water monomer and dimer. J Phys Chem 98:10089–10094CrossRefGoogle Scholar
  190. 190.
    Pople JA (1999) Quantum chemical models (Nobel lecture). Angew Chem Int Ed 38:1894–1902CrossRefGoogle Scholar
  191. 191.
    Tomasi J, Mennucci B, Cammi R (2005) Quantum mechanical continuum solvation models. Chem Rev 105:2999–3093PubMedCrossRefGoogle Scholar
  192. 192.
    Singh UC, Kollman PA (1984) An approach to computing electrostatic charges for molecules. J Comput Chem 5:129–145CrossRefGoogle Scholar
  193. 193.
    Laio A, Vandevondele J, Rothlisberger U (2002) D-RESP : dynamically generated electrostatic potential derived charges from quantum mechanics/molecular mechanics simulations. J Phys Chem B 106:7300–7307CrossRefGoogle Scholar
  194. 194.
    Wang J, Wang W, Kollman PA, Case DA (2006) Automatic atom type and bond type perception in molecular mechanical calculations. J Mol Graph Model 25:247–260PubMedCrossRefGoogle Scholar
  195. 195.
    Dolinsky TJ, Nielsen JE, Mccammon JA, Baker NA (2004) PDB2PQR: an automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Res 32:W665–W667PubMedPubMedCentralCrossRefGoogle Scholar
  196. 196.
    Schuttelkopf AW, Van Aalten DM (2004) PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallogr D Biol Crystallogr 60:1355–1363PubMedCrossRefGoogle Scholar
  197. 197.
    Kandasamy SK, Larson RG (2006) Molecular dynamics simulations of model trans-membrane peptides in lipid bilayers: a systematic investigation of hydrophobic mismatch. Biophys J 90:2326–2343PubMedPubMedCentralCrossRefGoogle Scholar
  198. 198.
    Lindahl E, Sansom MSP (2008) Membrane proteins : molecular dynamics simulations. Curr Opin Struct Biol 18:425–431PubMedCrossRefGoogle Scholar
  199. 199.
    Gurtovenko AA, Vattulainen I (2009) Calculation of the electrostatic potential of lipid bilayers from molecular dynamics simulations: methodological issues. J Chem Phys 130:215107PubMedCrossRefGoogle Scholar
  200. 200.
    Stansfeld PJ, Sansom MS (2011) Molecular simulation approaches to membrane proteins. Structure 19:1562–1572PubMedCrossRefGoogle Scholar
  201. 201.
    Jo S, Kim T, Iyer VG, Im W (2008) CHARMM-GUI: a web-based graphical user interface for CHARMM. J Comput Chem 29:1859–1865PubMedCrossRefGoogle Scholar
  202. 202.
    Wu EL, Cheng X, Jo S, Rui H, Song KC, Davila-Contreras EM, Qi Y, Lee J, Monje-Galvan V, Venable RM, Klauda JB, Im W (2014) CHARMM-GUI membrane builder toward realistic biological membrane simulations. J Comput Chem 35:1997–2004PubMedPubMedCentralCrossRefGoogle Scholar
  203. 203.
    Lomize MA, Pogozheva ID, Joo H, Mosberg HI, Lomize AL (2012) OPM database and PPM web server: resources for positioning of proteins in membranes. Nucleic Acids Res 40:D370–D376PubMedCrossRefGoogle Scholar
  204. 204.
    Kimmett T, Smith N, Witham S, Petukh M, Sarkar S, Alexov E (2014) ProBLM web server: protein and membrane placement and orientation package. Comput Math Methods Med 2014:838259PubMedPubMedCentralCrossRefGoogle Scholar
  205. 205.
    Kufareva I, Lenoir M, Dancea F, Sridhar P, Raush E, Bissig C, Gruenberg J, Abagyan R, Overduin M (2014) Discovery of novel membrane binding structures and functions. Biochem Cell Biol 92:555–563PubMedPubMedCentralCrossRefGoogle Scholar
  206. 206.
    Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79:926–935CrossRefGoogle Scholar
  207. 207.
    Joung IS, Cheatham TE (2008) Determination of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations. J Phys Chem B 112:9020–9041PubMedPubMedCentralCrossRefGoogle Scholar
  208. 208.
    Pearlman DA, Case DA, Caldwell JW, Ross WS, Cheatham Iii TE, Debolt S, Ferguson D, Seibel G, Kollman P (1995) AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput Phys Commun 91:1–41CrossRefGoogle Scholar
  209. 209.
    Wimberly BT, Guymon R, Mccutcheon JP, White SW, Ramakrishnan V (1999) A detailed view of a ribosomal active site: the structure of the L11-RNA complex. Cell 97:491–502PubMedCrossRefGoogle Scholar
  210. 210.
    Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26:1781–1802PubMedPubMedCentralCrossRefGoogle Scholar
  211. 211.
    Pronk S, Pall S, Schulz R, Larsson P, Bjelkmar P, Apostolov R, Shirts MR, Smith JC, Kasson PM, Van Der Spoel D, Hess B, Lindahl E (2013) GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29:845–854PubMedPubMedCentralCrossRefGoogle Scholar
  212. 212.
    Miller BR, Mcgee TD, Swails JM, Homeyer N, Gohlke H, Roitberg AE (2012) an efficient program for end-state free energy calculations. J Chem Theory Comput 8:3314–3321PubMedCrossRefGoogle Scholar
  213. 213.
    Tsui V, Case DA (2000) Molecular dynamics simulations of nucleic acids with a generalized born solvation model. J Am Chem Soc 122:2489–2498CrossRefGoogle Scholar
  214. 214.
    Bondi A (1964) van der Waals Volumes and Radii. J Phys Chem 68:441–451CrossRefGoogle Scholar
  215. 215.
    Onufriev A, Bashford D, Case DA (2004) Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins 55:383–394PubMedCrossRefGoogle Scholar
  216. 216.
    Mongan J, Simmerling C, Mccammon JA, Case DA, Onufriev A (2007) Generalized Born model with a simple, robust molecular volume correction. J Chem Theory Comput 3:156–169PubMedPubMedCentralCrossRefGoogle Scholar
  217. 217.
    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 Comput Chem 30:2785–2791PubMedPubMedCentralCrossRefGoogle Scholar
  218. 218.
    Grossfield A, Zuckerman DM (2009) Quantifying uncertainty and sampling quality in biomolecular simulations. Annu Rep Comput Chem 5:23–48PubMedPubMedCentralCrossRefGoogle Scholar
  219. 219.
    Grossfield A, Feller SE, Pitman MC (2007) Convergence of molecular dynamics simulations of membrane proteins. Proteins 40:31–40CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2018

Authors and Affiliations

  • Pierpaolo Cacciotto
    • 1
  • Venkata K. Ramaswamy
    • 1
  • Giuliano Malloci
    • 1
  • Paolo Ruggerone
    • 1
  • Attilio V. Vargiu
    • 1
    Email author
  1. 1.Department of PhysicsUniversity of CagliariMonserratoItaly

Personalised recommendations