Detangling energy and charge transfer in Photosystem I

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Lyudmila Slipchenko of Purdue University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop computational methodologies and software tools for predictive modeling of energy and charge transfer in photosynthetic complexes, and to provide computational analysis of the main steps of energy transfer and charge separation in Photosystem I. Photosystems I (PS I) is a major complex shared by all oxygenic photosynthetic organisms utilized for sunlight energy conversion on Earth. The structure and function of PS I is optimized by evolution and preserved for billions of years. However, while disentangling the structure-function relations in this highly efficient natural solar cell is essential for designing optimal routes of solar energy conversion, molecular-level understanding of energy transfer and charge separation in PS I lacks critical details. Slipchenko will develop efficient and robust computational methodology in which hybrid quantum-classical description of the photosynthetic protein is augmented with machine learning algorithms. Using these models, Slipchenko and her research group will pursue to elucidate the structure-function relations in PS I that can be mimicked and templated in artificial photocells. The developed methodology will provide the community of computational chemists with new algorithms and tools for efficient and rigorous modeling of complex molecular systems. Slipchenko’s research program will provide training opportunity for participating students and postdocs in the field of theoretical and computational electronic structure theory and data science. Lyudmila Slipchenko and her group will develop computational methodologies and software tools for predictive modeling of energy and charge transfer in photosynthetic complexes. The method developments are based on (i) hybrid machine learning, quantum and classical mechanics models that dramatically speed up ground and excited state calculations in biological systems, and (ii) energy decomposition models for electronic excited states that elucidate the structure-function relations in a coupled system. Empowered by the new methodological developments and expertise in modeling photosynthetic proteins of the Fenna-Matthews-Olson (FMO) family, Slipchenko group is pursuing to build the system Hamiltonian consistent with optical signatures of energy transfer and charge separation in Photosystem I, and to elucidate kinetics of the primary charge-separation events and the role of accessory pigments in the PS I reaction center. Understanding of the structure-function relations in PS I is of both fundamental and practical importance as PS I encompasses an evolutionary optimized photovoltaic machinery that can be mimicked and templated in artificial photoelectronic devices. The developed algorithms, computational codes and machine learning potentials provide the community of computational chemists with tools for efficient and rigorous modeling of complex molecular systems. All developed codes will be available to the community via open-source libraries and software packages libefp, GAMESS, GROMACS, and open-source modules in the Q-Chem quantum chemistry software.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.