Reverse conformational changes of the light chain-binding domain of myosin V and VI processive motor heads during and after hydrolysis of ATP by small-angle X-ray solution scattering

Taste substance binding elicits conformational change of taste receptor T1r heterodimer extracellular domains

Sweet and umami tastes are perceived by T1r taste receptors in oral cavity. T1rs are class C G-protein coupled receptors (GPCRs), and the extracellular ligand binding domains (LBDs) of T1r1/T1r3 and T1r2/T1r3 heterodimers are responsible for binding of chemical substances eliciting umami or sweet taste. However, molecular analyses of T1r have been hampered due to the difficulties in recombinant expression and protein purification, and thus little is known about mechanisms for taste perception. Here we show the first molecular view of reception of a taste substance by a taste receptor, where the binding of the taste substance elicits a different conformational state of T1r2/T1r3 LBD heterodimer. Electron microscopy has showed a characteristic dimeric structure. Förster resonance energy transfer and X-ray solution scattering have revealed the transition of the dimerization manner of the ligand binding domains, from a widely spread to compactly organized state upon taste substance binding, which may correspond to distinct receptor functional states.

Difference in hydration structures between F-actin and myosin subfragment-1 detected by small-angle X-ray and neutron scattering

Hydration structures around F-actin and myosin subfragment-1 (S1), which play central roles as counterparts in muscle contraction, were investigated by small-angle X-ray scattering (SAXS) and small-angle neutron scattering (SANS). The radius of gyration of chymotryptic S1 was evaluated to be 41.3±1.1 Å for SAXS, 40.1±3.0 Å for SANS in H₂O, and 37.8±0.8 Å for SANS in D₂O, respectively. The values of the cross-sectional radius of gyration of F-actin were 25.4±0.03 Å for SAXS, 23.4±2.4 Å for SANS in H₂O, and 22.6 ± 0.6 Å for SANS in D₂O, respectively. These differences arise from different contributions of the hydration shell to the scattering curves. Analysis by model calculations showed that the hydration shell of S1 has the average density 10–15% higher than bulk water, being the typical hydration shell. On the other hand, the hydration shell of F-actin has the average density more than 19% higher than bulk water, indicating that F-actin has a denser, unusual hydration structure. The results indicate a difference in the hydration structures around F-actin and S1. The unusual hydration structure around F-actin may have the structural property of so-called “hyper-mobile water” around F-actin.

Accurate flexible fitting of high-resolution protein structures to small-angle x-ray scattering data using a coarse-grained model with implicit hydration shell

Small-angle x-ray scattering (SAXS) is a powerful technique widely used to explore conformational states and transitions of biomolecular assemblies in solution. For accurate model reconstruction from SAXS data, one promising approach is to flexibly fit a known high-resolution protein structure to low-resolution SAXS data by computer simulations. This is a highly challenging task due to low information content in SAXS data. To meet this challenge, we have developed what we believe to be a novel method based on a coarse-grained (one-bead-per-residue) protein representation and a modified form of the elastic network model that allows large-scale conformational changes while maintaining pseudobonds and secondary structures. Our method optimizes a pseudoenergy that combines the modified elastic-network model energy with a SAXS-fitting score and a collision energy that penalizes steric collisions. Our method uses what we consider a new implicit hydration shell model that accounts for the contribution of hydration shell to SAXS data accurately without explicitly adding waters to the system. We have rigorously validated our method using five test cases with simulated SAXS data and three test cases with experimental SAXS data. Our method has successfully generated high-quality structural models with root mean-squared deviation of 1 ∼ 3 Å from the target structures.