Abstract
<jats:p>Iron sulfur (Fe S) clusters are among the most ancient biological cofactors, yet the physical properties associated with the recurrent biological utilization of specific Fe S architectures remain unclear. Here, we analyzed 2,404 experimentally resolved Fe S clusters using an integrated framework combining structural geometry, geometry derived effective coupling network robustness, and coarse-grained open-system quantum transport simulations. We show that 4Fe 4S clusters occupy a compact and partially distinct region of structural descriptor space characterized by low geometric distortion, elevated geometry derived network robustness, and broad taxonomic representation within the available structural dataset. Geometry derived coarse grained effective Hamiltonian reconstruction and Lindblad simulations further showed architecture dependent differences in Hamiltonian organization and simulated transport behavior under a common set of model assumptions. Together, these findings establish a hierarchical comparative framework linking Fe S geometry, effective Hamiltonian organization, simulated open system transport, and broad taxonomic recurrence, and suggest that geometry-derived transport organization may represent one physical property contributing to the recurrent biological utilization of Fe S architectures.</jats:p>