ct8b01069_si_002.zip (14.98 MB)
Assessment of MC-PDFT Excitation Energies for a Set of QM/MM Models of Rhodopsins
dataset
posted on 2019-02-05, 00:00 authored by María
del Carmen Marín, Luca De Vico, Sijia S. Dong, Laura Gagliardi, Donald G. Truhlar, Massimo OlivucciA methodology for the automatic production
of quantum mechanical/molecular
mechanical (QM/MM) models of retinal-binding rhodopsin proteins and
subsequent prediction of their spectroscopic properties has been proposed
recently by some of the authors. The technology employed for the evaluation
of the excitation energies is called Automatic Rhodopsin Modeling
(ARM), and it involves the use of the complete active space self-consistent
field (CASSCF) method followed by a multiconfiguration second-order
perturbation theory (in particular, CASPT2) calculation of external
correlation energies. Although it was shown that ARM is capable of
successfully reproducing and predicting spectroscopic property trends
in chromophore-embedding protein sets, practical applications of such
technology are limited by the high computational costs of the multiconfiguration
perturbation theory calculations. In the present work we benchmark
the more affordable multiconfiguration pair-density functional theory
(MC-PDFT) method whose accuracy has been recently validated for retinal
chromophores in the gas phase, indicating that MC-PDFT could potentially
be used to analyze large (e.g., few hundreds) sets of rhodopsin proteins.
Here, we test this theory for a set of rhodopsin QM/MM models whose
experimental absorption maxima (λamax) have been measured. The results
indicate that MC-PDFT may be employed to calculate λamax values for this important
class of photoresponsive proteins.
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correlation energiesretinal-binding rhodopsin proteinsCASSCFmethodgas phaserhodopsin proteinsmax valuesmulticonfiguration pair-densityMC-PDFT Excitation Energiesphotoresponsive proteinsexcitation energieschromophore-embedding protein setsCASPTspectroscopic propertiesperturbation theorytechnologyspectroscopic property trendsAutomatic Rhodopsin Modelingmulticonfiguration perturbation theory calculationsmodelQM
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