Yoshitake Sakae

Exploration of Conformational Spaces of High‐Mannose‐Type Oligosaccharides by an NMR‐Validated Simulation

Exploration of the conformational spaces of flexible biomacromolecules is essential for quantitatively understanding the energetics of their molecular recognition processes. We employed stable isotope- and lanthanide-assisted NMR approaches in conjunction with replica-exchange molecular dynamics (REMD) simulations to obtain atomic descriptions of the conformational dynamics of high-mannose-type oligosaccharides, which harbor intracellular glycoprotein-fate determinants in their triantennary structures. The experimentally validated REMD simulation provided quantitative views of the dynamic conformational ensembles of the complicated, branched oligosaccharides, and indicated significant expansion of the conformational space upon removal of a terminal mannose residue during the functional glycan-processing pathway.

Optimization of protein force-field parameters with the Protein Data Bank

We propose a novel method to optimize existing force-field parameters for protein systems. The method consists of minimizing the summation of the square of the force acting on each atom in the proteins with the structures from the Protein Data Bank. We performed this optimization to the partial-charge and torsion-energy parameters of the AMBER parm94 force field, using 100 molecules from the Protein Data Bank. We then performed folding simulations of α-helical and β-hairpin peptides. The optimized force-field parameters gave structures more consistent with the experimental implications than the original AMBER force field.

Secondary-Structure Design of Proteins by a Backbone Torsion Energy

We propose a new backbone-torsion-energy term in the force field for protein systems. This torsion-energy term is represented by a double Fourier series in two variables, the backbone dihedral angl...

PROTEIN FORCE-FIELD PARAMETERS OPTIMIZED WITH THE PROTEIN DATA BANK. I. FORCE-FIELD OPTIMIZATIONS

We optimized five existing sets of force-field parameters for protein systems by our recently proposed method. The five force fields are AMBER parm94, AMBER parm96, AMBER parm99, CHARMM version 22, and OPLS-AA. The method consists of minimizing the sum of the square of the force acting on each atom in the proteins with the structures from the Protein Data Bank (PDB). We selected the partial-charge and backbone torsion-energy parameters for this optimization, and 100 molecules from the PDB were used. We gave detailed comparisons of the optimized force fields and found that there is a tendency of convergence towards the same function for the torsion-energy term.

PROTEIN FORCE-FIELD PARAMETERS OPTIMIZED WITH THE PROTEIN DATA BANK II: COMPARISONS OF FORCE FIELDS BY FOLDING SIMULATIONS OF SHORT PEPTIDES

In Paper I of this series, the formulations of the optimization method of existing force-field parameters for protein systems have been presented. We then applied it to five sets of force-field parameters, namely, AMBER parm94, AMBER parm96, AMBER parm99, CHARMM version 22, and OPLS-AA. In order to test the validity of these force fields, the folding simulations of α-helical and β-hairpin peptides have been performed with each of the original and optimized force-field parameters. We found that all five modified force-field parameters gave both α-helical and β-hairpin structures more consistent with the experimental implications than the original force fields.

Conformational dynamics of oligosaccharides characterized by paramagnetism-assisted NMR spectroscopy in conjunction with molecular dynamics simulation.

Oligosaccharides play pivotal roles in physiological and pathological contexts primarily through their interactions with proteins on cell surfaces and in intracellular environments. Although crystallographic approaches provide cumulative information about the atomic details of oligosaccharides complexed with proteins, quantitative characterization of the dynamic conformation of uncomplexed oligosaccharides is essential for better understanding of the energetics of carbohydrate–protein interactions. Nuclear magnetic resonance (NMR) spectroscopy is a potentially powerful tool for describing the conformational dynamics of oligosaccharides in solutions at an atomic resolution. However, methodological improvements are needed in applying NMR techniques to the analyses of the dynamic conformations of oligosaccharides during sample preparation, spectral observation, and data interpretation. This presentation outlines our recently developed method of dealing with dynamic conformational ensembles of oligosaccharides using paramagnetism-assisted NMR spectroscopy in conjunction with molecular dynamics (MD) simulation. A key to this approach is the introduction of a paramagnetic lanthanide ion to the reducing end of oligosaccharides as the source of the atomic long-distance information. We successfully applied this method to the validation of MD-derived conformational spaces occupied by a series of sialyl oligosaccharide moieties of GM1, GM2, and GM3 gangliosides. The applicability of NMR is also revealed for characterizing the dynamic interactions of ganglioside clusters with intrinsically disordered proteins associated with neurodegenerative disorders using ganglioside-embedding small bicelles as nanoscale standardized membrane mimics.

Protein structure predictions by parallel simulated annealing molecular dynamics using genetic crossover.

We propose a conformational search method to find a global minimum energy structure for protein systems. The simulated annealing is a powerful method for local conformational search. On the other hand, the genetic crossover can search the global conformational space. Our method incorporates these attractive features of the simulated annealing and genetic crossover. In the previous works, we have been using the Monte Carlo algorithm for simulated annealing. In the present work, we use the molecular dynamics algorithm instead. To examine the effectiveness of our method, we compared our results with those of the normal simulated annealing molecular dynamics simulations by using an α‐helical miniprotein. We used genetic two‐point crossover here. The conformations, which have lower energy than those obtained from the conventional simulated annealing, were obtained.

Structure–function insights into direct lipid transfer between membranes by Mmm1–Mdm12 of ERMES

The endoplasmic reticulum (ER)–mitochondrial encounter structure (ERMES) physically links the membranes of the ER and mitochondria in yeast. Although the ER and mitochondria cooperate to synthesize glycerophospholipids, whether ERMES directly facilitates the lipid exchange between the two organelles remains controversial. Here, we compared the x-ray structures of an ERMES subunit Mdm12 from Kluyveromyces lactis with that of Mdm12 from Saccharomyces cerevisiae and found that both Mdm12 proteins possess a hydrophobic pocket for phospholipid binding. However in vitro lipid transfer assays showed that Mdm12 alone or an Mmm1 (another ERMES subunit) fusion protein exhibited only a weak lipid transfer activity between liposomes. In contrast, Mdm12 in a complex with Mmm1 mediated efficient lipid transfer between liposomes. Mutations in Mmm1 or Mdm12 impaired the lipid transfer activities of the Mdm12–Mmm1 complex and furthermore caused defective phosphatidylserine transport from the ER to mitochondrial membranes via ERMES in vitro. Therefore, the Mmm1–Mdm12 complex functions as a minimal unit that mediates lipid transfer between membranes.

Controlling the secondary-structure-forming tendencies of proteins by a backbone torsion-energy term

We examined a new backbone torsion-energy term proposed by us in the force field for protein systems. This torsion-energy term is represented by a double Fourier series in two variables, namely the backbone dihedral angles φ and ψ. It gives a natural representation of the torsion energy in the Ramachandran space in the sense that any two-dimensional energy surface periodic in both φ and ψ can be expanded by the double Fourier series. We can then easily control secondary-structure-forming tendencies by modifying the torsion-energy surface. For instance, we can increase or decrease the α-helix-forming-tendencies by lowering or raising the torsion-energy surface in the α-helix region and likewise increase or decrease the β-sheet-forming tendencies by lowering or raising the surface in the β-sheet region in the Ramachandran space. We applied this torsion-energy modification method to six force fields, AMBER parm94, AMBER parm96, AMBER parm99, CHARMM27, OPLS-AA and OPLS-AA/L, and demonstrated that our modifications of the torsion-energy terms resulted in the expected changes of secondary-structure-forming tendencies by performing folding simulations of α-helical and β-hairpin peptides.

Conformational effects of N -glycan core fucosylation of immunoglobulin G Fc region on its interaction with Fcγ receptor IIIa

Antibody-dependent cellular cytotoxicity (ADCC) is promoted through interaction between the Fc region of immunoglobulin G1 (IgG1) and Fcγ receptor IIIa (FcγRIIIa), depending on N-glycosylation of these glycoproteins. In particular, core fucosylation of IgG1-Fc N-glycans negatively affects this interaction and thereby compromises ADCC activity. To address the mechanisms of this effect, we performed replica-exchange molecular dynamics simulations based on crystallographic analysis of a soluble form of FcγRIIIa (sFcγRIIIa) in complex with IgG1-Fc. Our simulation highlights increased conformational fluctuation of the N-glycan at Asn162 of sFcγRIIIa upon fucosylation of IgG1-Fc, consistent with crystallographic data giving no interpretable electron density for this N-glycan, except for the innermost part. The fucose residue disrupts optimum intermolecular carbohydrate-carbohydrate interactions, rendering this sFcγRIIIa glycan distal from the Fc glycan. Moreover, our simulation demonstrates that core fucosylation of IgG1-Fc affects conformational dynamics and rearrangements of surrounding amino acid residues, typified by Tyr296 of IgG1-Fc, which was more extensively involved in the interaction with sFcγRIIIa without Fc core fucosylation. Our findings offer a structural foundation for designing and developing therapeutic antibodies with improved ADCC activity.