534
S. von Grafenstein et al.
49. Kirchmair J, Spitzer GM, Liedl KR (2011) Consideration of water and solvation effects in
virtual screening. In: Sotriffer C (ed) Virtual screening: principals, challenges, and practical
guidelines, vol 82. Wiley, Weinheim, pp 263–289
50. Cole JC, Korb O, Olsson TSG, Liebeschuetz J (2011) The basis for target-based virtual
screening: protein structures. In: Sotriffer C (ed) Virtual screening: principals, challenges,
and practical guidelines, vol 82. Wiley, Weinheim, pp 87–114
51. Borjesson U, Hunenberger PH (2001) Explicit-solvent molecular dynamics simulation at
constant pH: methodology and application to small amines. J Chem Phys 114(22):9706–9719
52. Merski M, Shoichet BK (2013) The impact of introducing a histidine into an apolar cavity site
on docking and ligand recognition. J Med Chem 56(7):2874–2884. doi:10.1021/jm301823g
53. Kim MO, Nichols SE, Wang Y, McCammon JA (2013) Effects of histidine protonation and
rotameric states on virtual screening of M-tuberculosis RmlC. J Comput-Aided Mol Des
27(3):235–246. doi:10.1007/s10822-013-9643-9
54. Labute P (2009) Protonate3D: assignment of ionization states and hydrogen coordinates to
macromolecular structures. Proteins: Str, Funct, Bioinform 75(1):187–205. doi:10.1002/
prot.22234
55. Halperin I, Ma BY, Wolfson H, Nussinov R (2002) Principles of docking: an overview of
search algorithms and a guide to scoring functions. Proteins: Str, Funct, Genet 47(4):409–
443. doi:10.1002/prot.10115
56. Sinko W, Lindert S, McCammon JA (2013) Accounting for receptor flexibility and enhanced sampling methods in computer-aided drug design. Chem Biol Drug Des 81(1):41–49.
doi:10.1111/cbdd.12051
57. Osguthorpe DJ, Sherman W, Hagler AT (2012) Exploring protein flexibility: incorporating
structural ensembles from crystal structures and simulation into virtual screening protocols. J
Phys Chem B 116(23):6952–6959. doi:10.1021/jp3003992
58. Fulle S, Gohlke H (2010) Molecular recognition of RNA: challenges for modelling interactions and plasticity. J Mol Recognit 23(2):220–231. doi:10.1002/jmr.1000
59. Bruno A, Amori L, Costantino G (2011) Addressing the conformational flexibility of serine
racemase by combining targeted molecular dynamics, conformational sampling and docking
studies. Mol Inform 30(4):317–328. doi:10.1002/minf.201000162
60. Abagyan R, Totrov M, Kuznetsov D (1994) ICM—a new method for protein modeling and
design—applications to docking and structure prediction from the distorted native conformation. J Comput Chem 15(5):488–506. doi:10.1002/jcc.540150503
61. Sugita Y, Okamoto Y (1999) Replica-exchange molecular dynamics method for protein folding. Chem Phys Lett 314(1–2):141–151. doi:10.1016/s0009-2614(99)01123-9
62. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21(6):1087–1092.
doi:10.1063/1.1699114
63. Gervasio FL, Laio A, Parrinello M (2005) Flexible docking in solution using metadynamics.
J Am Chem Soc 127(8):2600–2607. doi:10.1021/ja0445950
64. Zacharias M (2004) Rapid protein-ligand docking using soft modes from molecular dynamics
simulations to account for protein deformability: binding of FK506 to FKBP. Proteins: Str,
Funct, Bioinform 54(4):759–767. doi:10.1002/prot.10637
65. Hinsen K (1998) Analysis of domain motions by approximate normal mode calculations. Proteins: Str, Funct, Genet 33(3):417–429. doi:10.1002/(sici)1097-0134(19981115)33:3<417::aidprot10>3.0.co;2-8
66. May A, Zacharias M (2008) Protein-ligand docking accounting for receptor side chain and
global flexibility in normal modes: evaluation on kinase inhibitor cross docking. J Med Chem
51(12):3499–3506. doi:10.1021/jm800071v
67. Leis S, Zacharias M (2011) Efficient inclusion of receptor flexibility in grid-based proteinligand docking. J Comput Chem 32(16):3433–3439. doi:10.1002/jcc.21923
68. Cavasotto CN, Kovacs JA, Abagyan RA (2005) Representing receptor flexibility in ligand
docking through relevant normal modes. J Am Chem Soc 127(26):9632–9640. doi:10.1021/
ja042260c
S. von Grafenstein et al.
49. Kirchmair J, Spitzer GM, Liedl KR (2011) Consideration of water and solvation effects in
virtual screening. In: Sotriffer C (ed) Virtual screening: principals, challenges, and practical
guidelines, vol 82. Wiley, Weinheim, pp 263–289
50. Cole JC, Korb O, Olsson TSG, Liebeschuetz J (2011) The basis for target-based virtual
screening: protein structures. In: Sotriffer C (ed) Virtual screening: principals, challenges,
and practical guidelines, vol 82. Wiley, Weinheim, pp 87–114
51. Borjesson U, Hunenberger PH (2001) Explicit-solvent molecular dynamics simulation at
constant pH: methodology and application to small amines. J Chem Phys 114(22):9706–9719
52. Merski M, Shoichet BK (2013) The impact of introducing a histidine into an apolar cavity site
on docking and ligand recognition. J Med Chem 56(7):2874–2884. doi:10.1021/jm301823g
53. Kim MO, Nichols SE, Wang Y, McCammon JA (2013) Effects of histidine protonation and
rotameric states on virtual screening of M-tuberculosis RmlC. J Comput-Aided Mol Des
27(3):235–246. doi:10.1007/s10822-013-9643-9
54. Labute P (2009) Protonate3D: assignment of ionization states and hydrogen coordinates to
macromolecular structures. Proteins: Str, Funct, Bioinform 75(1):187–205. doi:10.1002/
prot.22234
55. Halperin I, Ma BY, Wolfson H, Nussinov R (2002) Principles of docking: an overview of
search algorithms and a guide to scoring functions. Proteins: Str, Funct, Genet 47(4):409–
443. doi:10.1002/prot.10115
56. Sinko W, Lindert S, McCammon JA (2013) Accounting for receptor flexibility and enhanced sampling methods in computer-aided drug design. Chem Biol Drug Des 81(1):41–49.
doi:10.1111/cbdd.12051
57. Osguthorpe DJ, Sherman W, Hagler AT (2012) Exploring protein flexibility: incorporating
structural ensembles from crystal structures and simulation into virtual screening protocols. J
Phys Chem B 116(23):6952–6959. doi:10.1021/jp3003992
58. Fulle S, Gohlke H (2010) Molecular recognition of RNA: challenges for modelling interactions and plasticity. J Mol Recognit 23(2):220–231. doi:10.1002/jmr.1000
59. Bruno A, Amori L, Costantino G (2011) Addressing the conformational flexibility of serine
racemase by combining targeted molecular dynamics, conformational sampling and docking
studies. Mol Inform 30(4):317–328. doi:10.1002/minf.201000162
60. Abagyan R, Totrov M, Kuznetsov D (1994) ICM—a new method for protein modeling and
design—applications to docking and structure prediction from the distorted native conformation. J Comput Chem 15(5):488–506. doi:10.1002/jcc.540150503
61. Sugita Y, Okamoto Y (1999) Replica-exchange molecular dynamics method for protein folding. Chem Phys Lett 314(1–2):141–151. doi:10.1016/s0009-2614(99)01123-9
62. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21(6):1087–1092.
doi:10.1063/1.1699114
63. Gervasio FL, Laio A, Parrinello M (2005) Flexible docking in solution using metadynamics.
J Am Chem Soc 127(8):2600–2607. doi:10.1021/ja0445950
64. Zacharias M (2004) Rapid protein-ligand docking using soft modes from molecular dynamics
simulations to account for protein deformability: binding of FK506 to FKBP. Proteins: Str,
Funct, Bioinform 54(4):759–767. doi:10.1002/prot.10637
65. Hinsen K (1998) Analysis of domain motions by approximate normal mode calculations. Proteins: Str, Funct, Genet 33(3):417–429. doi:10.1002/(sici)1097-0134(19981115)33:3<417::aidprot10>3.0.co;2-8
66. May A, Zacharias M (2008) Protein-ligand docking accounting for receptor side chain and
global flexibility in normal modes: evaluation on kinase inhibitor cross docking. J Med Chem
51(12):3499–3506. doi:10.1021/jm800071v
67. Leis S, Zacharias M (2011) Efficient inclusion of receptor flexibility in grid-based proteinligand docking. J Comput Chem 32(16):3433–3439. doi:10.1002/jcc.21923
68. Cavasotto CN, Kovacs JA, Abagyan RA (2005) Representing receptor flexibility in ligand
docking through relevant normal modes. J Am Chem Soc 127(26):9632–9640. doi:10.1021/
ja042260c