533
15 (How to) Profit from Molecular Dynamics-based Ensemble Docking
31. Rudrawar S, Dyason JC, Rameix-Welti MA, Rose FJ, Kerry PS, Russell RJ, van der Werf
S, Thomson RJ, Naffakh N, von Itzstein M (2010) Novel sialic acid derivatives lock open
the 150-loop of an influenza A virus group-1 sialidase. Nat Comm 1 113. doi:10.1038/
ncomms1114
32. Amaro RE, Swift RV, Votapka L, Li WW, Walker RC, Bush RM (2011) Mechanism of
150-cavity formation in influenza neuraminidase. Nat Comm 2388. doi:10.1038/ncomms1390
33. Wallnoefer HG, Lingott T, Gutierrez JM, Merfort I, Liedl KR (2010) Backbone flexibility
controls the activity and specificity of a protein-protein interface: specificity in snake venom
metalloproteases. J Am Chem Soc 132(30):10330–10337. doi:10.1021/ja909908y
34. Case DA, Darden TA, Cheatham III TE, Simmerling CL, Wang J, Duke RE, Luo R, Walker
RC, 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, Wu X, Brozell SR, Steinbrecher T,
Gohlke H, Cai Q, Ye X, Wang J, Hsieh M-J, Cui G, Roe DR, Mathews DH, Seetin MG, Salomon-Ferrer R, Sagui C, Babin V, Luchko T, Gusarov S, Kovalenko A, Kollman PA (2012)
AMBER12. University of California, San Francisco
35. Roe DR, Cheatham TE (2013) PTRAJ and CPPTRAJ: software for processing and analysis of
molecular dynamics trajectory data. J Chem Theory Comput 9(7):3084–3095. doi:10.1021/
ct400341p
36. von Grafenstein S, Wallnoefer HG, Kirchmair J, Fuchs JE, Huber RG, Spitzer GM, Schmidtke
M, Sauerbrei A, Rollinger JM, Liedl KR (2013) Interface dynamics explain assembly dependency of influenza neuraminidase catalytic activity. J Biomol Struct Dyn. Published online
doi:10.1080/07391102.2013.855142
37. McCammon JA, Gelin BR, Karplus M (1977) Dynamics of folded proteins. Nature
267(5612):585–590. doi:10.1038/267585a0
38. Xu M, Lill MA (2011) Significant enhancement of docking sensitivity using implicit ligand
sampling. J Chem Inf Model 51(3):693–706. doi:10.1021/ci100457t
39. Wang JM, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of
a general amber force field. J Comput Chem 25(9):1157–1174
40. Fuchs JE, Huber RG, Von Grafenstein S, Wallnoefer HG, Spitzer GM, Fuchs D, Liedl KR
(2012) Dynamic regulation of phenylalanine hydroxylase by simulated redox manipulation.
PloS One 7(12):e53005. doi:10.1371/journal.pone.0053005
41. Lin J-H, Perryman AL, Schames JR, McCammon JA (2002) Computational drug design accommodating receptor flexibility: the relaxed complex scheme. J Am Chem Soc
124(20):5632–5633. doi:10.1021/ja0260162
42. Seeliger D, de Groot BL (2010) Conformational transitions upon ligand binding: holo-structure prediction from apo conformations. PloS Comp Biol 6(1):e1000634. doi:10.1371/journal.pcbi.1000634
43. Nichols SE, Baron R, Ivetac A, McCammon JA (2011) Predictive power of molecular dynamics receptor structures in virtual screening. J Chem Inf Model 51(6):1439–1446. doi:10.1021/
ci200117n
44. McGovern SL, Shoichet BK (2003) Information decay in molecular docking screens
against holo, apo, and modeled conformations of enzymes. J Med Chem 46(14):2895–2907.
doi:10.1021/jm0300330
45. Mackey MD, Melville JL (2009) Better than random? The chemotype enrichment problem. J
Chem Inf Model 49(5):1154–1162. doi:10.1021/ci8003978
46. Bolstad ESD, Anderson AC (2009) In pursuit of virtual lead optimization: pruning ensembles
of receptor structures for increased efficiency and accuracy during docking. Proteins: Str,
Funct, Bioinform 75(1):62–74. doi:10.1002/prot.22214
47. Armen RS, Chen J, Brooks CL III (2009) An evaluation of explicit receptor flexibility in
molecular docking using molecular dynamics and torsion angle molecular dynamics. J Chem
Theory Comput 5(10):2909–2923. doi:10.1021/ct900262t
48. Marelius J, Ljungberg KB, Aqvist J (2001) Sensitivity of an empirical affinity scoring function to changes in receptor-ligand complex conformations. Eur J Pharm Sci 14(1):87–95.
doi:10.1016/s0928-0987(01)00162-2
15 (How to) Profit from Molecular Dynamics-based Ensemble Docking
31. Rudrawar S, Dyason JC, Rameix-Welti MA, Rose FJ, Kerry PS, Russell RJ, van der Werf
S, Thomson RJ, Naffakh N, von Itzstein M (2010) Novel sialic acid derivatives lock open
the 150-loop of an influenza A virus group-1 sialidase. Nat Comm 1 113. doi:10.1038/
ncomms1114
32. Amaro RE, Swift RV, Votapka L, Li WW, Walker RC, Bush RM (2011) Mechanism of
150-cavity formation in influenza neuraminidase. Nat Comm 2388. doi:10.1038/ncomms1390
33. Wallnoefer HG, Lingott T, Gutierrez JM, Merfort I, Liedl KR (2010) Backbone flexibility
controls the activity and specificity of a protein-protein interface: specificity in snake venom
metalloproteases. J Am Chem Soc 132(30):10330–10337. doi:10.1021/ja909908y
34. Case DA, Darden TA, Cheatham III TE, Simmerling CL, Wang J, Duke RE, Luo R, Walker
RC, 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, Wu X, Brozell SR, Steinbrecher T,
Gohlke H, Cai Q, Ye X, Wang J, Hsieh M-J, Cui G, Roe DR, Mathews DH, Seetin MG, Salomon-Ferrer R, Sagui C, Babin V, Luchko T, Gusarov S, Kovalenko A, Kollman PA (2012)
AMBER12. University of California, San Francisco
35. Roe DR, Cheatham TE (2013) PTRAJ and CPPTRAJ: software for processing and analysis of
molecular dynamics trajectory data. J Chem Theory Comput 9(7):3084–3095. doi:10.1021/
ct400341p
36. von Grafenstein S, Wallnoefer HG, Kirchmair J, Fuchs JE, Huber RG, Spitzer GM, Schmidtke
M, Sauerbrei A, Rollinger JM, Liedl KR (2013) Interface dynamics explain assembly dependency of influenza neuraminidase catalytic activity. J Biomol Struct Dyn. Published online
doi:10.1080/07391102.2013.855142
37. McCammon JA, Gelin BR, Karplus M (1977) Dynamics of folded proteins. Nature
267(5612):585–590. doi:10.1038/267585a0
38. Xu M, Lill MA (2011) Significant enhancement of docking sensitivity using implicit ligand
sampling. J Chem Inf Model 51(3):693–706. doi:10.1021/ci100457t
39. Wang JM, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of
a general amber force field. J Comput Chem 25(9):1157–1174
40. Fuchs JE, Huber RG, Von Grafenstein S, Wallnoefer HG, Spitzer GM, Fuchs D, Liedl KR
(2012) Dynamic regulation of phenylalanine hydroxylase by simulated redox manipulation.
PloS One 7(12):e53005. doi:10.1371/journal.pone.0053005
41. Lin J-H, Perryman AL, Schames JR, McCammon JA (2002) Computational drug design accommodating receptor flexibility: the relaxed complex scheme. J Am Chem Soc
124(20):5632–5633. doi:10.1021/ja0260162
42. Seeliger D, de Groot BL (2010) Conformational transitions upon ligand binding: holo-structure prediction from apo conformations. PloS Comp Biol 6(1):e1000634. doi:10.1371/journal.pcbi.1000634
43. Nichols SE, Baron R, Ivetac A, McCammon JA (2011) Predictive power of molecular dynamics receptor structures in virtual screening. J Chem Inf Model 51(6):1439–1446. doi:10.1021/
ci200117n
44. McGovern SL, Shoichet BK (2003) Information decay in molecular docking screens
against holo, apo, and modeled conformations of enzymes. J Med Chem 46(14):2895–2907.
doi:10.1021/jm0300330
45. Mackey MD, Melville JL (2009) Better than random? The chemotype enrichment problem. J
Chem Inf Model 49(5):1154–1162. doi:10.1021/ci8003978
46. Bolstad ESD, Anderson AC (2009) In pursuit of virtual lead optimization: pruning ensembles
of receptor structures for increased efficiency and accuracy during docking. Proteins: Str,
Funct, Bioinform 75(1):62–74. doi:10.1002/prot.22214
47. Armen RS, Chen J, Brooks CL III (2009) An evaluation of explicit receptor flexibility in
molecular docking using molecular dynamics and torsion angle molecular dynamics. J Chem
Theory Comput 5(10):2909–2923. doi:10.1021/ct900262t
48. Marelius J, Ljungberg KB, Aqvist J (2001) Sensitivity of an empirical affinity scoring function to changes in receptor-ligand complex conformations. Eur J Pharm Sci 14(1):87–95.
doi:10.1016/s0928-0987(01)00162-2