Characterizing the protein landscape in thylakoid membranes of Chlamydomonas reinhardtii using a Monte Carlo-simulated annealing algorithm

Abstract

Thylakoid membrane organization plays a crucial role in photosynthetic efficiency, yet the spatial arrangement of protein complexes within the membrane remains challenging to resolve experimentally. To address this, we developed a computational framework that employs coarse-grained modeling and advanced algorithms to simulate the distribution of major protein complexes, including PSII supercomplexes, cytb₆f, and LHCII. By systematically varying membrane size and protein composition, we analyzed protein organization using statistical methods such as the radial distribution function (g(r)) and the nearest neighbor distribution function (NNDF). Comparing our simulated membranes to experimental cryo-electron tomography (cryo-ET) data, we observed strong agreement in protein spacing and clustering trends. Specifically, our results indicate that Chlamydomonas thylakoid membranes primarily contain the C₂S₂M₂ PSII supercomplex, as suggested by NNDF comparisons. While the presence of larger C₂S₂M₂N₂ complexes has been reported, their abundance likely varies depending on environmental conditions and stress factors. These findings demonstrate the potential of our computational approach to complement experimental techniques, providing insights into protein organization at a resolution that remains difficult to achieve in in situ studies. Future applications of this framework could extend to different membrane systems and varying physiological conditions, further refining our understanding of dynamic thylakoid architecture.Chemistr