Using atomistic molecular dynamics simulations, we study the temperature dependence of the mechanical unfolding of a model supramolecular complex, a dimer of interlocked calixarene capsules. This system shows reversible transitions between two conformations that are stabilized by different networks of hydrogen bonds. We study the forced dissociation and formation of these networks as a function of temperature and find a strong impact of the nonequilibrium conditions imposed by pulling the system mechanically. The kinetics of the transition between the two conformations is ideally suited to investigate the range of validity of the stochastic models employed in the analysis of force dependent kinetic rates obtained from experimental or simulation data. These models usually assume activated dynamics for the relevant transitions, and therefore, the analytical expressions for the kinetic rates are of an Arrhenius form. A study of the temperature- and force-dependent kinetics by simulation allows an analysis of the transition rates without any model assumption. We find that the temperature dependence of the rates is well described by an Arrhenius law for each value of the force. This enables us to determine the activation free energy and the bare kinetic rate as a function of force independent of each other. In accord with the common model assumptions, we find that the activation free energy decreases with increasing force. The force dependence of the bare rates is compatible with the results of model calculations in the low force regime, and deviations are observed at high forces.

1.
E.
Evans
and
K.
Ritchie
,
Biophys. J.
72
,
1541
(
1997
).
2.
E.
Evans
,
Annu. Rev. Biophys. Biomol. Struct.
30
,
105
(
2001
).
3.
A.
Noy
and
R. W.
Friddle
,
Methods
60
,
142
(
2013
).
4.
O. K.
Dudko
,
Q. Rev. Biophys.
49
,
e3
(
2016
).
5.
F.
Rico
,
A.
Russek
,
L.
Gonzalez
,
H.
Grubmüller
, and
S.
Scheuring
,
Proc. Natl. Acad. Sci. U. S. A.
116
,
6594
(
2019
).
6.
Y.
Zhang
and
O. K.
Dudko
,
Proc. Natl. Acad. Sci. U. S. A.
110
,
16432
(
2013
).
7.
G. I.
Bell
,
Science
200
,
618
(
1978
).
8.
O. K.
Dudko
,
G.
Hummer
, and
A.
Szabo
,
Phys. Rev. Lett.
96
,
108101
(
2006
).
9.
G.
Arya
,
Mol. Simul.
42
,
1542
(
2016
).
10.
U.
Seifert
,
Europhys. Lett.
58
,
792
(
2002
).
11.
G.
Diezemann
,
T.
Schlesier
,
B.
Geil
, and
A.
Janshoff
,
Phys. Rev. E
82
,
051132
(
2010
).
12.
G.
Diezemann
,
J. Chem. Phys.
140
,
184905
(
2014
).
13.
N. G. V.
Kampen
,
Stochastic Processes in Physics and Chemistry
, 3rd ed (
North Holland
,
Amsterdamm, Boston
,
2007
).
14.
G.
Stirnemann
,
S.-g.
Kang
,
R.
Zhou
, and
B. J.
Berne
,
Proc. Natl. Acad. Sci. U. S. A.
111
,
3413
(
2014
).
15.
M.
Kouza
,
P. D.
Lan
,
A. M.
Gabovich
,
A.
Kolinski
, and
M. S.
Li
,
J. Chem. Phys.
146
,
135101
(
2017
).
16.
M.
Schlierf
and
M.
Rief
,
J. Mol. Biol.
354
,
497
(
2005
).
17.
M.
Cieplak
,
T.
Hoang
, and
M.
Robbins
,
Proteins: Struct., Funct., Bioinf.
56
,
285
(
2004
).
18.
C.
Hyeon
and
D.
Thirumalai
,
Proc. Natl. Acad. Sci. U. S. A.
102
,
6789
(
2005
).
19.
M.
Janke
,
Y.
Rudzevich
,
O.
Molokanova
,
T.
Metzroth
,
I.
Mey
,
G.
Diezemann
,
P. E.
Marszalek
,
J.
Gauss
,
V.
Böhmer
, and
A.
Janshoff
,
Nat. Nanotechnol.
4
,
225
(
2009
).
20.
T.
Schlesier
,
T.
Metzroth
,
A.
Janshoff
,
J.
Gauss
, and
G.
Diezemann
,
J. Phys. Chem. B
115
,
6445
(
2011
).
21.
T.
Schlesier
and
G.
Diezemann
,
J. Phys. Chem. B
117
,
1862
(
2013
).
22.
S.
Jaschonek
and
G.
Diezemann
,
J. Chem. Phys.
146
,
124901
(
2017
).
23.
H.
Berendsen
,
D.
van der Spoel
, and
R.
van Drunen
,
Comput. Phys. Commun.
91
,
43
(
1995
).
24.
E.
Lindahl
,
B.
Hess
, and
D.
van der Spoel
,
J. Mol. Model.
7
,
306
(
2001
).
25.
W. L.
Jorgensen
and
J.
Tirado-Rives
,
J. Am. Chem. Soc.
110
,
1657
(
1988
).
26.
W. L.
Jorgensen
,
D. S.
Maxwell
, and
J.
Tirado-Rives
,
J. Am. Chem. Soc.
118
,
11225
(
1996
).
27.
T.
Darden
,
D.
York
, and
L.
Pedersen
,
J. Chem. Phys.
98
,
10089
(
1993
).
28.
M.
Allen
and
D.
Tildesley
,
Computer Simulation of Liquids
(
Oxford Science Publications, Clarendon Press
,
1987
).
29.
B.
Hess
,
H.
Bekker
,
H. J. C.
Berendsen
, and
J. G. E. M.
Fraaije
,
J. Comput. Chem.
18
,
1463
(
1997
).
30.
S.
Jaschonek
,
K.
Schäfer
, and
G.
Diezemann
,
J. Phys. Chem. B
123
,
4688
(
2019
).
31.
G.
Bussi
,
D.
Donadio
, and
M.
Parrinello
,
J. Chem. Phys.
126
,
014101
(
2007
).
32.
M.
Parrinello
and
A.
Rahman
,
J. Appl. Phys.
52
,
7182
(
1981
).
33.
E.
Paci
,
G.
Ciccotti
,
M.
Ferrario
, and
R.
Kapral
,
Chem. Phys. Lett.
176
,
581
(
1991
).
34.
M.
Souaille
and
B.
Roux
,
Comput. Phys. Commun.
135
,
40
(
2001
).
35.
S.
Kumar
,
J. M.
Rosenberg
,
D.
Bouzida
,
R. H.
Swendsen
, and
P. A.
Kollman
,
J. Comput. Chem.
13
,
1011
(
1992
).
36.
A.
Villa
,
C.
Peter
, and
N. F. A.
van der Vegt
,
J. Chem. Theory Comput.
6
,
2434
(
2010
).
37.
F.
Knoch
,
K.
Schäfer
,
G.
Diezemann
, and
T.
Speck
,
J. Chem. Phys.
148
,
044109
(
2018
).
38.
U.
Seifert
,
Phys. Rev. Lett.
84
,
2750
(
2000
).
39.
T.
Erdmann
and
U.
Schwarz
,
Europhys. Lett.
66
,
603
(
2004
).
40.
G.
Diezemann
and
A.
Janshoff
,
J. Chem. Phys.
129
,
084904
(
2008
).
41.
G.
Hummer
and
A.
Szabo
,
Biophys. J.
85
,
5
(
2003
).
42.
K.
Schulten
,
Z.
Schulten
, and
A.
Szabo
,
J. Chem. Phys.
74
,
4426
(
1981
).
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