Dynamic Balance between Protein Core and Solvent Shell: Ultrafast Hemin Dynamics Maps Energy Flow in Non-heme Proteins

Energy flow is the hidden force that drives vital processes in biomolecules, from catalysis to molecular transport. While heme proteins have long been the centerpiece of studies on rapid energy dissipation, ultrafast energy flow in non-heme proteins (and those lacking intrinsic cofactors), some of which are key players in drug delivery and nutrient transport, remains relatively less explored experimentally. Here, we set out to uncover energy flow in human serum albumin (HSA), bovine serum albumin (BSA), and β-lactoglobulin (β-LG) by incorporating hemin chloride as the photoreceptor and utilizing femtosecond transient absorption spectroscopy. HSA and BSA, despite having structural similarities, showed different hemin relaxation behaviors, arising from subtle variations in their hemin-binding pocket environments. In β-LG, on the other hand, hemin binds at the monomer-monomer interface (thereby disrupting the native dimer state) and hence remains the most exposed to the surrounding solvent bath, exhibited a slower energy transfer. To gain a better understanding, we also investigated hemin dynamics in aqueous and organic solvents as well as in micellar environments (normal and reverse micelles), uncovering that hydrophobic solvents sped up energy relaxation while water slowed it down. Surfactants such as SDS (sodium dodecyl sulphate), Brij 35 (polyoxyethylene(23)lauryl ether), and CTAB (cetyltrimethylammonium bromide) offered distinctive handles on factors affecting energy flow, while reverse micelles enabled a more controlled energy dissipation under varying degrees of confinement, mimicking biological environments. These findings illuminate how subtle shifts in external environments can dramatically reshape energy dynamics. Considering the importance and universality of energy flow, such perceptions are fundamental to gaining a broader understanding of the manner in which the physiological interior succeeds in driving a vast array of biological processes at their optimum.