The Translation Inhibitor Rocaglamide Targets a Bimolecular Cavity between eIF4A and Polypurine RNA.

A class of translation inhibitors, exemplified by the natural product rocaglamide A (RocA), isolated from Aglaia genus plants, exhibits antitumor activity by clamping eukaryotic translation initiation factor 4A (eIF4A) onto polypurine sequences in mRNAs. This unusual inhibitory mechanism raises the question of how the drug imposes sequence selectivity onto a general translation factor. Here, we determined the crystal structure of the human eIF4A1⋅ATP analog⋅RocA⋅polypurine RNA complex. RocA targets the "bi-molecular cavity" formed characteristically by eIF4A1 and a sharply bent pair of consecutive purines in the RNA. Natural amino acid substitutions found in Aglaia eIF4As changed the cavity shape, leading to RocA resistance. This study provides an example of an RNA-sequence-selective interfacial inhibitor fitting into the space shaped cooperatively by protein and RNA with specific sequences.

FMOe: Preprocessing and Visualizing Package of the Fragment Molecular Orbital Method for Molecular Operating Environment and Its Applications in Covalent Ligand and Metalloprotein Analyses.

The fragment molecular orbital (FMO) method is an efficient quantum chemical calculation technique for large biomolecules, dividing each into smaller fragments and providing interfragment interaction energies (IFIEs) that support our understanding of molecular recognition. The ab initio fragment MO method (ABINIT-MP), an FMO processing program, can automatically divide typical proteins and nucleic acids. In contrast, small molecules such as ligands and heterosystems must be manually divided. Thus, we developed a graphical user interface to easily handle such manual fragmentation as a library for the Molecular Operating Environment (MOE) that preprocesses and visualizes FMO calculations. We demonstrated fragmentation with IFIE analyses for the two following cases: (1) covalent cysteine-ligand bonding inside the SARS-CoV-2 main protease (Mpro) and nirmatrelvir (Paxlovid) complex and (2) the metal coordination inside a zinc-bound cyclic peptide. IFIE analysis successfully identified the key amino acid residues for the molecular recognition of nirmatrelvir with Mpro and the details of their interactions (e.g., hydrogen bonds and CH/π interactions) via ligand fragmentation of functional group units. In metalloproteins, we found an efficient and accurate scheme for the fragmentation of Zn2+ ions with four histidines coordinated to the ion. FMOe simplifies manual fragmentation, allowing users to experiment with various fragmentation patterns and perform in-depth IFIE analysis with high accuracy. In the future, our findings will provide valuable insight into complicated cases, such as ligand fragmentation in modality drug discovery, especially for medium-sized molecules and metalloprotein fragmentation around metals.

Structural basis of transcription regulation by CNC family transcription factor, Nrf2.

Several basic leucine zipper (bZIP) transcription factors have accessory motifs in their DNA-binding domains, such as the CNC motif of CNC family or the EHR motif of small Maf (sMaf) proteins. CNC family proteins heterodimerize with sMaf proteins to recognize CNC-sMaf binding DNA elements (CsMBEs) in competition with sMaf homodimers, but the functional role of the CNC motif remains elusive. In this study, we report the crystal structures of Nrf2/NFE2L2, a CNC family protein regulating anti-stress transcriptional responses, in a complex with MafG and CsMBE. The CNC motif restricts the conformations of crucial Arg residues in the basic region, which form extensive contact with the DNA backbone phosphates. Accordingly, the Nrf2-MafG heterodimer has approximately a 200-fold stronger affinity for CsMBE than canonical bZIP proteins, such as AP-1 proteins. The high DNA affinity of the CNC-sMaf heterodimer may allow it to compete with the sMaf homodimer on target genes without being perturbed by other low-affinity bZIP proteins with similar sequence specificity.

Molecular action of larvicidal flavonoids on ecdysteroidogenic glutathione S-transferase Noppera-bo in Aedes aegypti.

BACKGROUND: Mosquito control is a crucial global issue for protecting the human community from mosquito-borne diseases. There is an urgent need for the development of selective and safe reagents for mosquito control. Flavonoids, a group of chemical substances with variable phenolic structures, such as daidzein, have been suggested as potential mosquito larvicides with less risk to the environment. However, the mode of mosquito larvicidal action of flavonoids has not been elucidated. RESULTS: Here, we report that several flavonoids, including daidzein, inhibit the activity of glutathione S-transferase Noppera-bo (Nobo), an enzyme used for the biosynthesis of the insect steroid hormone ecdysone, in the yellow fever mosquito Aedes aegypti. The crystal structure of the Nobo protein of Ae. aegypti (AeNobo) complexed with the flavonoids and its molecular dynamics simulation revealed that Glu113 forms a hydrogen bond with the flavonoid inhibitors. Consistent with this observation, substitution of Glu113 with Ala drastically reduced the inhibitory activity of the flavonoids against AeNobo. Among the identified flavonoid-type inhibitors, desmethylglycitein (4',6,7-trihydroxyisoflavone) exhibited the highest inhibitory activity in vitro. Moreover, the inhibitory activities of the flavonoids correlated with the larvicidal activity, as desmethylglycitein suppressed Ae. aegypti larval development more efficiently than daidzein. CONCLUSION: Our study demonstrates the mode of action of flavonoids on the Ae. aegypti Nobo protein at the atomic, enzymatic, and organismal levels.

Protein-ligand binding affinity prediction of cyclin-dependent kinase-2 inhibitors by dynamically averaged fragment molecular orbital-based interaction energy.

Fragment molecular orbital (FMO) method is a powerful computational tool for structure-based drug design, in which protein-ligand interactions can be described by the inter-fragment interaction energy (IFIE) and its pair interaction energy decomposition analysis (PIEDA). Here, we introduced a dynamically averaged (DA) FMO-based approach in which molecular dynamics simulations were used to generate multiple protein-ligand complex structures for FMO calculations. To assess this approach, we examined the correlation between the experimental binding free energies and DA-IFIEs of six CDK2 inhibitors whose net charges are zero. The correlation between the experimental binding free energies and snapshot IFIEs for X-ray crystal structures was R2  = 0.75. Using the DA-IFIEs, the correlation significantly improved to 0.99. When an additional CDK2 inhibitor with net charge of -1 was added, the DA FMO-based scheme with the dispersion energies still achieved R2  = 0.99, whereas R2 decreased to 0.32 employing all the energy terms of PIEDA.

Special Features of COVID-19 in the FMODB: Fragment Molecular Orbital Calculations and Interaction Energy Analysis of SARS-CoV-2-Related Proteins.

SARS-CoV-2 is the causative agent of coronavirus (known as COVID-19), the virus causing the current pandemic. There are ongoing research studies to develop effective therapeutics and vaccines against COVID-19 using various methods and many results have been published. The structure-based drug design of SARS-CoV-2-related proteins is promising, however, reliable information regarding the structural and intra- and intermolecular interactions is required. We have conducted studies based on the fragment molecular orbital (FMO) method for calculating the electronic structures of protein complexes and analyzing their quantitative molecular interactions. This enables us to extensively analyze the molecular interactions in residues or functional group units acting inside the protein complexes. Such precise interaction data are available in the FMO database (FMODB) (https://drugdesign.riken.jp/FMODB/). Since April 2020, we have performed several FMO calculations on the structures of SARS-CoV-2-related proteins registered in the Protein Data Bank. We have published the results of 681 structures, including three structural proteins and 11 nonstructural proteins, on the COVID-19 special page (as of June 8, 2021). In this paper, we describe the entire COVID-19 special page of the FMODB and discuss the calculation results for various proteins. These data not only aid the interpretation of experimentally determined structures but also the understanding of protein functions, which is useful for rational drug design for COVID-19.

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.

Structural basis of protein arginine rhamnosylation by glycosyltransferase EarP.

Protein glycosylation regulates many cellular processes. Numerous glycosyltransferases with broad substrate specificities have been structurally characterized. A novel inverting glycosyltransferase, EarP, specifically transfers rhamnose from dTDP-ß-L-rhamnose to Arg32 of bacterial translation elongation factor P (EF-P) to activate its function. Here we report a crystallographic study of Neisseria meningitidis EarP. The EarP structure contains two tandem Rossmann-fold domains, which classifies EarP in glycosyltransferase superfamily B. In contrast to other structurally characterized protein glycosyltransferases, EarP binds the entire ß-sheet structure of EF-P domain I through numerous interactions that specifically recognize its conserved residues. Thus Arg32 is properly located at the active site, and causes structural change in a conserved dTDP-ß-L-rhamnose-binding loop of EarP. Rhamnosylation by EarP should occur via an SN2 reaction, with Asp20 as the general base. The Arg32 binding and accompanying structural change of EarP may induce a change in the rhamnose-ring conformation suitable for the reaction.

High-Precision Atomic Charge Prediction for Protein Systems Using Fragment Molecular Orbital Calculation and Machine Learning.

Here, we have constructed neural network-based models that predict atomic partial charges with high accuracy at low computational cost. The models were trained using high-quality data acquired from quantum mechanics calculations using the fragment molecular orbital method. We have succeeded in obtaining highly accurate atomic partial charges for three representative molecular systems of proteins, including one large biomolecule (approx. 2000 atoms). The novelty of our approach is the ability to take into account the electronic polarization in the system, which is a system-dependent phenomenon, being important in the field of drug design. Our high-precision models are useful for the prediction of atomic partial charges and expected to be widely applicable in structure-based drug designs such as structural optimization, high-speed and high-precision docking, and molecular dynamics calculations.

Characterization of crystal water molecules in a high-affinity inhibitor and hematopoietic prostaglandin D synthase complex by interaction energy studies.

Hematopoietic prostaglandin D synthase (H-PGDS) is one of the two enzymes that catalyze prostaglandin D2 synthesis and a potential therapeutic target of allergic and inflammatory responses. To reveal key molecular interactions between a high-affinity ligand and H-PGDS, we designed and synthesized a potent new inhibitor (KD: 0.14 nM), determined the crystal structure in complex with human H-PGDS, and quantitatively analyzed the ligand-protein interactions by the fragment molecular orbital calculation method. In the cavity, 10 water molecules were identified, and the interaction energy calculation indicated their stable binding to the surface amino acids in the cavity. Among them, 6 water molecules locating from the deep inner cavity to the peripheral part of the cavity contributed directly to the ligand binding by forming hydrogen bonding interactions. Arg12, Gly13, Gln36, Asp96, Trp104, Lys112 and an essential co-factor glutathione also had strong interactions with the ligand. A strong repulsive interaction between Leu199 and the ligand was canceled out by forming a hydrogen bonding network with the adjacent conserved water molecule. Our quantitative studies including crystal water molecules explained that compounds with an elongated backbone structure to fit from the deep inner cavity to the peripheral part of the cavity would have strong affinity to human H-PGDS.

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.

Quantum chemical calculation dataset for representative protein folds by the fragment molecular orbital method.

The function of a biomacromolecule is not only determined by its three-dimensional structure but also by its electronic state. Quantum chemical calculations are promising non-empirical methods available for determining the electronic state of a given structure. In this study, we used the fragment molecular orbital (FMO) method, which applies to biopolymers such as proteins, to provide physicochemical property values on representative structures in the SCOP2 database of protein families, a subset of the Protein Data Bank. Our dataset was constructed by over 5,000 protein structures, including over 200 million inter-fragment interaction energies (IFIEs) and their energy components obtained by pair interaction energy decomposition analysis (PIEDA) using FMO-MP2/6-31 G*. Moreover, three basis sets, 6-31 G*, 6-31 G**, and cc-pVDZ, were used for the FMO calculations of each structure, making it possible to compare the energies obtained with different basis functions for the same fragment pair. The total data size is approximately 6.7 GB. Our dataset will be useful for functional analyses and machine learning based on the physicochemical property values of proteins.

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.

Structure-Activity Relationship and In Silico Evaluation of cis- and trans-PCPA-Derived Inhibitors of LSD1 and LSD2.

trans-2-Phenylcycloproylamine (trans-PCPA) has been used as the scaffold to develop covalent-binding inhibitors against lysine-specific demethylase 1 (LSD1/KDM1A), a therapeutic target for several cancers. However, the effects of different structural moieties on the inhibitory activity, selectivity, and reactivity of these derivatives, including the cis isomers, against LSD1 and its paralogue LSD2/KDM1B are not fully understood. Here we synthesized 65 cis- and trans-PCPA derivatives and evaluated their inhibitory activity against LSD1 and LSD2. One of the derivatives, 7c (cis-4-Br-2,5-F2-PCPA; S1024), inhibited LSD1 and LSD2 with K i values of 0.094 µM and 8.4 µM, respectively, and increased the level of dimethylated histone H3 at K4 in CCRF-CEM cells. A machine learning-based regression model (Q 2 = 0.61) to predict LSD1-inhibitory activity was also constructed and showed a good prediction accuracy (R 2 = 0.81) for 12 test-set compounds, including 7c. The present methodology would be useful when designing covalent-binding inhibitors for other enzymes.

Design and Synthesis of Tranylcypromine-Derived LSD1 Inhibitors with Improved hERG and Microsomal Stability Profiles.

Lysine-specific demethylase 1 (LSD1/KDM1A) is a promising therapeutic target for the treatment of cancers. Several derivatives of tranylcypromine (trans-2-phenylcyclopropylamine) have been developed as LSD1 inhibitors. One such derivative is S2157; however, this compound has a high hERG channel inhibitory activity and a low microsomal stability, making it unsuitable as a drug candidate. Here, using an in silico hERG inhibition prediction model, we designed, synthesized, and evaluated a novel series of S2157 derivatives characterized by modifications of the benzyloxy and piperazine groups. Among the synthesized derivatives, a compound possessing 2-fluoropyridine and 2,8-diaza-spiro[4.5]decane groups (compound 10) showed the most desirable activities, and its eutomer, S1427, was isolated by the optical resolution of 10. In addition to potent LSD1 inhibitory activity, S1427 exhibited desirable hERG channel inhibition and microsomal stability profiles.

An interpretation of positional displacement of the helix12 in nuclear receptors: preexistent swing-up motion triggered by ligand binding.

Positional displacement of helix12 (H12) in the estrogen receptor alpha, which belongs to the nuclear receptor (NR) superfamily, is studied by the molecular dynamics (MD) simulation and the linear response theory. Tendency of the H12 to swing up upon ligand binding, which is consistent with X-ray structures and earlier MD simulations, is reproduced by the calculation of the conformational fluctuation in apo state and the response to the external perturbation. Our study thus provides an interpretation of the positional change of the H12 such that it is derived by the preexistent swing-up motion where the ligand binding works only as a trigger. Our finding, which illustrates underlying mechanism of the H12 motion, would contribute to finding a way to regulate the transcriptional activity by synthesized ligands because the transcriptional activity of the NR is governed by the position of the H12.

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.

Intermolecular Interaction Analyses on SARS-CoV-2 Spike Protein Receptor Binding Domain and Human Angiotensin-Converting Enzyme 2 Receptor-Blocking Antibody/Peptide Using Fragment Molecular Orbital Calculation.

The spike glycoprotein (S-protein) mediates SARS-CoV-2 entry via intermolecular interaction with human angiotensin-converting enzyme 2. The receptor binding domain (RBD) of the S-protein has been considered critical for this interaction and acts as the target of numerous neutralizing antibodies and antiviral peptides. This study used the fragment molecular orbital method to analyze the interactions between the RBD and antibodies/peptides and extracted crucial residues that can be used as epitopes. The interactions evaluated as interfragment interaction energy values between the RBD and 12 antibodies/peptides showed a fairly good correlation with the experimental activity pIC50 (R2 = 0.540). Nine residues (T415, K417, Y421, F456, A475, F486, N487, N501, and Y505) were confirmed as being crucial. Pair interaction energy decomposition analyses showed that hydrogen bonds, electrostatic interactions, and π-orbital interactions are important. Our results provide essential information for understanding SARS-CoV-2-antibody/peptide binding and may play roles in future antibody/antiviral drug design.

Identification of correlated inter-residue interactions in protein complex based on the fragment molecular orbital method.

A theoretical scheme to systematically describe correlated (network-like) interactions between molecular fragments is proposed within the framework of the fragment molecular orbital (FMO) method. The method is mathematically based on the singular value decomposition (SVD) of the inter-fragment interaction energy (IFIE) matrix obtained by the FMO calculation, and can be applied to a comprehensive description of protein-protein interactions in the context of molecular recognition. In the present study we apply the proposed method to a complex of measles virus hemagglutinin and human SLAM receptor, thus finding a usefulness for efficiently eliciting the correlated interactions among the amino-acid residues involved in the two proteins. Additionally, collective interaction networks by amino-acid residues important for mutation experiments can be clearly visualized.

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.