Computational simulations of excitation energy transfer and electron transfer in biological systems
Embargo Date
2028-06-05
OA Version
Citation
Abstract
Exploring excitation energy and electron transfer in proteins and other macromolecules is key to understanding many vital biological processes. In acquiring a deeper conceptualization of electron and excitation energy transfer pathways in a breadth of biological environments, we gain the ability to understand the common structural and energetic patterns enabling these processes. As high level quantum calculations of an entire macromolecule are prohibitively expensive, and classical studies lack insight into electronic states, hybrid quantum-classical approaches are the most promising for simulating this type of process. In this dissertation we have used and developed techniques aimed to advance two directions of theoretical characterization of excitation and electron transfer processes in biomolecules: (i) accurate description of the energetic parameters of excitation energy transfer in photosynthetic complexes (ii) identification of the electron transfer pathways in proteins based on their crystal structure. The two specific projects addressing these aims are outlined below. The first direction of the work presented in this dissertation concerns characterizing the energetic landscape of the PCP complex in order to gain insight into the contested mechanism of highly efficient excitation energy transfer. As accurate energetic parameters are needed and it has been shown that protein polarization can have a significant effect on electronic properties such as ionization/attachment energies, redox potentials, and excitation energies, BioEFP, a polarizable QM/MM method, was thoroughly explored in the context of characterizing excited states of peridinin. Subsequently, the obtained energetic parameters for peridinin, as well as chlorophyll, were further used to construct an excitonic Hamiltonian model for the system. The second direction concerns the development of eMap 2.0, an open-source web-based software, which extends the capabilities of eMap from analyzing ETPs in single proteins to multiple proteins. This development allows users an intuitive way to screen families of proteins for the existence of common electron transfer pathways, and can provide insight into protein function and evolution. We demonstrate this new ability through analyzing protein families including cryptochromes/photolyases, Ia RNR, and bCcPs/MauGs. We will further demonstrate how eMap can be used in conjunction with other bioinformatic and AI structure-prediction tools to identify ETP rooted functions based on sequence data alone.
Description
2025
License
Attribution-NonCommercial 4.0 International