Yoshio Okiyama

Prediction of probable mutations in influenza virus hemagglutinin protein based on large-scale ab initio fragment molecular orbital calculations.

Ab initio electronic-state calculations for influenza virus hemagglutinin (HA) trimer complexed with Fab antibody were performed on the basis of the fragment molecular orbital (FMO) method at the second and third-order Møller-Plesset (MP2 and MP3) perturbation levels. For the protein complex containing 2351 residues and 36,160 atoms, the inter-fragment interaction energies (IFIEs) were evaluated to illustrate the effective interactions between all the pairs of amino acid residues. By analyzing the calculated data on the IFIEs, we first discussed the interactions and their fluctuations between multiple domains contained in the trimer complex. Next, by combining the IFIE data between the Fab antibody and each residue in the HA antigen with experimental data on the hemadsorption activity of HA mutants, we proposed a protocol to predict probable mutations in HA. The proposed protocol based on the FMO-MP2.5 calculation can explain the historical facts concerning the actual mutations after the emergence of A/Hong Kong/1/68 influenza virus with subtype H3N2, and thus provides a useful methodology to enumerate those residue sites likely to mutate in the future.

Hydration effects on enzyme–substrate complex of nylon oligomer hydrolase: inter-fragment interaction energy study by the fragment molecular orbital method

Fragment molecular orbital calculations were successfully applied to a nylon oligomer hydrolase, NylB, to investigate the hydration effects on an enzyme–substrate binding structure. Statistically corrected inter-fragment interaction energy analyses were performed on this system to quantitatively characterise the interactions between the substrate, 6-aminohexanoate linear dimer (ALD), and the amino acid residues, such as Asp181, Ser112, and Ile 345, which are regarded as important for enzyme–substrate complex formation by NylB. We found that the direct interaction between ALD and NylB is weakened by hydration, because water molecules cause charge translation or polarisation of ALD or each amino acid residue. However, including the interaction energy between ALD and water molecules greatly stabilises this complex. These results indicate the importance of the hydration effects in enzyme–substrate complex formation.

Hydration of ligands of influenza virus neuraminidase studied by the fragment molecular orbital method.

The fragment molecular orbital (FMO) method was applied to quantum chemical calculations of neuramic acid, the natural substrate of the influenza virus neuraminidase, and two of its competitive inhibitors, Oseltamivir (Tamiful(®)) and Zanamivir (Relenza(®)), to investigate their hydrated structures and energetics. Each of the three ligands was immersed in an explicit water solvent, geometry-optimized by classical MM and QM/MM methods, and subjected to FMO calculations with 2-, 3-, and 4-body corrections under several fragmentation options. The important findings were that QM/MM optimization was preferable to obtain reliable hydrated structures of the ligands, that the 3-body correction was important for quantitative evaluation of the solvation energy, and that the dehydration effect was most remarkable near the hydrophobic sections of the ligands. In addition, the hydration energy calculated by the explicit solvent was compared with the hydration free energy calculated by the implicit solvent via the Poisson-Boltzmann equation, and the two showed a fairly good correlation. These findings will serve as useful information for rapid drug design.

Fragment Molecular Orbital Calculations with Implicit Solvent Based on the Poisson–Boltzmann Equation: Implementation and DNA Study

In this study, an ab initio fragment molecular orbital (FMO) methodology was developed to evaluate the solvent effects on electrostatic interactions, which make a significant contribution to the physical and chemical processes occurring in biological systems. Here, a fully polarizable solute consisting of the FMO electron density was electrostatically coupled with an implicit solvent based on the Poisson-Boltzmann (PB) equation; in addition, the nonpolar contributions empirically obtained from the molecular surface area (SA) were added. Interaction analysis considering solvent-screening and dispersion effects is now available as a powerful tool to determine the local stabilities inside solvated biomolecules. This methodology is applied to a deoxyribonucleic acid (DNA) duplex known as the Dickerson dodecamer. We found that excessively large electrostatic interactions inside the duplex are effectively damped by the screening, and the frontier molecular orbital energies are also successfully lowered. These observations indicate the stability of highly charged DNA duplexes in solution. Moreover, the solvation free energies in the implicit model show fairly good agreement with those in the explicit model while avoiding the costly statistical sampling of the electrolyte distribution. Consequently, our FMO-PBSA approach could yield new insights into biological phenomena and pharmacological problems via this ab initio methodology.

Towards good correlation between fragment molecular orbital interaction energies and experimental IC50 for ligand binding: A case study of p38 MAP kinase

We describe several procedures for the preprocessing of fragment molecular orbital (FMO) calculations on p38 mitogen-activated protein (MAP) kinase and discuss the influence of the procedures on the protein–ligand interaction energies represented by inter-fragment interaction energies (IFIEs). The correlation between the summation of IFIEs for a ligand and amino acid residues of protein (IFIE-sum) and experimental affinity values (IC50) was poor when considered for the whole set of protein–ligand complexes. To improve the correlation for prediction of ligand binding affinity, we carefully classified data set by the ligand charge, the DFG-loop state (DFG-in/out loop), which is characteristic of kinase, and the scaffold of ligand. The correlation between IFIE-sums and the activity values was examined using the classified data set. As a result, it was confirmed that there was a selected data set that showed good correlation between IFIE-sum and activity value by appropriate classification. In addition, we found that the differences in protonation and hydrogen orientation caused by subtle differences in preprocessing led to a relatively large difference in IFIE values. Further, we also examined the effect of structure optimization with different force fields. It was confirmed that the difference in the force field had no significant effect on IFIE-sum. From the viewpoint of drug design using FMO calculations, various investigations on IFIE-sum in this research, such as those regarding several classifications of data set and the different procedures of structural preparation, would be expected to provide useful knowledge for improvement of prediction ability about the ligand binding affinity.

Theoretical Analysis of Activity Cliffs among Benzofuranone-Class Pim1 Inhibitors Using the Fragment Molecular Orbital Method with Molecular Mechanics Poisson–Boltzmann Surface Area (FMO+MM-PBSA) Approach

Significant activity changes due to small structural changes (i.e., activity cliffs) of serine/threonine kinase Pim1 inhibitors were studied theoretically using the fragment molecular orbital method with molecular mechanics Poisson-Boltzmann surface area (FMO+MM-PBSA) approach. This methodology enables quantum-chemical calculations for large biomolecules with solvation. In the course of drug discovery targeting Pim1, six benzofuranone-class inhibitors were found to differ only in the position of the indole-ring nitrogen atom. By comparing the various qualities of complex structures based on X-ray, classical molecular mechanics (MM)-optimized, and quantum/molecular mechanics (QM/MM)-optimized structures, we found that the QM/MM-optimized structures provided the best correlation (R2 = 0.85) between pIC50 and the calculated FMO+MM-PBSA binding energy. Combining the classical solvation energy with the QM binding energy was important to increase the correlation. In addition, decomposition of the interaction energy into various physicochemical components by pair interaction energy decomposition analysis suggested that CH-π and electrostatic interactions mainly caused the activity differences.