PMID- 18601324
OWN - NLM
STAT- MEDLINE
DCOM- 20080828
LR  - 20240318
IS  - 1089-7690 (Electronic)
IS  - 0021-9606 (Print)
IS  - 0021-9606 (Linking)
VI  - 128
IP  - 24
DP  - 2008 Jun 28
TI  - The multiscale coarse-graining method. I. A rigorous bridge between atomistic and 
      coarse-grained models.
PG  - 244114
LID - 10.1063/1.2938860 [doi]
LID - 244114
AB  - Coarse-grained (CG) models provide a computationally efficient method for rapidly 
      investigating the long time- and length-scale processes that play a critical role 
      in many important biological and soft matter processes. Recently, Izvekov and 
      Voth introduced a new multiscale coarse-graining (MS-CG) method [J. Phys. Chem. B 
      109, 2469 (2005); J. Chem. Phys. 123, 134105 (2005)] for determining the 
      effective interactions between CG sites using information from simulations of 
      atomically detailed models. The present work develops a formal statistical 
      mechanical framework for the MS-CG method and demonstrates that the variational 
      principle underlying the method may, in principle, be employed to determine the 
      many-body potential of mean force (PMF) that governs the equilibrium distribution 
      of positions of the CG sites for the MS-CG models. A CG model that employs such a 
      PMF as a "potential energy function" will generate an equilibrium probability 
      distribution of CG sites that is consistent with the atomically detailed model 
      from which the PMF is derived. Consequently, the MS-CG method provides a formal 
      multiscale bridge rigorously connecting the equilibrium ensembles generated with 
      atomistic and CG models. The variational principle also suggests a class of 
      practical algorithms for calculating approximations to this many-body PMF that 
      are optimal. These algorithms use computer simulation data from the atomically 
      detailed model. Finally, important generalizations of the MS-CG method are 
      introduced for treating systems with rigid intramolecular constraints and for 
      developing CG models whose equilibrium momentum distribution is consistent with 
      that of an atomically detailed model.
FAU - Noid, W G
AU  - Noid WG
AD  - Center for Biophysical Modeling and Simulation and Department of Chemistry, 
      University of Utah, Salt Lake City, Utah 84112-0850, USA.
FAU - Chu, Jhih-Wei
AU  - Chu JW
FAU - Ayton, Gary S
AU  - Ayton GS
FAU - Krishna, Vinod
AU  - Krishna V
FAU - Izvekov, Sergei
AU  - Izvekov S
FAU - Voth, Gregory A
AU  - Voth GA
FAU - Das, Avisek
AU  - Das A
FAU - Andersen, Hans C
AU  - Andersen HC
LA  - eng
GR  - F32 GM076839/GM/NIGMS NIH HHS/United States
GR  - 5 F32 GM076839-02/GM/NIGMS NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, U.S. Gov't, Non-P.H.S.
PL  - United States
TA  - J Chem Phys
JT  - The Journal of chemical physics
JID - 0375360
SB  - IM
CIN - J Chem Phys. 128:244115. PMID: 18601325
CIN - J. Phys. Chem. B 109, 2469 (2005). PMID: 16851243
CIN - J. Chem. Phys. 123, 134105 (2005). PMID: 16223273
MH  - Computer Simulation
MH  - *Models, Chemical
MH  - Models, Statistical
MH  - Statistical Distributions
PMC - PMC2671183
EDAT- 2008/07/08 09:00
MHDA- 2008/08/30 09:00
PMCR- 2009/06/28
CRDT- 2008/07/08 09:00
PHST- 2008/07/08 09:00 [pubmed]
PHST- 2008/08/30 09:00 [medline]
PHST- 2008/07/08 09:00 [entrez]
PHST- 2009/06/28 00:00 [pmc-release]
AID - 506824JCP [pii]
AID - 10.1063/1.2938860 [doi]
PST - ppublish
SO  - J Chem Phys. 2008 Jun 28;128(24):244114. doi: 10.1063/1.2938860.