The multiscale coarse-graining (MS-CG) method is a method for constructing a coarse-grained (CG) model of a system using data obtained from molecular dynamics simulations of the corresponding atomically detailed model. The formal statistical mechanical derivation of the method shows that the potential energy function extracted from an MS-CG calculation is a variational approximation for the true potential of mean force of the CG sites, one that becomes exact in the limit that a complete basis set is used in the variational calculation if enough data are obtained from the atomistic simulations. Most applications of the MS-CG method have employed a representation for the nonbonded part of the CG potential that is a sum of all possible pair interactions. This approach, despite being quite successful for some CG models, is inadequate for some others. Here we propose a systematic method for including three body terms as well as two body terms in the nonbonded part of the CG potential energy. The current method is more general than a previous version presented in a recent paper of this series [L. Larini, L. Lu, and G. A. Voth, J. Chem. Phys.132, 164107 (2010)] https://doi.org/10.1063/1.3394863, in the sense that it does not make any restrictive choices for the functional form of the three body potential. We use hierarchical multiresolution functions that are similar to wavelets to develop very flexible basis function expansions with both two and three body basis functions. The variational problem is solved by a numerical technique that is capable of automatically selecting an appropriate subset of basis functions from a large initial set. We apply the method to two very different coarse-grained models: a solvent free model of a two component solution made of identical Lennard-Jones particles and a one site model of SPC/E water where a site is placed at the center of mass of each water molecule. These calculations show that the inclusion of three body terms in the nonbonded CG potential can lead to significant improvement in the accuracy of CG potentials and hence of CG simulations.

1.
M. P.
Allen
and
D. P.
Tildesley
,
Computer Simulation of Liquids
(
Oxford University Press
,
Oxford
,
1987
).
2.
D.
Frenkel
and
B.
Smit
,
Understanding Molecular Simulation: From Algorithms to Applications
(
Academic
,
2002
).
3.
S. O.
Nielsen
,
C. F.
Lopez
,
G.
Srinivas
, and
M. L.
Klein
,
J. Phys.: Condens. Matter
16
,
R481
(
2004
), and references therein.
4.
T.
Head-Gordon
and
S.
Brown
,
Curr. Opin. Struct. Biol.
13
,
160
(
2003
), and references therein.
5.
V.
Tozzini
,
Curr. Opin. Struct. Biol.
15
,
144
(
2005
), and references therein.
6.
I.
Bahar
and
A.
Rader
,
Curr. Opin. Struct. Biol.
15
,
586
(
2005
), and references therein.
7.
G. S.
Ayton
,
W. G.
Noid
, and
G. A.
Voth
,
Curr. Opin. Struct. Biol.
17
,
192
(
2007
).
8.
M.
Müller
,
K.
Katsov
, and
M.
Schick
,
Phys. Rep.
434
,
113
(
2006
), and references therein.
9.
J.
Baschnagel
,
K.
Binder
,
P.
Doruker
,
A. A.
Gusev
,
O.
Hahn
,
K.
Kremer
,
W. L.
Mattice
,
F.
Müller-Plathe
,
M.
Murat
,
W.
Paul
, et al.,
Advances in Polymer Science
(
Springer-Verlag
,
Berlin
,
2000
), Vol.
152
, p.
41
, and references therein.
10.
Coarse-Graining of Condensed Phase and Biomolecular Systems
, edited by
G. A.
Voth
(
CRC
,
2009
).
12.
N.
and
H.
Abe
,
Biopolymers
20
,
991
(
1981
).
13.
H.
Abe
and
N.
,
Biopolymers
20
,
1013
(
1981
).
14.
S.
Miyazawa
and
R. L.
Jernigan
,
Macromolecules
18
,
534
(
1985
).
15.
A. P.
Lyubartsev
and
A.
Laaksonen
,
Phys. Rev. E
52
,
3730
(
1995
).
16.
J. C.
Shelley
,
M. Y.
Shelley
,
R. C.
Reeder
,
S.
Bandyopadhyay
, and
M. L.
Klein
,
J. Phys. Chem. B
105
,
4464
(
2001
).
17.
S. J.
Marrink
,
A. H.
de Vries
, and
A. E.
Mark
,
J. Phys. Chem. B
108
,
750
(
2004
).
18.
A.
Liwo
,
S.
Oldziej
,
C.
Czaplewski
,
U.
Kozlowska
, and
H. A.
Scheraga
,
J. Phys. Chem. B
108
,
9421
(
2004
).
19.
A.
Liwo
,
C.
Czaplewski
,
J.
Pillardy
, and
H. A.
Scheraga
,
J. Chem. Phys.
115
,
2323
(
2001
).
20.
I. G.
Kevrekidis
,
C. W.
Gear
, and
G.
Hummer
,
AIChE J.
50
,
1346
(
2004
).
21.
N.-V.
Buchete
,
J. E.
Straub
, and
D.
Thirumalai
,
Protein Sci.
13
,
862
(
2004
).
22.
D.
Curco
,
R.
Nussinov
, and
C.
Aleman
,
J. Phys. Chem. B
111
,
14006
(
2007
).
23.
M.
Lu
and
J.
Ma
,
Proc. Natl. Acad. Sci. U.S.A.
105
,
15358
(
2008
).
24.
M. A.
Jonikas
,
R. J.
Radmer
,
A.
Laederach
,
R.
Das
,
S.
Pearlman
,
D.
Herschlag
, and
R. B.
Altman
,
RNA
15
,
189
(
2009
).
25.
R. B.
Pandey
and
B. L.
Farmer
,
J. Chem. Phys.
130
,
044906
(
2009
).
26.
T.
Ha-Duong
,
N.
Basdevant
, and
D.
Borgis
,
Chem. Phys. Lett.
468
,
79
(
2009
).
27.
Z.
Zhang
and
W.
Wriggers
,
J. Phys. Chem. B
112
,
14026
(
2008
).
28.
A. Y.
Shih
,
A.
Arkhipov
,
P. L.
Freddolino
, and
K.
Schulten
,
J. Phys. Chem. B
110
,
3674
(
2006
).
29.
P. J.
Bond
,
J.
Holyoake
,
A.
Ivetac
,
S.
Khalid
, and
M. S.
Sansom
,
J. Struct. Biol.
157
,
593
(
2007
).
30.
D.
Reith
,
M.
Pütz
, and
F.
Müller-Plathe
,
J. Comput. Chem.
24
,
1624
(
2003
).
31.
L.
Monticelli
,
S. K.
Kandasamy
,
X.
Periole
,
R. G.
Larson
,
D. P.
Tieleman
, and
S.-J.
Marrink
,
J. Chem. Theory Comput.
4
,
819
(
2008
).
32.
K.
Moritsugu
and
J. C.
Smith
,
Biophys. J.
95
,
1639
(
2008
).
33.
C. F.
Abrams
,
L.
Delle Site
, and
K.
Kremer
,
Phys. Rev. E
67
,
021807
(
2003
).
34.
R. E.
Rudd
and
J. Q.
Broughton
,
Phys. Rev. B
58
,
R5893
(
1998
).
35.
R. L. C.
Akkermans
and
W. J.
Briels
,
J. Chem. Phys.
114
,
1020
(
2001
).
36.
H.
Fukunaga
,
J.
Takimoto
, and
M.
Doi
,
J. Chem. Phys.
116
,
8183
(
2002
).
37.
S. O.
Nielsen
,
C. F.
Lopez
,
G.
Srinivas
, and
M. L.
Klein
,
J. Chem. Phys.
119
,
7043
(
2003
).
38.
V.
Molinero
and
W. A.
Goddard
,
J. Phys. Chem. B
108
,
1414
(
2004
).
39.
G. S.
Ayton
,
H. L.
Tepper
,
D. T.
Mirijanian
, and
G. A.
Voth
,
J. Chem. Phys.
120
,
4074
(
2004
).
40.
S. D.
Chao
,
J. D.
Kress
, and
A.
Redondo
,
J. Chem. Phys.
122
,
234912
(
2005
).
41.
V.
Tozzini
and
J. A.
McCammon
,
Chem. Phys. Lett.
413
,
123
(
2005
).
42.
J.-W.
Chu
and
G. A.
Voth
,
Proc. Natl. Acad. Sci. U.S.A.
102
,
13111
(
2005
).
43.
P. A.
Golubkov
and
P.
Ren
,
J. Chem. Phys.
125
,
064103
(
2006
).
44.
H.
Gohlke
and
M.
Thorpe
,
Biophys. J.
91
,
2115
(
2006
).
45.
D. A.
Kondrashov
,
Q.
Cui
, and
G. N.
Phillips
,
Biophys. J.
91
,
2760
(
2006
).
46.
L.-J.
Chen
,
H.-J.
Qian
,
Z.-Y.
Lu
,
Z.-S.
Li
, and
C.-C.
Sun
,
J. Phys. Chem. B
110
,
24093
(
2006
).
47.
S.
Izvekov
and
G. A.
Voth
,
J. Phys. Chem. B
109
,
2469
(
2005
).
48.
S.
Izvekov
and
G. A.
Voth
,
J. Chem. Phys.
123
,
134105
(
2005
).
49.
W. G.
Noid
,
J.-W.
Chu
,
G. S.
Ayton
,
V.
Krishna
,
S.
Izvekov
,
G. A.
Voth
,
A.
Das
, and
H. C.
Andersen
,
J. Chem. Phys.
128
,
244114
(
2008
).
50.
A.
Das
and
H. C.
Andersen
,
J. Chem. Phys.
132
,
164106
(
2010
).
51.
W. G.
Noid
,
P.
Liu
,
Y.
Wang
,
J.-W.
Chu
,
G. S.
Ayton
,
S.
Izvekov
,
H. C.
Andersen
, and
G. A.
Voth
,
J. Chem. Phys.
128
,
244115
(
2008
).
52.
A.
Das
and
H. C.
Andersen
,
J. Chem. Phys.
131
,
034102
(
2009
).
53.
L.
Lu
and
G. A.
Voth
,
J. Phys. Chem. B
113
,
1501
(
2009
).
54.
L.
Lu
,
S.
Izvekov
,
A.
Das
,
H. C.
Andersen
, and
G. A.
Voth
,
J. Chem. Theory Comput.
6
,
954
(
2010
).
55.
Y.
Wang
,
S.
Izvekov
,
T.
Yan
, and
G. A.
Voth
,
J. Phys. Chem. B
110
,
3564
(
2006
).
56.
S.
Izvekov
and
G. A.
Voth
,
J. Chem. Theory Comput.
2
,
637
(
2006
).
57.
J.
Zhou
,
I. F.
Thorpe
,
S.
Izvekov
, and
G. A.
Voth
,
Biophys. J.
92
,
4289
(
2007
).
58.
I. F.
Thorpe
,
J.
Zhou
, and
G. A.
Voth
,
J. Phys. Chem. B
112
,
13079
(
2008
).
59.
S.
Izvekov
,
A.
Violi
, and
G. A.
Voth
,
J. Phys. Chem. B
109
,
17019
(
2005
).
60.
Q.
Shi
,
S.
Izvekov
, and
G. A.
Voth
,
J. Phys. Chem. B
110
,
15045
(
2006
).
61.
L.
Larini
,
L.
Lu
, and
G. A.
Voth
,
J. Chem. Phys.
132
,
164107
(
2010
).
62.
F. H.
Stillinger
and
T. A.
Weber
,
Phys. Rev. B
31
,
5262
(
1985
).
63.
A.
Das
and
H. C.
Andersen
,
J. Chem. Phys.
136
,
194113
(
2012
).
64.
See supplementary material at http://dx.doi.org/10.1063/1.4705417 for a description of the construction of three body basis functions for multicomponent systems.
65.
W. C.
Swope
,
H. C.
Andersen
,
P. H.
Berens
, and
K. R.
Wilson
,
J. Chem. Phys.
76
,
637
(
1982
).
66.
H. C.
Andersen
,
J. Chem. Phys.
72
,
2384
(
1980
).
67.
H. J.C.
Berendsen
,
J. R.
Grigera
, and
T. P.
Straatsma
,
J. Phys. Chem.
91
,
6269
(
1987
).
68.
B.
Hess
,
C.
Kutzner
,
D.
van der Spoel
, and
E.
Lindahl
,
J. Chem. Theory Comput.
4
,
435
(
2008
).
70.
W. G.
Hoover
,
Phys. Rev. A
31
,
1695
(
1985
).
71.
T.
Darden
,
D.
York
, and
L.
Pedersen
,
J. Chem. Phys.
98
,
10089
(
1993
).
72.
S.
Miyamoto
and
P. A.
Kollman
,
J. Comput. Chem.
13
,
952
(
1992
).
73.
We use the word “atomistic” to describe a simulation or a model in which all atoms are represented explicitly or in which H atoms have been incorporated into united atoms. Thus the “particles” or “atoms” in this context are actually atoms or combined atoms.

Supplementary Material

You do not currently have access to this content.