Low-cost bacterial production of the receptor binding domain (RBD) of the SARS-CoV-2 Omicron spike protein holds significant potential in expediting the development of therapeutics against COVID-19. However, RBD contains eight cysteines forming four disulfide bonds, and expression in E. coli using standard protocols produces insoluble RBD forming non-native disulfide bonds. Here, we expressed RBD in E. coli T7 SHuffle with high aeration, which enhanced disulfide formation in the cytoplasm and reshuffling of non-native disulfide bonds, and at a low temperature of 16°C, which stabilized the native conformation and thus the formation of the native disulfide bonds. The yield of RBD was as high as 3 mg per 200 mL culture. We analyzed the conformational and biophysical properties of our E. coli-expressed RBD. First, the RP-HPLC elution profile indicated a single peak, suggesting that RBD was folded with a single disulfide bond pairing pattern. Next, circular dichroism analysis indicated a secondary structure content very close to that computed from the crystal structure. RBD’s thermal denaturation monitored by CD was cooperative, strongly indicating a well-folded protein structure. Moreover, limited proteolysis showed that RBD was nearly as stable as RNase A, and the formation of native disulfide bonds was confirmed by LC-MS analysis. Furthermore, BLI analysis indicated a strong binding of RBD with the hACE2 with a dissociation constant of 0.83 nM, confirming the folded nature of RBD. Altogether, these results demonstrate that our E. coli-expression system can provide a large amount of highly purified RBD with correct disulfide bonds and native-like biochemical and biophysical properties.

In the gastropod mollusk Lymnaea stagnalis, insulin-like peptides in the central nervous system (CNS) control behavioral changes associated with associative learning. Insulin administration to the Lymnaea CNS enhances the synaptic plasticity involved in this type of learning, but it has remained unclear which molecules in the insulin response cascade are involved. Here, to advance a comprehensive analysis, we used two-dimensional electrophoresis and comparative quantitative mass spectrometry to perform a protein analysis investigating the CNS molecules that respond to insulin administration. Our results revealed increased phosphorylation of AKT and RICTOR in the PI3K/AKT/mTOR signaling cascade and cytoskeleton-related proteins. Although it was expected that the molecules in the PI3K/AKT/mTOR signaling cascade were phosphorylated by insulin administration, our findings confirmed the correlation between insulin-induced phosphorylation of cytoskeleton-related proteins strongly involved in the synaptic changes and learning and memory mechanisms. These results contribute to elucidate the relationship between the insulin response and learning and memory mechanisms not only in Lymnaea but also in various invertebrates and vertebrates.

Aggregates of amyloid-β (Aβ) peptides are thought to cause Alzheimer’s disease. Polyphenolic compounds are known to inhibit Aβ aggregation. We applied replica permutation with solute tempering (RPST) to the system of Aβ fragments, Aβ(16–22), and polyphenols to elucidate the mechanism of inhibition of Aβ aggregation. The RPST molecular dynamics simulations were performed for two polyphenols, myricetin (MYC) and rosmarinic acid (ROA). Two Aβ fragments were distant, and the number of residues forming the intermolecular β-sheet was reduced in the presence of MYC and ROA compared with that in the absence of polyphenols. MYC was found to interact with glutamic acid and phenylalanine of Aβ fragments. These interactions induce helix structure formation of Aβ fragments, making it difficult to form β-sheet. ROA interacted with glutamic acid and lysine, which reduced the hydrophilic interaction between Aβ fragments. These results indicate that these polyphenols inhibit the aggregation of Aβ fragments with different mechanisms.

The consistency principle represents a physicochemical condition requisite for ideal protein folding. It assumes that any pair of amino acid residues in partially folded structures has an attractive short-range interaction only if the two residues are in contact within the native structure. The residue-specific equilibrium constant, K, and the residue-specific rate constant, k (forward and backward), can be determined by NMR and hydrogen-deuterium exchange studies. Linear free energy relationships (LFER) in the rate-equilibrium free energy relationship (REFER) plots (i.e., log k vs. log K) are widely seen in protein-related phenomena, but our REFER plot differs from them in that the data points are derived from one polypeptide chain under a single condition. Here, we examined the theoretical basis of the residue-based LFER. First, we derived a basic equation, ρ_ij=½(φ_i+φ_j), from the consistency principle, where ρ_ij is the slope of the line segment that connects residues i and j in the REFER plot, and φ_i and φ_j are the local fractions of the native state in the transient state ensemble (TSE). Next, we showed that the general solution is the alignment of the (log K, log k) data points on a parabolic curve in the REFER plot. Importantly, unlike LFER, the quadratic free energy relationship (QFER) is compatible with the heterogeneous formation of local structures in the TSE. Residue-based LFER/QFER provides a unique insight into the TSE: A foldable polypeptide chain consists of several folding units, which are consistently coupled to undergo smooth structural changes.

A small and flexible molecule, ribocil A (non-binder) or B (binder), binds to the deep pocket of the aptamer domain of the FMN riboswitch, which is an RNA molecule. This binding was studied by mD-VcMD, which is a generalized-ensemble simulation method. Ribocil A and B are structurally similar because they are optical isomers to each other. In the initial conformation of simulation, the ligands and the aptamer were completely dissociated in explicit solvent. The aptamer–ribocil B binding was stronger than the aptamer–ribocil A binding, which agrees with experiments. The computed free-energy landscape for the aptamer–ribocil B binding was funnel-like, whereas that for the aptamer–ribocil A binding was rugged. When passing through the gate (named “front gate”) of the binding pocket, each ligand interacted with bases of the riboswitch by non-native π-π stackings, and the stackings restrained the ligand’s orientation to be advantageous to reach the binding site smoothly. When the ligands reached the binding site in the pocket, the non-native stackings were replaced by the native stackings. The ligand’s orientation restriction is discussed referring to a selection mechanism reported in an earlier work on a drug–GPCR interaction. The present simulation showed another pathway leading the ligands to the binding site. The gate (“rear gate”) for this pathway was located completely opposite to the front gate on the aptamer’s surface. However, the approach from the rear gate required overcoming a free-energy barrier regarding ligand’s rotation before reaching the binding site.