Department of Chemistry and Physics, 400 Cedar Ave, Monmouth University, West Long Branch, New Jersey, 07764.
J Comput Chem. 2018 Mar 30;39(8):438-449. doi: 10.1002/jcc.25134. Epub 2017 Dec 15.
Excitation energy transfer (EET) determines the fate of sunlight energy absorbed by light-harvesting proteins in natural photosynthetic systems and photovoltaic cells. As previously reported (D. Kosenkov, J. Comput. Chem. 2016, 37(19), 1847), PyFREC software enables computation of electronic couplings between organic molecules with a molecular fragmentation approach. The present work reports implementation of direct fragmentation-based computation of the electronic couplings and EET rates in pigment-protein complexes within the Förster theory in PyFREC. The new feature enables assessment of EET pathways in a wide range of photosynthetic complexes, as well as artificial molecular architectures that include light-harvesting proteins or tagged fluorescent biomolecules. The developed methodology has been tested analyzing EET in the Fenna-Matthews-Olson (FMO) pigment-protein complex. The pathways of excitation energy transfer in FMO have been identified based on the kinetics studies. © 2017 Wiley Periodicals, Inc.
激发能转移(EET)决定了天然光合作用系统和光伏电池中光捕获蛋白吸收的太阳光能量的命运。如前所述(D. Kosenkov,J. Comput. Chem. 2016,37(19),1847),PyFREC 软件能够通过分子分段方法计算有机分子之间的电子偶合。本工作报告了在 PyFREC 中,在福斯特理论内,用直接分段法计算色素-蛋白复合物中的电子偶合和 EET 速率。该新功能能够评估广泛的光合作用复合物以及包括光捕获蛋白或标记荧光生物分子的人工分子结构中的 EET 途径。所开发的方法学已通过分析 Fenna-Matthews-Olson(FMO)色素-蛋白复合物中的 EET 进行了测试。基于动力学研究,确定了 FMO 中激发能转移的途径。©2017 年 Wiley 期刊,Inc.