Abstract
Molecular dynamics simulations often adopt coarse-grained (CG) models to investigate length- and time-scales that cannot be effectively addressed with atomically detailed models. However, the effective potentials that govern CG models are configuration-dependent free energies with significant entropic contributions that have important consequences for the transferability and thermodynamic properties of CG models. This review summarizes recent work investigating the fundamental origin and practical ramifications of these entropic contributions, as well as their sensitivity to the CG mapping. We first analyze the energetic and entropic components of the many-body potential of mean force. By adopting a simple model for protein fluctuations, we examine how these components vary with the CG representation. We then introduce a “dual potential” approach for addressing these entropic considerations in more complex systems, such as ortho-terphenyl (OTP). We demonstrate that this dual approach not only accurately describes the structure and energetic properties of the underlying atomic model, but also accurately predicts the temperature-dependence of the CG potentials. Furthermore, by considering two different CG representations of OTP, we elucidate how these contributions vary with resolution. In sum, we hope this work will prove useful for improving the transferability and thermodynamic properties of CG models for soft materials.
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Data availability statement
The manuscript has associated data in a data repository. [Authors’ comment: The data that support the findings of this study are available from the Penn State DataCommons repository: https://www.datacommons.psu.edu. The data for Figures 3-5 are available at DataCommons with the https://doi.org/10.26208/139c-8x65. The data for Figures 7-8 are available at DataCommons under the title “Systematic study of temperature and density variations in effective potentials for coarse-grained models of molecular liquids.” The data for Figures 9-10 are available at DataCommons with the https://doi.org/10.26208/sj0e-pj49. The data for Figures 12-16 are available at DataCommons with the https://doi.org/10.26208/45tq-fw66. The data for Figures 1 and 2, as well as the images for Figures 6 and 11 will be available at DataCommons under the title of this paper and also at a DOI to be published.]
References
M.L. Klein, W. Shinoda, Science 321(5890), 798 (2008). https://doi.org/10.1126/science.1157834
C. Peter, K. Kremer, Faraday Discuss. 144, 9 (2010)
M. Guenza, M. Dinpajooh, J. McCarty, I. Lyubimov, J. Phys. Chem. B 122(45), 10257 (2018)
M. Muller, K. Katsov, M. Schick, Phys. Rep. 434(5–6), 113 (2006). https://doi.org/10.1016/j.physrep.2006.08.003
F. Schmid, Macromol. Rapid Comm. 30(9–10), 741 (2009). https://doi.org/10.1002/marc.200800750
M. Deserno, Macromol. Rapid Comm. 30(9–10), 752 (2009). https://doi.org/10.1002/marc.200900090
W.G. Noid, J. Chem. Phys. 139(9), 090901 (2013). https://doi.org/10.1063/1.4818908
W.G. Noid, Methods Mol. Biol. 924, 487 (2013). https://doi.org/10.1007/978-1-62703-017-5_19
M.G. Saunders, G.A. Voth, Annu. Rev. Biophys. 42, 73 (2013). https://doi.org/10.1146/annurev-biophys-083012-130348
E. Brini, E.A. Algaer, P. Ganguly, C. Li, F. Rodríguez-Ropero, N.F.A. van der Vegt, Soft Matter 9, 2108 (2013). https://doi.org/10.1039/C2SM27201F
R. Potestio, C. Peter, K. Kremer, Entropy 16(8), 4199 (2014). https://doi.org/10.3390/e16084199
H.I. Ingólfsson, C.A. Lopez, J.J. Uusitalo, D.H. de Jong, S.M. Gopal, X. Periole, S.J. Marrink, Wiley Interdiscipl. Rev. Comput. Mol. Sci. 4(3), 225 (2014). https://doi.org/10.1002/wcms.1169
S. Kmiecik, D. Gront, M. Kolinski, L. Wieteska, A.E. Dawid, A. Kolinski, Chem. Rev. 116, 7898 (2016)
S.Y. Joshi, S.A. Deshmukh, Mol. Simul. 2020, 1–18 (2020)
M. Giulini, M. Rigoli, G. Mattiotti, R. Menichetti, T. Tarenzi, R. Fiorentini, R. Potestio, Front. Mol. Biosci. 8, 460 (2021). https://doi.org/10.3389/fmolb.2021.676976
J.F. Rudzinski, Computing 7(3), 42 (2019)
A. Liwo, C. Czaplewski, J. Pillardy, H.A. Scheraga, J. Chem. Phys. 115, 2323 (2001)
C.N. Likos, Phys. Rep. 348(4–5), 267 (2001). https://doi.org/10.1016/S0370-1573(00)00141-1
R.L.C. Akkermans, W.J. Briels, J. Chem. Phys. 114(2), 1020 (2001). https://doi.org/10.1063/1.1330744
N.J.H. Dunn, T.T. Foley, W.G. Noid, Acc. Chem. Res. 49(12), 2832 (2016)
M.E. Tuckerman, Statistical Mechanics: Theory and Molecular Simulation (Oxford University Press, Oxford, Great Britain, 2013)
W.G. Noid, J.W. Chu, G.S. Ayton, V. Krishna, S. Izvekov, G.A. Voth, A. Das, H.C. Andersen, J. Chem. Phys. 128, 244114 (2008)
G. Ciccotti, R. Kapral, E. Vanden-Eijnden, ChemPhysChem 6, 1809 (2005)
L. Zhang, J. Han, H. Wang, R. Car, W.E. Noe, J. Chem. Phys. 149(3), 034101 (2018). https://doi.org/10.1063/1.5027645
W. Wang, R. Gómez-Bombarelli, NPJ Comput. Mat. 5(1), 125 (2019). https://doi.org/10.1038/s41524-019-0261-5
J.F. Rudzinski, W.G. Noid, J. Chem. Phys. 135(21), 214101 (2011). https://doi.org/10.1063/1.3663709
S. Kullback, R.A. Leibler, Ann. Math. Stat. 22(1), 79 (1951)
T.T. Foley, M.S. Shell, W.G. Noid, J. Chem. Phys. 143, 243104 (2015)
J.G. Kirkwood, J. Chem. Phys. 3(5), 300 (1935)
D. Frenkel, B. Smit, Understanding Molecular Simulation: From Algorithms to Applications, 2nd edn. (Academic Press, San Diego, 2002)
J.W. Wagner, J.F. Dama, A.E.P. Durumeric, G.A. Voth, J. Chem. Phys. 145(4), 044108 (2016). https://doi.org/10.1063/1.4959168
K.M. Lebold, W.G. Noid, J. Chem. Phys. 151(16), 164113 (2019)
T.T. Foley, K.M. Kidder, M.S. Shell, W. Noid, Proc. Natl. Acad. Sci. USA 117(39), 24061 (2020)
P.J. Flory, M. Gordon, N.G. McCrum, Proc. R. Soc. Lond. A: Math. Phys. Sci. 351(1666), 351 (1976). https://doi.org/10.1098/rspa.1976.0146
T. Haliloglu, I. Bahar, B. Erman, Phys. Rev. Lett. 79, 3090 (1997)
I. Bahar, T.R. Lezon, L.W. Yang, E. Eyal, Annu. Rev. Biophys. 39, 23 (2010). https://doi.org/10.1146/annurev.biophys.093008.131258
J.M. Harris, J.L. Hirst, M.J. Mossinghoff, Combinatorics and Graph Theory (Springer, Berlin, 2010)
M.C. Wang, G.E. Uhlenbeck, Rev. Mod. Phys. 17, 323 (1945)
T.R. Lezon, I. Bahar, PLoS Comput. Biol. 6(6), e1000816 (2010). https://doi.org/10.1371/journal.pcbi.1000816
D.A. McQuarrie, Statistical Mechanics (University Science Books, Berlin, 2000)
R. Baron, A.H. de Vries, P.H. Hünenberger, W.F. van Gunsteren, J. Phys. Chem. B 110(16), 8464 (2006). https://doi.org/10.1021/jp055888y
R. Baron, V. Molinero, J. Chem. Theory Comput. 8(10), 3696 (2012). https://doi.org/10.1021/ct300121r
S.T. Lin, M. Blanco, W. Goddard, J. Chem. Phys. 119, 11792 (2003)
M.P. Bernhardt, M. Dallavalle, N.F. Van der Vegt, Soft Mater. 2020, 1–16 (2020)
E. Brini, V. Marcon, N.F.A. van der Vegt, Phys. Chem. Chem. Phys. 13(22), 10468 (2011). https://doi.org/10.1039/c0cp02888f
A.P. Lyubartsev, A. Laaksonen, Phys. Rev. E 55, 5689 (1997). https://doi.org/10.1103/PhysRevE.55.5689
G.G. Rondina, M.C. Böhm, F. Müller-Plathe, J. Chem. Theory Comput. 16(3), 1431 (2020)
M.K. Meinel, F. Müller-Plathe, J. Chem. Theory Comput. 16(3), 1411 (2020)
M.E.J. Newman, G.T. Barkema, Monte Carlo Methods in Statistical Physics (Clarendon Press, Hoboken, 1999)
M.R. Shirts, J.D. Chodera, J. Chem. Phys. 129(12), 124105 (2008)
H. Gohlke, M.F. Thorpe, Biophys. J. 91, 2115 (2006)
Z.Y. Zhang, L.Y. Lu, W.G. Noid, V. Krishna, J. Pfaendtner, G.A. Voth, Biophys. J. 95(11), 5073 (2008)
Z.Y. Zhang, G.A. Voth, J. Chem. Theory Comput. 6(9), 2990 (2010). https://doi.org/10.1021/ct100374a
P. Koehl, F. Poitevin, R. Navaza, M. Delarue, J. Chem. Theory Comput. 13(3), 1424 (2017)
M. Girvan, M.E.J. Newman, Proc. Natl. Acad. Sci. USA 99(12), 7821 (2002). https://doi.org/10.1073/pnas.122653799
J. Reichardt, S. Bornholdt, Phys. Rev. E 74, 1 (2006). https://doi.org/10.1103/PhysRevE.74.016110
S. Fortunato, Phys. Rep. 486(3–5), 75 (2010). https://doi.org/10.1016/j.physrep.2009.11.002
M.T. Schaub, J.C. Delvenne, S.N. Yaliraki, M. Barahona, PLoS One, 2012, p. e32210. https://doi.org/10.1371/journal.pone.0032210
M. Giulini, R. Menichetti, M.S. Shell, R. Potestio, J. Chem. Theory Comput. 16(11), 6795 (2020)
D.H.E. Gross, Microcanonical Thermodynamics (WORLD SCIENTIFICWORLD, 2001). https://doi.org/10.1142/4340
L. Boninsegna, R. Banisch, C. Clementi, J. Chem. Theory Comput. 14(1), 453 (2018). https://doi.org/10.1021/acs.jctc.7b00990. (Publisher: American Chemical Society)
M.A. Webb, J.Y. Delannoy, J.J. de Pablo, J. Chem. Theory Comput. (2018). https://doi.org/10.1021/acs.jctc.8b00920
M. Chakraborty, C. Xu, A.D. White, J. Chem. Phys. 149(13), 134106 (2018)
J. Wang, S. Olsson, C. Wehmeyer, A. Pérez, N.E. Charron, G. De Fabritiis, F. Noé, C. Clementi, A.C.S. Cent, Science 5(5), 755 (2019)
J. Ruza, W. Wang, D. Schwalbe-Koda, S. Axelrod, W.H. Harris, R. Gómez-Bombarelli, J. Chem. Phys. 153(16), 164501 (2020)
Z. Li, G.P. Wellawatte, M. Chakraborty, H.A. Gandhi, C. Xu, A.D. White, Chemistry 11(35), 9524 (2020)
M. Chakraborty, J. Xu, A.D. White, Phys. Chem. Chem. Phys. 22(26), 14998 (2020)
S. Izvekov, G.A. Voth, J. Phys. Chem. B 109, 2469 (2005)
S. Izvekov, G.A. Voth, J. Chem. Phys. 123, 134105 (2005)
W.G. Noid, P. Liu, Y.T. Wang, J.W. Chu, G.S. Ayton, S. Izvekov, H.C. Andersen, G.A. Voth, J. Chem. Phys. 128, 244115 (2008)
M. Dallavalle, N.F. van der Vegt, Phys. Chem. Chem. Phys. 19(34), 23034 (2017)
A. Khot, S.B. Shiring, B.M. Savoie, J. Chem. Phys. 151(24), 244105 (2019)
V.A. Harmandaris, D. Reith, N.F.A. Van der Vegt, K. Kremer, Macromol. Chem. Phys. 208, 2109 (2007). https://doi.org/10.1002/macp.200700245
O. Bezkorovaynaya, A. Lukyanov, K. Kremer, C. Peter, J. Comp. Chem. 33(9), 937 (2012). https://doi.org/10.1002/jcc.22915
T. Ohkuma, K. Kremer, Polymer 130, 88 (2017)
J.F. Rudzinski, W.G. Noid, J. Chem. Theory Comput. 11(3), 1278 (2015)
J.F. Rudzinski, W.G. Noid, J. Phys. Chem. B 118(28), 8295 (2014)
J.F. Rudzinski, W.G. Noid, J. Phys. Chem. B 116(29), 8621 (2012). https://doi.org/10.1021/jp3002004
J.F. Rudzinski, W.G. Noid, Eur. Phys. J.: Spec. Top. 224, 2193 (2015)
J. Jin, G.A. Voth, J. Chem. Theory Comput. 14, 2180 (2018)
A. Chaimovich, M.S. Shell, Phys. Rev. E 89(2), 022140 (2014)
C. Scherer, D. Andrienko, Phys. Chem. Chem. Phys. 20(34), 22387 (2018)
J.I. Monroe, M.S. Shell, J. Chem. Phys. 151(9), 094501 (2019)
J. Jin, Y. Han, A.J. Pak, G.A. Voth, J. Chem. Phys. 154(4), 044104 (2021)
J. Jin, A.J. Pak, Y. Han, G.A. Voth, J. Chem. Phys. 154(4), 044105 (2021)
M.S. Shell, J. Chem. Phys. 129, 144108 (2008)
A. Chaimovich, M.S. Shell, J. Chem. Phys. 134(9), 094112 (2011)
M.S. Shell, Coarse-Graining with the Relative Entropy (Wiley, Hoboken, 2016). https://doi.org/10.1002/9781119290971.ch5
A. Isihara, J. Phys. A: Math. Nucl. Gen. 1(5), 539 (1968)
A. Lyubartsev, A. Mirzoev, L.J. Chen, A. Laaksonen, Faraday Discuss. 144, 43 (2010)
D. Reith, M. Pütz, F. Müller-Plathe, J. Comp. Chem. 24, 1624 (2003)
A.P. Lyubartsev, A. Laaksonen, Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscipl. Top. 52, 3730 (1995)
T. Murtola, M. Karttunen, I. Vattulainen, J. Chem. Phys. 131, 055101 (2009)
N.J.H. Dunn, W.G. Noid, J. Chem. Phys. 144, 204124 (2016)
F. Ercolessi, J.B. Adams, Europhys. Lett. 26, 583 (1994)
A.J. Chorin, Multiscale Model. Simul. 1, 105 (2003)
A.J. Chorin, O.H. Hald, Stochastic Tools in Mathematics and Science (Springer, New York, 2006)
W.G. Noid, J.W. Chu, G.S. Ayton, G.A. Voth, J. Phys. Chem. B 111, 4116 (2007)
A. Das, H.C. Andersen, J. Chem. Phys. 132, 164106 (2010)
N.J.H. Dunn, W.G. Noid, J. Chem. Phys. 143(24), 243148 (2015)
J.W. Mullinax, W.G. Noid, Phys. Rev. Lett. 103, 198104 (2009)
J.W. Mullinax, W.G. Noid, J. Phys. Chem. C 114, 5661 (2010)
S.P. Carmichael, M.S. Shell, J. Phys. Chem. B 116(29), 8383 (2012). https://doi.org/10.1021/jp2114994
S.Y. Mashayak, M.N. Jochum, K. Koschke, N.R. Aluru, V. Rühle, C. Junghans, PLOS One 2015, 20 (2015)
L. Larini, L.Y. Lu, G.A. Voth, J. Chem. Phys. 132(16), 164107 (2010)
J.A. Harrison, J.D. Schall, S. Maskey, P.T. Mikulski, M.T. Knippenberg, B.H. Morrow, App. Phys. Rev. 5(3), 031104 (2018). https://doi.org/10.1063/1.5020808
A.A. Louis, J. Phys.: Condens. Matter 14, 9187 (2002)
M.E. Johnson, T. Head-Gordon, A.A. Louis, J. Chem. Phys. 126, 144509 (2007)
F.H. Stillinger, H. Sakai, S. Torquato, J. Chem. Phys. 117(1), 288 (2002). https://doi.org/10.1063/1.1480863
Y.T. Wang, W.G. Noid, P. Liu, G.A. Voth, Phys. Chem. Chem. Phys. 11(12), 2002 (2009). https://doi.org/10.1039/b819182d
A.J. Clark, J. McCarty, I.Y. Lyubimov, M.G. Guenza, Phys. Rev. Lett. 109, 168301 (2012). https://doi.org/10.1103/PhysRevLett.109.168301
J. McCarty, A.J. Clark, J. Copperman, M.G. Guenza, J. Chem. Phys. 140(20), 204913 (2014)
G. D’Adamo, A. Pelissetto, C. Pierleoni, J. Chem. Phys. 138(23), 234107 (2013). https://doi.org/10.1063/1.4810881
J. Ghosh, R. Faller, Mol. Simul. 33, 759 (2007)
P. Carbone, H.A.K. Varzaneh, X. Chen, F. Müller-Plathe, J. Chem. Phys. 128, 064904 (2008)
D.M. Huang, R. Faller, K. Do, A.J. Moule, J. Chem. Theory Comput. 6(2), 526 (2010). https://doi.org/10.1021/ct900496t. PMID: 26617308
G. Megariotis, A. Vyrkou, A. Leygue, D.N. Theodorou, Ind. Eng. Chem. Res. 50, 546 (2011)
B. Mukherjee, L. Delle Site, K. Kremer, C. Peter, J. Phys. Chem. B 116(29), 8474 (2012)
A. Mirzoev, A.P. Lyubartsev, Phys. Chem. Chem. Phys. 13, 5722 (2011). https://doi.org/10.1039/C0CP02397C
Q. Xiao, H. Guo, Phys. Chem. Chem. Phys. 18, 29808 (2016). https://doi.org/10.1039/C6CP03753D
T.D. Potter, J. Tasche, M.R. Wilson, Phys. Chem. Chem. Phys. 21, 1912 (2019). https://doi.org/10.1039/C8CP05889J
S. Mortezazadeh, Y. Jamali, H. Naderi-Manesh, A.P. Lyubartsev, PLoS One 14, e0214673 (2019)
J.W. Mullinax, W.G. Noid, J. Chem. Phys. 131, 104110 (2009)
T.C. Moore, C.R. Iacovella, C. McCabe, J. Chem. Phys. 140(22), 224104 (2014)
J.F. Rudzinski, K. Lu, S.T. Milner, J.K. Maranas, W.G. Noid, J. Chem. Theory Comput. 13(5), 2185 (2017)
T. Sanyal, J. Mittal, M.S. Shell, J. Chem. Phys. 151(4), 044111 (2019)
K. Shen, N. Sherck, M. Nguyen, B. Yoo, S. Köhler, J. Speros, K.T. Delaney, G.H. Fredrickson, M.S. Shell, J. Chem. Phys. 153(15), 154116 (2020)
J.F. Rudzinski, T. Bereau, J. Chem. Phys. 153(21), 214110 (2020)
J. Zhang, H. Guo, J. Phys. Chem. B 118(17), 4647 (2014). https://doi.org/10.1021/jp411615f
F. Cao, H. Sun, J. Chem. Theory Comput. 11, 4760 (2015). https://doi.org/10.1021/acs.jctc.5b00573
J. Jin, A. Yu, G.A. Voth, J. Chem. Theory Comput. 16(11), 6823 (2020)
J. Xia, Q. Xiao, H. Guo, Polymer 148, 284 (2018)
C. Hu, T. Lu, H. Guo, J. Chem. Inf. Model. 59(5), 2009 (2019). https://doi.org/10.1021/acs.jcim.8b00887
T. Vettorel, H. Meyer, J. Chem. Theory Comput. 2, 616 (2006)
H.J. Qian, P. Carbone, X. Chen, H.A. Karimi-Varzaneh, C.C. Liew, F. Müller-Plathe, Macromolecules 41(24), 9919 (2008)
A. Chaimovich, M.S. Shell, Phys. Chem. Chem. Phys. 11(12), 1901 (2009). https://doi.org/10.1039/b818512c
K. Farah, A.C. Fogarty, M.C. Böhm, F. Müller-Plathe, Phys. Chem. Chem. Phys. 13(7), 2894 (2011). https://doi.org/10.1039/c0cp01333a
L. Lu, G.A. Voth, J. Chem. Phys. 134(22), 224107 (2011). https://doi.org/10.1063/1.3599049
A. Liwo, M. Khalili, C. Czaplewski, S. Kalinowski, S. Ołdziej, K. Wachucik, H.A. Scheraga, J. Phys. Chem. B 111(1), 260 (2007). https://doi.org/10.1021/jp065380a
G. Deichmann, M. Dallavalle, D. Rosenberger, N.F. van der Vegt, J. Phys. Chem. B 123(2), 504 (2018)
D. Rosenberger, N.F.A. van der Vegt, Phys. Chem. Chem. Phys. 20, 6617 (2018). https://doi.org/10.1039/c7cp08246k
C. Hu, T. Lu, H. Guo, J. Chem. Inf. Model. 59(5), 2009 (2019)
Y. Li, V. Agrawal, J. Oswald, J. Polym. Sci., Part B: Polym. Phys. 57(6), 331 (2019)
M. King, S. Pasler, C. Peter, J. Phys. Chem. C 123(5), 3152 (2019)
K.M. Lebold, W.G. Noid, J. Chem. Phys. 150(1), 014104 (2019)
R.J. Szukalo, W. Noid, Soft Mater. 18, 1 (2020)
K.M. Lebold, W.G. Noid, J. Chem. Phys. 150, 234107 (2019)
J. Jin, A.J. Pak, G.A. Voth, J. Phys. Chem. Lett. 10(16), 4549 (2019)
R.J. Szukalo, W.G. Noid, J. Phys.: Condens. Matter 33(15), 154004 (2021). https://doi.org/10.1088/1361-648x/abdff8
A.P. Lyubartsev, A. Laaksonen, Phys. Rev. E 55(5), 5689 (1997)
J.F. Dama, A.V. Sinitskiy, M. McCullagh, J. Weare, B. Roux, A.R. Dinner, G.A. Voth, J. Chem. Theory Comput. 9, 2466 (2013). https://doi.org/10.1021/ct4000444
F. Müller-Plathe, ChemPhysChem 3, 754 (2002)
H. Wang, C. Junghans, K. Kremer, Eur. Phys. J. E: Soft Matter Biol. Phys. 28(2), 221 (2009)
I. Pagonabarraga, D. Frenkel, J. Chem. Phys. 115(11), 5015 (2001)
T. Sanyal, M.S. Shell, J. Chem. Phys. 145(3), 034109 (2016). https://doi.org/10.1063/1.4958629
M.R. DeLyser, W.G. Noid, J. Chem. Phys. 147, 134111 (2017)
T. Sanyal, M.S. Shell, J. Phys. Chem. B 122, 5678 (2018)
M.R. DeLyser, W. Noid, J. Chem. Phys. 151(22), 224106 (2019)
M. DeLyser, W. Noid, J. Chem. Phys. 153(22), 224103 (2020)
N. Shahidi, A. Chazirakis, V. Harmandaris, M. Doxastakis, J. Chem. Phys. 152(12), 124902 (2020). https://doi.org/10.1063/1.5143245
G. Tóth, J. Phys.: Condens. Matter 19(33), 335222 (2007). https://doi.org/10.1088/0953-8984/19/33/335222
T. Dannenhoffer-Lafage, J.W. Wagner, A.E.P. Durumeric, G.A. Voth, J. Chem. Phys. 151(13), 134115 (2019). https://doi.org/10.1063/1.5116027
M.D. Ediger, C.A. Angell, S.R. Nagel, J. Chem. Phys. 100(31), 13200 (1996)
L. Berthier, G. Biroli, Rev. Mod. Phys. 83(2), 587 (2011)
X. Song, M. Jensen, V. Jogini, R.A. Stein, C.H. Lee, H.S. Mchaourab, D.E. Shaw, E. Gouaux, Nature 556(7702), 515 (2018). https://doi.org/10.1038/s41586-018-0039-9
W. Xia, J. Song, N.K. Hansoge, F.R. Phelan Jr., S. Keten, J.F. Douglas, J. Phys. Chem. B 122(6), 2040 (2018)
W.L. Jorgensen, D.S. Maxwell, J. Tirado-Rives, J. Am. Chem. Soc. 118, 11225 (1996)
N.J.H. Dunn, K.M. Lebold, M.R. DeLyser, J.F. Rudzinski, W.G. Noid, J. Phys. Chem. B 122(13), 3363 (2018). https://doi.org/10.1021/acs.jpcb.7b09993
W. Humphrey, A. Dalke, K. Schulten, J. Mol. Graph. 14, 33 (1996)
Acknowledgements
The authors gratefully acknowledge the essential contributions of Tommy Foley, M. Scott Shell, and Kate Lebold to the prior studies that are explicitly discussed herein. The authors also acknowledge former group members Michael DeLyser, Nick Dunn, Joe Rudzinski, and Wayne Mullinax, who made important contributions to the computational methods employed in these studies. The authors gratefully acknowledge financial support from the National Science Foundation (Grant nos. MCB-1053970, CHE-1565631, CHE-1856337) that made this work possible, as well as a fellowship to Kate Lebold from the Molecular Sciences Software Institute under NSF Grant No. ACI-1547580. Portions of this research were conducted with Advanced CyberInfrastructure computational resources provided by The Institute for Computational and Data Sciences at The Pennsylvania State University (http://icds.psu.edu). In addition, parts of this research were conducted with XSEDE resources awarded by Grant TG - CHE170062. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation (Grant ACI-1548562). Figs. 1-3, 11, and 15, and 16 employed VMD [169]. VMD is developed with NIH support by the Theoretical and Computational Biophysics group at the Beckman Institute, University of Illinois at Urbana-Champaign.
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KK and RS contributed equally to this work under the supervision of WN, KK and RS both performed original calculations and analyzed previously published results. KK, RS, and WN wrote and edited the manuscript.
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Kidder, K.M., Szukalo, R.J. & Noid, W.G. Energetic and entropic considerations for coarse-graining. Eur. Phys. J. B 94, 153 (2021). https://doi.org/10.1140/epjb/s10051-021-00153-4
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DOI: https://doi.org/10.1140/epjb/s10051-021-00153-4