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@ARTICLE{Dittrich:1007045,
author = {Dittrich, Jonas and Popara, Milana and Kubiak, Jakub and
Dimura, Mykola and Schepers, Bastian and Verma, Neha and
Schmitz, Birte and Dollinger, Peter and Kovacic, Filip and
Jaeger, Karl-Erich and Seidel, Claus A. M. and Peulen,
Thomas-Otavio and Gohlke, Holger},
title = {{R}esolution of {M}aximum {E}ntropy {M}ethod-{D}erived
{P}osterior {C}onformational {E}nsembles of a {F}lexible
{S}ystem {P}robed by {FRET} and {M}olecular {D}ynamics
{S}imulations},
journal = {Journal of chemical theory and computation},
volume = {19},
number = {8},
issn = {1549-9618},
address = {Washington, DC},
reportid = {FZJ-2023-01951},
pages = {2389 - 2409},
year = {2023},
abstract = {Maximum entropy methods (MEMs) determine posterior
distributions by combining experimental data with prior
information. MEMs are frequently used to reconstruct
conformational ensembles of molecular systems for
experimental information and initial molecular ensembles. We
performed time-resolved Förster resonance energy transfer
(FRET) experiments to probe the interdye distance
distributions of the lipase-specific foldase Lif in the apo
state, which likely has highly flexible, disordered, and/or
ordered structural elements. Distance distributions
estimated from ensembles of molecular dynamics (MD)
simulations serve as prior information, and FRET
experiments, analyzed within a Bayesian framework to recover
distance distributions, are used for optimization. We tested
priors obtained by MD with different force fields (FFs)
tailored to ordered (FF99SB, FF14SB, and FF19SB) and
disordered proteins (IDPSFF and FF99SBdisp). We obtained
five substantially different posterior ensembles. As in our
FRET experiments the noise is characterized by photon
counting statistics, for a validated dye model, MEM can
quantify consistencies between experiment and prior or
posterior ensembles. However, posterior populations of
conformations are uncorrelated to structural similarities
for individual structures selected from different prior
ensembles. Therefore, we assessed MEM simulating varying
priors in synthetic experiments with known target ensembles.
We found that (i) the prior and experimental information
must be carefully balanced for optimal posterior ensembles
to minimize perturbations of populations by overfitting and
(ii) only ensemble-integrated quantities like inter-residue
distance distributions or density maps can be reliably
obtained but not ensembles of atomistic structures. This is
because MEM optimizes ensembles but not individual
structures. This result for a highly flexible system
suggests that structurally varying priors calculated from
varying prior ensembles, e.g., generated with different FFs,
may serve as an ad hoc estimate for MEM reconstruction
robustness.},
cin = {IBG-4 / NIC / JSC / IBG-1 / IMET},
ddc = {610},
cid = {I:(DE-Juel1)IBG-4-20200403 / I:(DE-Juel1)NIC-20090406 /
I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IBG-1-20101118 /
I:(DE-Juel1)IMET-20090612},
pnm = {2171 - Biological and environmental resources for
sustainable use (POF4-217) / 5111 - Domain-Specific
Simulation $\&$ Data Life Cycle Labs (SDLs) and Research
Groups (POF4-511) / Forschergruppe Gohlke $(hkf7_20200501)$
/ Analysis of the conformational changes during activation
of lipase A by its foldase $(hdd16_20171101)$},
pid = {G:(DE-HGF)POF4-2171 / G:(DE-HGF)POF4-5111 /
$G:(DE-Juel1)hkf7_20200501$ / $G:(DE-Juel1)hdd16_20171101$},
typ = {PUB:(DE-HGF)16},
pubmed = {37023001},
UT = {WOS:000973179200001},
doi = {10.1021/acs.jctc.2c01090},
url = {https://juser.fz-juelich.de/record/1007045},
}