Quantum Chemical Interaction Analysis between SARS-CoV-2 Main Protease and Ensitrelvir Compared with Its Initial Screening Hit.

A non-covalent oral drug targeting SARS-CoV-2 main protease (Mpro), ensitrelvir (Xocova), has been developed using structure-based drug design (SBDD). To elucidate the factors responsible for enhanced inhibitory activities from an in silico screening hit compound to ensitrelvir, we analyzed the interaction energies of the inhibitors with each residue of Mpro using fragment molecular orbital (FMO) calculations. This analysis reveals that functional group conversion for P1' and P1 parts in the inhibitors increases the strength of existing interactions with Mpro and also provides novel interactions for ensitrelvir; the associated changes in the conformation of Mpro induce further interactions for ensitrelvir in other parts, including hydrogen bonds, a halogen bond, and π-orbital interactions. Thus, we illuminate the promising strategies of SBDD for leading ensitrelvir to get higher activity against Mpro by elucidating microscopic interactions through FMO-based analysis. These detailed mechanism findings, including water cross-linkings, will help to design novel inhibitors in SBDD.

The position of the nitro group affects the mutagenicity of nitroarenes.

The ease with which a nitrated polyaromatic hydrocarbon (NO2PAH) is activated by reductive metabolism is an important factor in determining mutagenicity. However, the mutagenicity of 3-nitrobenzo[a]pyrene (3-NO2BaP) is stronger than that of 1-NO2BaP despite similar reduction properties, and the more potent mutagenicity of 3,6-diNO2BaP relative to that of 1,6-diNO2BaP cannot be explained by relative reducibility. Here, we investigated structural factors leading to the mutagenicity of these compounds by synthesizing 1- and 3-NO2BaP derivatives with C6-position substituents that affect reduction properties and testing the mutagenicity of the compounds and their derivatives against Salmonella typhimurium TA98 and TA98NR. The LUMO and LUMO+1 energies of 6-substituted 3-NO2BaPs were found to correlate with mutagenicity, but such correlations were much weaker with 6-substituted 1-NO2BaPs, indicating that the mutagenicity of 3-NO2BaPs is influenced by the ease of reductive metabolic activation. In silico structural analyses demonstrated that the distances between the nitrogen of the N-acetoxyamino group in reductive metabolites and a DNA alkylation target were longer for 1-NO2BaPs than for 3-NO2BaPs. Therefore, the active metabolites of 6-substituted 3-NO2BaPs intercalate with DNA at a distance where they can readily form adducts with guanine. Conversely, the unfavorable position of intercalated active metabolites of 1-NO2BaPs relative to guanine leads to difficult adduct formation despite the facile formation of the active metabolite due to a low LUMO energy. Therefore, the chemical reducibility of the nitro group and, more importantly, the ease of adduct formation between an active metabolite and DNA are essential for the prediction of the mutagenicity of NO2PAHs.

Dynamic Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method.

By the splendid advance in computation power realized with the Fugaku supercomputer, it has become possible to perform ab initio fragment molecular orbital (FMO) calculations for thousands of dynamic structures of protein-ligand complexes in a parallel way. We thus carried out electron-correlated FMO calculations for a complex of the 3C-like (3CL) main protease (Mpro) of the new coronavirus (SARS-CoV-2) and its inhibitor N3 incorporating the structural fluctuations sampled by classical molecular dynamics (MD) simulation in hydrated conditions. Along with a statistical evaluation of the interfragment interaction energies (IFIEs) between the N3 ligand and the surrounding amino-acid residues for 1000 dynamic structure samples, in this study we applied a novel approach based on principal component analysis (PCA) and singular value decomposition (SVD) to the analysis of IFIE data in order to extract the dynamically cooperative interactions between the ligand and the residues. We found that the relative importance of each residue is modified via the structural fluctuations and that the ligand is bound in the pharmacophore in a dynamic manner through collective interactions formed by multiple residues, thus providing new insight into structure-based drug discovery.

In silico modeling of PAX8-PPARγ fusion protein in thyroid carcinoma: influence of structural perturbation by fusion on ligand-binding affinity.

Paired box 8 (PAX8)-peroxisome proliferator-activated receptor γ (PPARγ) rearrangement is believed to play an important role in tumorigenesis of PAX8-PPARγ fusion protein (PPFP) thyroid carcinomas, while without establishing any standard treatment, including drugs. Although PPFP is a potential promising target for therapeutic agents, the three-dimensional (3D) structure and functions have not yet been experimentally elucidated. In this study, we aimed to construct the 3D structure of PPFP and to aid in the development of therapies that can target PPFP for thyroid carcinomas. The 3D structure of PPFP was constructed by homology modeling based on crystallographic structure data. To validate the modeled structure, we analyzed the thermal fluctuations by molecular dynamics simulations and predicted the physical properties using bioinformatic analyses. We found that the modeled structure was stable under hydrated conditions and had features indicating the actual existence of the structure. Furthermore, the binding free energies of the ligand rosiglitazone with PPARγ and PPFP were evaluated by the molecular mechanics-Poisson-Boltzmann surface area method. We found that rosiglitazone has different binding affinities for the same binding pockets of PPARγ and PPFP, and the optimal compound for PPFP can differ from that of PPARγ. This suggests the need for the development of drugs targeting PPFP that allow for the fusion, rather than focusing on the PPARγ side of PPFP and searching for the best compounds for that pocket. Our findings are expected to lead to the development of new therapies for thyroid tumors.

FMODB: The World's First Database of Quantum Mechanical Calculations for Biomacromolecules Based on the Fragment Molecular Orbital Method.

We developed the world's first web-based public database for the storage, management, and sharing of fragment molecular orbital (FMO) calculation data sets describing the complex interactions between biomacromolecules, named FMO Database (https://drugdesign.riken.jp/FMODB/). Each entry in the database contains relevant background information on how the data was compiled as well as the total energy of each molecular system and interfragment interaction energy (IFIE) and pair interaction energy decomposition analysis (PIEDA) values. Currently, the database contains more than 13 600 FMO calculation data sets, and a comprehensive search function implemented at the front-end. The procedure for selecting target proteins, preprocessing the experimental structures, construction of the database, and details of the database front-end were described. Then, we demonstrated a use of the FMODB by comparing IFIE value distributions of hydrogen bond, ion-pair, and XH/π interactions obtained by FMO method to those by molecular mechanics approach. From the comparison, the statistical analysis of the data provided standard reference values for the three types of interactions that will be useful for determining whether each interaction in a given system is relatively strong or weak compared to the interactions contained within the data in the FMODB. In the final part, we demonstrate the use of the database to examine the contribution of halogen atoms to the binding affinity between human cathepsin L and its inhibitors. We found that the electrostatic term derived by PIEDA greatly correlated with the binding affinities of the halogen containing cathepsin L inhibitors, indicating the importance of QM calculation for quantitative analysis of halogen interactions. Thus, the FMO calculation data in FMODB will be useful for conducting statistical analyses to drug discovery, for conducting molecular recognition studies in structural biology, and for other studies involving quantum mechanics-based interactions.

Molecular recognition of SARS-CoV-2 spike glycoprotein: quantum chemical hot spot and epitope analyses.

Due to the COVID-19 pandemic, researchers have attempted to identify complex structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein (S-protein) with angiotensin-converting enzyme 2 (ACE2) or a blocking antibody. However, the molecular recognition mechanism-critical information for drug and antibody design-has not been fully clarified at the amino acid residue level. Elucidating such a microscopic mechanism in detail requires a more accurate molecular interpretation that includes quantum mechanics to quantitatively evaluate hydrogen bonds, XH/π interactions (X = N, O, and C), and salt bridges. In this study, we applied the fragment molecular orbital (FMO) method to characterize the SARS-CoV-2 S-protein binding interactions with not only ACE2 but also the B38 Fab antibody involved in ACE2-inhibitory binding. By analyzing FMO-based interaction energies along a wide range of binding interfaces carefully, we identified amino acid residues critical for molecular recognition between S-protein and ACE2 or B38 Fab antibody. Importantly, hydrophobic residues that are involved in weak interactions such as CH-O hydrogen bond and XH/π interactions, as well as polar residues that construct conspicuous hydrogen bonds, play important roles in molecular recognition and binding ability. Moreover, through these FMO-based analyses, we also clarified novel hot spots and epitopes that had been overlooked in previous studies by structural and molecular mechanical approaches. Altogether, these hot spots/epitopes identified between S-protein and ACE2/B38 Fab antibody may provide useful information for future antibody design, evaluation of the binding property of the SARS-CoV-2 variants including its N501Y, and small or medium drug design against the SARS-CoV-2.

Fragment Molecular Orbital Based Interaction Analyses on COVID-19 Main Protease - Inhibitor N3 Complex (PDB ID: 6LU7).

The worldwide spread of COVID-19 (new coronavirus found in 2019) is an emergent issue to be tackled. In fact, a great amount of works in various fields have been made in a rather short period. Here, we report a fragment molecular orbital (FMO) based interaction analysis on a complex between the SARS-CoV-2 main protease (Mpro) and its peptide-like inhibitor N3 (PDB ID: 6LU7). The target inhibitor molecule was segmented into five fragments in order to capture site specific interactions with amino acid residues of the protease. The interaction energies were decomposed into several contributions, and then the characteristics of hydrogen bonding and dispersion stabilization were made clear. Furthermore, the hydration effect was incorporated by the Poisson-Boltzmann (PB) scheme. From the present FMO study, His41, His163, His164, and Glu166 were found to be the most important amino acid residues of Mpro in interacting with the inhibitor, mainly due to hydrogen bonding. A guideline for optimizations of the inhibitor molecule was suggested as well based on the FMO analysis.

Taking Water into Account with the Fragment Molecular Orbital Method.

This chapter describes the current status of development of the fragment molecular orbital (FMO) method for analyzing the electronic state and intermolecular interactions of biomolecular systems in solvent. The orbital energies and the inter-fragment interaction energies (IFIEs) for a specific molecular structure can be obtained directly by performing FMO calculations by exposing water molecules and counterions around biomolecular systems. Then, it is necessary to pay attention to the thickness of the water shell surrounding the biomolecules. The single-point calculation for snapshots from MD trajectory does not incorporate the effects of temperature and configurational fluctuation, but the SCIFIE (statistically corrected IFIE) method is proposed as a many-body correlated method that partially compensates for this deficiency. Furthermore, implicit continuous dielectric models have been developed as effective approaches to incorporating the screening effect of the solvent in thermal equilibrium, and we illustrate their usefulness for theoretical evaluation of IFIEs and ligand-binding free energy on the basis of the FMO-PBSA (Poisson-Boltzmann surface area) method and other computational methods.

New SIRT2 inhibitors: Histidine-based bleomycin spin-off.

Bleomycin is considered to exert its antitumor activity via DNA cleavage mediated by activated oxygen generated from the iron complex in its chelator moiety. Spin-offs from this moiety, HPH-1Trt and HPH-2Trt, with anti-cancer activities were recently synthesized. In this paper, we developed inhibitors of nicotinamide adenine dinucleotide-dependent deacetylase isoform 2 of Sirtuin protein (SIRT2), based on HPH-1Trt/HPH-2Trt, and aimed to generate new anti-cancer drugs. HPH-1Trt and HPH-2Trt had in vitro anti-SIRT2 inhibitory activity with 50% inhibitory concentration (IC50) values of 5.5 and 8.8 µM, respectively. A structural portion of HPH-1Trt/HPH-2Trt, a tritylhistidine derivative TH-1, had stronger activity (IC50 = 1.7 µM), and thus, fourteen derivatives of TH-1 were synthesized. Among them, TH-3 had the strongest activity (IC50 = 1.3 µM). Selective binding of TH-3 in the pocket of SIRT2 protein was confirmed with a molecular docking study. Furthermore, TH-3 strongly lowered viability of the breast cancer cell line MCF7 with an IC50 of 0.71 µM. A structure-activity relationship study using cell lines suggested that the mechanism of TH-3 to suppress MCF7 cells involves not only SIRT2 inhibition, but also another function. This compound may be a new candidate anti-cancer drug.

Fragment Molecular Orbital Calculations with Implicit Solvent Based on the Poisson-Boltzmann Equation: II. Protein and Its Ligand-Binding System Studies.

In this study, the electronic properties of bioactive proteins were analyzed using an ab initio fragment molecular orbital (FMO) methodology in solution: coupling with an implicit solvent model based on the Poisson-Boltzmann surface area called as FMO-PBSA. We investigated the solvent effects on practical and heterogeneous targets with uneven exposure to solvents unlike deoxyribonucleic acid analyzed in our recent study. Interfragment interaction energy (IFIE) and its decomposition analyses by FMO-PBSA revealed solvent-screening mechanisms that affect local stability inside ubiquitin protein: the screening suppresses excessiveness in bare charge-charge interactions and enables an intuitive IFIE analysis. The electrostatic character and associated solvation free energy also give consistent results as a whole to previous studies on the explicit solvent model. Moreover, by using the estrogen receptor alpha (ERα) protein bound to ligands, we elucidated the importance of specific interactions that depend on the electric charge and activatability as agonism/antagonism of the ligand while estimating the influences of the implicit solvent on the ligand and helix-12 bindings. The predicted ligand-binding affinities of bioactive compounds to ERα also show a good correlation with their in vitro activities. The FMO-PBSA approach would thus be a promising tool both for biological and pharmaceutical research targeting proteins.

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.

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.

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.

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.

Electron-correlated fragment-molecular-orbital calculations for biomolecular and nano systems.

Recent developments in the fragment molecular orbital (FMO) method for theoretical formulation, implementation, and application to nano and biomolecular systems are reviewed. The FMO method has enabled ab initio quantum-mechanical calculations for large molecular systems such as protein-ligand complexes at a reasonable computational cost in a parallelized way. There have been a wealth of application outcomes from the FMO method in the fields of biochemistry, medicinal chemistry and nanotechnology, in which the electron correlation effects play vital roles. With the aid of the advances in high-performance computing, the FMO method promises larger, faster, and more accurate simulations of biomolecular and related systems, including the descriptions of dynamical behaviors in solvent environments. The current status and future prospects of the FMO scheme are addressed in these contexts.

Three- and four-body corrected fragment molecular orbital calculations with a novel subdividing fragmentation method applicable to structure-based drug design.

We develop an inter-fragment interaction energy (IFIE) analysis based on the three- and four-body corrected fragment molecular orbital (FMO3 and FMO4) method to evaluate the interactions of functional group units in structure-based drug design context. The novel subdividing fragmentation method for a ligand (in units of their functional groups) and amino acid residues (in units of their main and side chains) enables us to understand the ligand-binding mechanism in more detail without sacrificing chemical accuracy of the total energy and IFIEs by using the FMO4 method. We perform FMO4 calculations with the second order Møller-Plesset perturbation theory for an estrogen receptor (ER) and the 17ß-estradiol (EST) complex using the proposed fragmentation method and assess the interaction for each ligand-binding site by the FMO4-IFIE analysis. When the steroidal EST is divided into two functional units including "A ring" and "D ring", respectively, the FMO4-IFIE analysis reveals their binding affinity with surrounding fragments of the amino acid residues; the "A ring" of EST has polarization interaction with the main chain of Thr347 and two hydrogen bonds with the side chains of Glu353 and Arg394; the "D ring" of EST has a hydrogen bond with the side chain of His524. In particular, the CH/π interactions of the "A ring" of EST with the side chains of Leu387 and Phe404 are easily identified in cooperation with the CHPI program. The FMO4-IFIE analysis using our novel subdividing fragmentation method, which provides higher resolution than the conventional IFIE analysis in units of ligand and each amino acid reside in the framework of two-body approximation, is a useful tool for revealing ligand-binding mechanism and would be applicable to rational drug design such as structure-based drug design and fragment-based drug design.

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.