PMID- 27045328
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20180124
LR  - 20180124
IS  - 1549-9626 (Electronic)
IS  - 1549-9618 (Linking)
VI  - 12
IP  - 5
DP  - 2016 May 10
TI  - A Direct Method for Incorporating Experimental Data into Multiscale 
      Coarse-Grained Models.
PG  - 2144-53
LID - 10.1021/acs.jctc.6b00043 [doi]
AB  - To extract meaningful data from molecular simulations, it is necessary to 
      incorporate new experimental observations as they become available. Recently, a 
      new method was developed for incorporating experimental observations into 
      molecular simulations, called experiment directed simulation (EDS), which 
      utilizes a maximum entropy argument to bias an existing model to agree with 
      experimental observations while changing the original model by a minimal amount. 
      However, there is no discussion in the literature of whether or not the minimal 
      bias systematically and generally improves the model by creating agreement with 
      the experiment. In this work, we show that the relative entropy of the biased 
      system with respect to an ideal target is always reduced by the application of a 
      minimal bias, such as the one utilized by EDS. Using all-atom simulations that 
      have been biased with EDS, one can then easily and rapidly improve a bottom-up 
      multiscale coarse-grained (MS-CG) model without the need for a time-consuming 
      reparametrization of the underlying atomistic force field. Furthermore, the 
      improvement given by the many-body interactions introduced by the EDS bias can be 
      maintained after being projected down to effective two-body MS-CG interactions. 
      The result of this analysis is a new paradigm in coarse-grained modeling and 
      simulation in which the "bottom-up" and "top-down" approaches are combined within 
      a single, rigorous formalism based on statistical mechanics. The utility of 
      building the resulting EDS-MS-CG models is demonstrated on two molecular systems: 
      liquid methanol and ethylene carbonate.
FAU - Dannenhoffer-Lafage, Thomas
AU  - Dannenhoffer-Lafage T
AD  - Department of Chemistry, James Franck Institute, Institute for Biophysical 
      Dynamics, and Computation Institute, The University of Chicago , 5735 South Ellis 
      Avenue, Chicago, Illinois 60637, United States.
FAU - White, Andrew D
AU  - White AD
AD  - Department of Chemistry, James Franck Institute, Institute for Biophysical 
      Dynamics, and Computation Institute, The University of Chicago , 5735 South Ellis 
      Avenue, Chicago, Illinois 60637, United States.
FAU - Voth, Gregory A
AU  - Voth GA
AD  - Department of Chemistry, James Franck Institute, Institute for Biophysical 
      Dynamics, and Computation Institute, The University of Chicago , 5735 South Ellis 
      Avenue, Chicago, Illinois 60637, United States.
LA  - eng
PT  - Journal Article
DEP - 20160415
PL  - United States
TA  - J Chem Theory Comput
JT  - Journal of chemical theory and computation
JID - 101232704
EDAT- 2016/04/06 06:00
MHDA- 2016/04/06 06:01
CRDT- 2016/04/06 06:00
PHST- 2016/04/06 06:00 [entrez]
PHST- 2016/04/06 06:00 [pubmed]
PHST- 2016/04/06 06:01 [medline]
AID - 10.1021/acs.jctc.6b00043 [doi]
PST - ppublish
SO  - J Chem Theory Comput. 2016 May 10;12(5):2144-53. doi: 10.1021/acs.jctc.6b00043. 
      Epub 2016 Apr 15.