Takefumi Yamashita

Hydrogen-bond assisted enormous broadening of infrared spectra of phenol-water cationic cluster: An ab initio mixed quantum-classical study

The infrared spectrum of phenol-water cationic cluster, [PhOH.H2O]+, taken by Sawamura et al. [J. Phys. Chem. 100, 8131 (1996)] is puzzling in that the peak due to the stretching mode of the phenolic OH (3657 cm-1 for a neutral monomer and 3524 cm-1 for PhOH.H2O) seemingly disappears and instead an extremely broad tail extending down to 2900 cm-1 is observed. The present authors theoretically ascribe this anomalous spectrum to an inhomogeneous broadening of the OH stretching peak caused by the hydrogen bond, the strength of which has been greatly enhanced by ionization of the phenyl ring. Indeed they estimate that the peak position is at 2300 cm-1 and the spectral width can become as wide as 1000 cm-1 at the cluster energy of 32 kcal/mol. This surprisingly wide broadening can be generic in hydrogen-bond systems, which in turn is useful to study the nature of the hydrogen-bond assisted dynamics in various systems such as those in DNA and proteins. To study the present system quantitatively, the authors have developed an ab initio mixed quantum-classical method, in which the nuclear motions on an adiabatic ab initio potential surface are treated such that only the OH stretching motion is described quantum mechanically, while all the other remaining modes are treated classically with on-the-fly scheme. This method includes the implementation of many numerical methodologies, which enables it to deal with a relatively large molecular system. With this theoretical method, the authors analyze the present anomalous broadening in a great detail. In particular, they suggest that one can extract direct information about the hydrogen-bond dynamics with respect to the clear correlation between the vibrational excitation energy of the OH stretching and intermolecular distance by means of a time-resolved infrared spectroscopy: Reflecting the slow and wide-range variation of the intermolecular distance of the relevant hydrogen bond, the time-resolved spectrum is predicted to vary (shift) largely covering the wide range of frequency domain. Thus, it is found that the short-time average along a selected trajectory sensitively reflects the change of the intermolecular distance. The authors also study the effect of internal energy on the hydrogen bonding and the OH spectrum.

The Feasibility of an Efficient Drug Design Method with High-Performance Computers

In this study, we propose a supercomputer-assisted drug design approach involving all-atom molecular dynamics (MD)-based binding free energy prediction after the traditional design/selection step. Because this prediction is more accurate than the empirical binding affinity scoring of the traditional approach, the compounds selected by the MD-based prediction should be better drug candidates. In this study, we discuss the applicability of the new approach using two examples. Although the MD-based binding free energy prediction has a huge computational cost, it is feasible with the latest 10 petaflop-scale computer. The supercomputer-assisted drug design approach also involves two important feedback procedures: The first feedback is generated from the MD-based binding free energy prediction step to the drug design step. While the experimental feedback usually provides binding affinities of tens of compounds at one time, the supercomputer allows us to simultaneously obtain the binding free energies of hundreds of compounds. Because the number of calculated binding free energies is sufficiently large, the compounds can be classified into different categories whose properties will aid in the design of the next generation of drug candidates. The second feedback, which occurs from the experiments to the MD simulations, is important to validate the simulation parameters. To demonstrate this, we compare the binding free energies calculated with various force fields to the experimental ones. The results indicate that the prediction will not be very successful, if we use an inaccurate force field. By improving/validating such simulation parameters, the next prediction can be made more accurate.

Molecular dynamics analysis to evaluate docking pose prediction

The accurate prediction of a ligand–protein complex structure is important for computer-assisted drug development. Although many docking methods have been developed over the last three decades, the success of binding structure prediction remains greatly limited. The purpose of this study was to demonstrate the usefulness of molecular dynamics (MD) simulation in assessing a docking pose predicted using a docking program. If the predicted pose is not unstable in an aqueous environment, MD simulation equilibrates the system and removes the ligand from the predicted position. Here we investigated two proteins that are important potential therapeutic targets: β2 adrenergic receptor (β2AR) and PR-Set7. While β2AR is rigid and its ligands are very similar to the template ligand (carazolol), PR-Set7 is very flexible and its ligands vary greatly from the template ligand (histone H4 tail peptide). On an empirical basis, we usually expect that the docking prediction is accurate when the protein is rigid and its ligands are similar to the template ligand. The MD analyses in this study clearly suggested such a tendency. Furthermore, we discuss the possibility that the MD simulation can predict the binding pose of a ligand.

Structural features of interfacial tyrosine residue in ROBO1 fibronectin domain-antibody complex: Crystallographic, thermodynamic, and molecular dynamic analyses

ROBO1, fibronectin Type‐III domain (Fn)‐containing protein, is a novel immunotherapeutic target for hepatocellular carcinoma in humans. The crystal structure of the antigen‐binding fragment (Fab) of B2212A, the monoclonal antibody against the third Fn domain (Fn3) of ROBO1, was determined in pursuit of antibody drug for hepatocellular carcinoma. This effort was conducted in the presence or absence of the antigen, with the chemical features being investigated by determining the affinity of the antibody using molecular dynamics (MD) and thermodynamics. The structural comparison of B2212A Fab between the complex and the free form revealed that the interfacial TyrL50 (superscripts L, H, and F stand for the residues in the light chain, heavy chain, and Fn3, respectively) played important roles in Fn3 recognition. That is, the aromatic ring of TyrL50 pivoted toward PheF68, forming a CH/π interaction and a new hydrogen bond with the carbonyl O atom of PheF68. MD simulations predicted that the TyrL50‐PheF68 interaction almost entirely dominated Fab‐Fn3 binding, and Ala‐substitution of TyrL50 led to a reduced binding of the resultant complex. On the contrary, isothermal titration calorimetry experiments underscored that Ala‐substitution of TyrL50 caused an increase of the binding enthalpy between B2212A and Fn3, but importantly, it induced an increase of the binding entropy, resulting in a suppression of loss in the Gibbs free energy in total. These results suggest that mutation analysis considering the binding entropy as well as the binding enthalpy will aid in the development of novel antibody drugs for hepatocellular carcinoma.

Energy quantization of chaos with the semiclassical phases alone

The mechanism of energy quantization is studied for classical dynamics on a highly anharmonic potential, ranging from integrable, mixed, and chaotic motions. The quantum eigenstates (standing waves) are created by the phase factors (the action integrals and the Maslov index) irrespective of the integrability, when the amplitude factors are relatively slowly varying. Indeed we show numerically that the time Fourier transform of an approximate semiclassical correlation function in which the amplitude factors are totally removed reproduces the spectral positions (energy eigenvalues) accurately in chaotic regime. Quantization with the phase information alone brings about dramatic simplification to molecular science, since the amplitude factors in the lowest order semiclassical approximation diverge exponentially in a chaotic domain.

Quasiclassical trajectory study of O(D1)+N2O→NO+NO: Classification of reaction paths and vibrational distribution

Quasiclassical trajectory calculations for the planar reaction of O(1D) + N2O --> NO + NO are performed on a newly constructed ab initio potential energy surface. In spite of the reduced dimension approximation, the agreement between the computational and experimental results is largely satisfactory, especially on the similar amount of excitation of the two kinds of NO products found by Akagi et al. [J. Chem. Phys. 111, 115 (1999)]. Analyzing the initial condition dependence of the trajectories, we find that the trajectories of this reaction can be classified into four reaction paths, which correspond to respective areas in the space of initial condition. In one of the four paths, a long-lived stable complex is formed in the course of reaction, whereas the other three paths have direct mechanism. Contradictory to conventional understanding of the chemical reaction dynamics, the direct paths show more efficient energy exchange between the NO stretching modes than that with a long-lived intermediate. This indicates that the vibrational mode coupling along the short-lived paths is considerably stronger than expected.

High performance computing for drug development on K computer

Massively parallel computations (MP-CAFEE) ware developed to calculate absolute binding free energies of small molecules bound to a protein by all-atom molecular dynamics. It uses the nonequilibrium work measurement and Bennett acceptance ratio methods to calculate the free energy difference between the bound and unbound states. The FUJI force field was developed in order to assign force field parameters to arbitrary organic molecules in a unified manner including proteins and nucleic acids. Its dihedral parameters agree with the torsion energy profiles calculated by high-level ab initio molecular orbital theory for the model systems of protein backbone. Comparing with various force fields it agrees well with recent observations by vibrational spectroscopy on Ramachandran angles population of alanine dipeptide in water. MP-CAFEE with FUJI force field has an efficient parallel algorithm and enough accuracy for computer aided drug design.

Toward rational antibody design: recent advancements in molecular dynamics simulations

Because antibodies have become an important therapeutic tool, rational antibody design is a challenging issue involving various science and technology fields. From the computational aspect, many types of design-assist methods have been developed, but their accuracy is not fully satisfactory. Because of recent advancements in computational power, molecular dynamics (MD) simulation has become a helpful tool to trace the motion of proteins and to characterize their properties. Thus, MD simulation has been applied to various systems involving antigen-antibody complexes and has been shown to provide accurate insight into antigen-antibody interactions and dynamics at an atomic resolution. Therefore, it is highly possible that MD simulation will play several roles complementing the conventional antibody design. In this review, we address several important features of MD simulation in the context of rational antibody design.

Tyrosine Sulfation Restricts the Conformational Ensemble of a Flexible Peptide, Strengthening the Binding Affinity for an Antibody

Protein tyrosine sulfation (PTS) is a post-translational modification regulating numerous biological events. PTS generally occurs at flexible regions of proteins, enhancing intermolecular interactions between proteins. Because of the high flexibility associated with the regions where PTS is generally encountered, an atomic-level understanding has been difficult to achieve by X-ray crystallography or nuclear magnetic resonance techniques. In this study, we focused on the conformational behavior of a flexible sulfated peptide and its interaction with an antibody. Molecular dynamics simulations and thermodynamic analysis indicated that PTS reduced the main-chain fluctuations upon the appearance of sulfate-mediated intramolecular H-bonds. Collectively, our data suggested that one of the mechanisms by which PTS may enhance protein-protein interactions consists of the limitation of conformational dynamics in the unbound state, thus reducing the loss of entropy upon binding and boosting the affinity for its partner.

An ensemble docking calculation of lysozyme and HyHEL-10: Insight into the binding mechanism

Although many computational methods have been proposed for predicting protein–protein complex structures, the prediction remains difficult at the atomic level. In this study, we applied a simple ensemble docking method to the complex of hen egg white lysozyme and its antibody (HyHEL-10). Although this method took into account the protein conformational ensemble, the result was not better than that of a typical rigid docking calculation. In the decomposition analysis, however, we found energetic minima near the crystal structure for a few conformation pairs. This may imply that conformational selection is essential during the early stage of binding.