A refined model of the chlorosomal antennae of the green bacterium Chlorobium tepidum from proton chemical shift constraints obtained with high-field2-D and 3-D MAS NMR dipolar correlation spectroscopy
Bj. Van Rossum et al., A refined model of the chlorosomal antennae of the green bacterium Chlorobium tepidum from proton chemical shift constraints obtained with high-field2-D and 3-D MAS NMR dipolar correlation spectroscopy, BIOCHEM, 40(6), 2001, pp. 1587-1595
Heteronuclear 2-D and 3-D magic-angle spinning NMR dipolar correlation spec
troscopy was applied to determine solid-state H-1 shifts for aggregated bac
teriochlorophyll c (BChl c) in uniformly C-13- enriched light harvesting ch
lorosomes of the green photosynthetic bacterium Chlorobium tepidum. A compl
ete assignment of 29 different observable resonances of the 61 protons of t
he aggregated BChl c in the intact chlorosomes is obtained, Aggregation shi
fts relative to monomeric BChl c in solution are detected for protons attac
hed to rings I, II, and III/V and to their side chains. The 2(1)-H-3, 3(2)-
H-3, and 3(1)-H resonances are shifted upfield by -2.2, -1, and -3.3 ppm, r
espectively, relative to monomeric BChl c in solution. Although the resonan
ces are inhomogeneously broadened and reveal considerable global structural
heterogeneity, the 5-CH and the 7-Me responses are doubled, which provides
evidence for the existence of at least two relatively well-defined structu
rally different arrangements. Ab initio quantum chemical modeling studies w
ere performed to refine a model for the self-assembled BChl c with two diff
erent types of BChl stacks. The BChl in the stacks can adopt either anti- o
r syn-configuration of the coordinative bond, where anti and syn designate
the relative orientation of the Mg-OH bond relative to the direction of the
17-17(1) bond. The analogy between aggregation shifts for BChl c in the ch
lorosome and for self-assembled chlorophyll a/H2O is explored, and a bilaye
r model for the tubular supra-structure of sheets of BChl c is proposed, fr
om a homology modeling approach.