Project 3

Multiscale modeling of energy transport for light-harvesting and non-photochemical quenching in higher plants

University of Pisa, Italy

Principal Investigator
Prof. Benedetta Mennucci

Assistant Investigator
Prof. Lorenzo Cupellini

Doctoral Candidate
Joel Santos

Project Description:

The main objectives of this project will be subdivided into several stages: first, we will establish a detailed structural and excitonic description of the M–CP2 subdomain, the key complex involved in light harvesting and non-photochemical quenching (NPQ) in higher plants. This description will be achieved through a multiscale approach that combines classical molecular dynamics (MD) simulations in a lipid bilayer environment with high-level (quantum mechanics/molecular mechanics) QM/MM calculations, accelerated by machine learning (ML) techniques for efficient and accurate site energy estimation. Once we have a robust exciton Hamiltonian, we will perform quantum master equation simulations to predict energy transfer pathways and spectroscopic properties. These simulations will further be extended to incorporate quenching mechanisms, allowing us to systematically identify and quantify energy dissipation routes under various structural and environmental conditions. Ultimately, this workflow will yield molecular-level insights into the regulation of photosynthesis, guiding future work on targeted protein mutations, functional optimization of antenna systems, and potential biomimetic applications in solar energy technologies.

Publications:

  1. Piermarco Saraceno, Samim Sardar, Roberto Caferri, Franco V. A. Camargo, Luca Dall’Osto, Cosimo D’Andrea, Roberto Bassi, Lorenzo Cupellini, Giulio Cerullo, and Benedetta Mennucci. Probing the Effect of Mutations on Light Harvesting in CP29 by Transient Absorption and First-Principles Simulations. The Journal of Physical Chemistry Letters 2024 15 (24), 6398-6408
  2. Elena Betti, Piermarco Saraceno, Edoardo Cignoni, Lorenzo Cupellini, and Benedetta Mennucci. Insights into Energy Transfer in Light-Harvesting Complex II Through Machine-Learning Assisted Simulations. The Journal of Physical Chemistry B 2024128 (21), 5188-5200.
  3. Edoardo Cignoni, Vladislav Slama, Lorenzo Cupellini, Benedetta Mennucci; The atomistic modeling of light-harvesting complexes from the physical models to the computational protocol. J. Chem. Phys. 28 March 2022; 156 (12): 120901