Department of Biotechnologies, Chemistry and Pharmacy , University of Siena , 53100 Siena , Italy.
Chemistry Department , Bowling Green State University , Bowling Green , 43403 Ohio , United States.
J Chem Theory Comput. 2019 Mar 12;15(3):1915-1923. doi: 10.1021/acs.jctc.8b01069. Epub 2019 Feb 20.
A 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 (λ ) have been measured. The results indicate that MC-PDFT may be employed to calculate λ values for this important class of photoresponsive proteins.
最近,作者中的一些人提出了一种用于自动生成结合视黄醛的蛋白的量子力学/分子力学(QM/MM)模型并预测其光谱性质的方法。用于评估激发能的技术称为自动视黄醛建模(ARM),它涉及使用完全活性空间自洽场(CASSCF)方法,然后进行多组态二级微扰理论(特别是 CASPT2)的外部相关能计算。虽然已经表明 ARM 能够成功地复制和预测发色团嵌入蛋白组中的光谱性质趋势,但该技术的实际应用受到多组态微扰理论计算的高计算成本的限制。在本工作中,我们基准测试了更经济的多组态对密度泛函理论(MC-PDFT)方法,该方法的准确性最近已在气相中的视黄醛上得到验证,表明 MC-PDFT 可能可用于分析大型(例如,几百个)视蛋白集。在这里,我们对一组视蛋白 QM/MM 模型进行了测试,这些模型的实验吸收最大值(λ)已经被测量。结果表明,MC-PDFT 可用于计算此类重要的光响应蛋白的 λ 值。