Synthesis and Evaluation of Habiterpenol Analogs.

Habiterpenol is a G2 checkpoint inhibitor isolated from the culture broth of Phytohabitans sp. 3787_5. Here, we report the synthesis of new habiterpenol analogs through the total synthesis process of habiterpenol and evaluating the analogs for G2 checkpoint inhibitory activity. We investigated two different synthetic approaches for total synthesis, with intramolecular conjugate addition and Ti(III)-mediated radical cyclization as key reactions. Although the former was unsuccessful, the latter reaction facilitated stereoselective total synthesis and determination of the absolute configuration of habiterpenol. The extension of these chemistries to a structure-activity relationship (SAR) study gave new habiterpenol analogs, which could not be derived from natural habiterpenol and only be synthesized by applying the total synthesis. Therefore, this study provides important insights into SAR studies of habiterpenol.

Identification of novel EED-EZH2 PPI inhibitors using an in silico fragment mapping method.

Enhancer of zeste homolog 2 (EZH2) is a histone lysine methyltransferase that is overexpressed in many cancers. Numerous EZH2 inhibitors have been developed as anticancer agents, but recent studies have also focused on protein-protein interaction (PPI) between embryonic ectoderm development (EED) and EZH2 as a novel drug discovery target. Because EED indirectly enhances EZH2 enzymatic activity, EED-EZH2 PPI inhibitors suppress the methyltransferase activity and inhibit cancer growth. By contrast to the numerous promising EZH2 inhibitors, there are a paucity of EED-EZH2 PPI inhibitors reported in the literature. Here, we aimed to discover novel EED-EZH2 PPI inhibitors by first identifying possible binders of EED using an in-house knowledge-based in silico fragment mapping method. Next, 3D pharmacophore models were constructed from the arrangement pattern of the potential binders mapped onto the EED surface. In all, 16 compounds were selected by 3D pharmacophore-based virtual screening followed by docking-based virtual screening. In vitro evaluation revealed that five of these compounds exhibited inhibitory activities. This study has provided structural insights into the discovery and the molecular design of novel EED-EZH2 PPI inhibitors using an in silico fragment mapping method.

Structure-based virtual screening for novel chymase inhibitors by in silico fragment mapping.

The term chymase refers to a family of chymotrypsin-like serine proteases stored within the secretory granules of mast cells. Recently, a variety of small molecule inhibitors for chymase have been developed with a primary focus on the treatment of cardiovascular diseases. Despite the expected therapeutic benefit of these chymase inhibitors, they have not been used clinically. Here, we attempted to identify new chymase inhibitors using a multistep structure-based virtual screening protocol combined with our knowledge-based in silico fragment mapping technique. The mapping procedure identified fragments with novel modes of interaction at the oxyanion hole of chymase. Next, we constructed a three-dimensional (3D) pharmacophore model and retrieved eight candidate chymase inhibitors from a commercial database that included approximately five million compounds. This selection was achieved using a multistep virtual screening protocol, which combined a 3D pharmacophore-based search, docking calculations, and analyses of binding free energy. One of the eight compounds exhibited concentration-dependent chymase inhibitory activity, which could be further optimized to develop more potent chymase inhibitors.

[Identifying Inhibitors of USP7-HDM2 Protein-Protein Interaction (PPI) by the in Silico Fragment-mapping Method].

Proteolysis mediated by the ubiquitin-proteome system plays an important role in cancer. Recently, a deubiquitinating enzyme, ubiquitin-specific protease 7 (USP7) has attracted attention as a key regulator of the p53-human double minute 2 (HDM2) pathway in cancer cells. Although some USP7 enzyme inhibitors have been identified, issues related to activity and selectivity prevent their therapeutic application. In this study, we aimed to search for novel USP7-HDM2 protein-protein interaction (PPI) inhibitors that do not affect the USP7 enzyme activity. Using the fragment-mapping program Fsubsite and the canonical subsite-fragment database (CSFDB) developed in our laboratory, we mapped a variety of fragments onto USP7 protein and constructed 3D-pharmacophore models based on the arrangement patterns of the mapped fragments. Finally, we performed 3D pharmacophore-based virtual screening of a commercial compound database and successfully selected promising USP7-HDM2 PPI inhibitor candidates.

Design of a New α-1-C-Alkyl-DAB Derivative Acting as a Pharmacological Chaperone for ß-Glucocerebrosidase Using Ligand Docking and Molecular Dynamics Simulation.

Some point mutations in ß-glucocerebrosidase cause either improper folding or instability of this protein, resulting in Gaucher disease. Pharmacological chaperones bind to the mutant enzyme and stabilize this enzyme; thus, pharmacological chaperone therapy was proposed as a potential treatment for Gaucher disease. The binding affinities of α-1-C-alkyl 1,4-dideoxy-1,4-imino-d-arabinitol (DAB) derivatives, which act as pharmacological chaperones for ß-glucocerebrosidase, abruptly increased upon elongation of their alkyl chain. In this study, the primary causes of such an increase in binding affinity were analyzed using protein⁻ligand docking and molecular dynamics simulations. We found that the activity cliff between α-1-C-heptyl-DAB and α-1-C-octyl-DAB was due to the shape and size of the hydrophobic binding site accommodating the alkyl chains, and that the interaction with this hydrophobic site controlled the binding affinity of the ligands well. Furthermore, based on the aromatic/hydrophobic properties of the binding site, a 7-(tetralin-2-yl)-heptyl-DAB compound was designed and synthesized. This compound had significantly enhanced activity. The design strategy in consideration of aromatic interactions in the hydrophobic pocket was useful for generating effective pharmacological chaperones for the treatment of Gaucher disease.

In silico fragment-mapping method: a new tool for fragment-based/structure-based drug discovery.

Here, we propose an in silico fragment-mapping method as a potential tool for fragment-based/structure-based drug discovery (FBDD/SBDD). For this method, we created a database named Canonical Subsite-Fragment DataBase (CSFDB) and developed a knowledge-based fragment-mapping program, Fsubsite. CSFDB consists of various pairs of subsite-fragments derived from X-ray crystal structures of known protein-ligand complexes. Using three-dimensional similarity-matching between subsites on one protein and another, Fsubsite compares the surface of a target protein with all subsites in CSFDB. When a local topography similar to the subsite is found on the surface, Fsubsite places a fragment combined with the subsite in CSFDB on the target protein. For validation purposes, we applied the method to the apo-structure of cyclin-dependent kinase 2 (CDK2) and identified four compounds containing three mapped fragments that existed in the list of known inhibitors of CDK2. Next, the utility of our fragment-mapping method for fragment-growing was examined on the complex structure of tRNA-guanine transglycosylase with a small ligand. Fsubsite mapped appropriate fragments on the same position as the binding ligand or in the vicinity of the ligand. Finally, a 3D-pharmacophore model was constructed from the fragments mapped on the apo-structure of heat shock protein 90-α (HSP90α). Then, 3D pharmacophore-based virtual screening was carried out using a commercially available compound database. The resultant hit compounds were very similar to a known ligand of HSP90α. As a result of these findings, this in silico fragment-mapping method seems to be a useful tool for computational FBDD and SBDD.

Linear Discriminant Analysis for the in Silico Discovery of Mechanism-Based Reversible Covalent Inhibitors of a Serine Protease: Application of Hydration Thermodynamics Analysis and Semi-empirical Molecular Orbital Calculation.

We recently reported that the Gibbs free energy of hydrolytic water molecules (ΔGwat) in acyl-trypsin intermediates calculated by hydration thermodynamics analysis could be a useful metric for estimating the catalytic rate constants (kcat) of mechanism-based reversible covalent inhibitors. For thorough evaluation, the proposed method was tested with an increased number of covalent ligands that have no corresponding crystal structures. After modeling acyl-trypsin intermediate structures using flexible molecular superposition, ΔGwat values were calculated according to the proposed method. The orbital energies of antibonding π* molecular orbitals (MOs) of carbonyl C=O in covalently modified catalytic serine (Eorb) were also calculated by semi-empirical MO calculations. Then, linear discriminant analysis (LDA) was performed to build a model that can discriminate covalent inhibitor candidates from substrate-like ligands using ΔGwat and Eorb. The model was built using a training set (10 compounds) and then validated by a test set (4 compounds). As a result, the training set and test set ligands were perfectly discriminated by the model. Hydrolysis was slower when (1) the hydrolytic water molecule has lower ΔGwat; (2) the covalent ligand presents higher Eorb (higher reaction barrier). Results also showed that the entropic term of hydrolytic water molecule (-TΔSwat) could be used for estimating kcat and for covalent inhibitor optimization; when the rotational freedom of the hydrolytic water molecule is limited, the chance for favorable interaction with the electrophilic acyl group would also be limited. The method proposed in this study would be useful for screening and optimizing the mechanism-based reversible covalent inhibitors.

Validation of molecular force field parameters for peptides including isomerized amino acids.

Recently, stereoinversions and isomerizations of amino acid residues in the proteins of living beings have been observed. Because isomerized amino acids cause structural changes and denaturation of proteins, isomerizations of amino acid residues are suspected to cause age-related diseases. In this study, AMBER molecular force field parameters were tested by using computationally generated nonapeptides and tripeptides including stereoinverted and/or isomerized amino acid residues. Energy calculations by using density functional theory were also performed for comparison. Although the force field parameters were developed by parameter fitting for l-α-amino acids, the accuracy of the computational results for d-amino acids and ß-amino acids was comparable to those for l-α-amino acids. The conformational energies for tripeptides calculated by using density functional theory were reproduced more accurately than those for nonapeptides calculated by using the molecular mechanical force field. The evaluations were performed for the ff99SB, ff03, ff12SB, and the latest ff14SB force field parameters.

Gibbs Free Energy of Hydrolytic Water Molecule in Acyl-Enzyme Intermediates of a Serine Protease: A Potential Application for Computer-Aided Discovery of Mechanism-Based Reversible Covalent Inhibitors.

In order to predict the potencies of mechanism-based reversible covalent inhibitors, the relationships between calculated Gibbs free energy of hydrolytic water molecule in acyl-trypsin intermediates and experimentally measured catalytic rate constants (kcat) were investigated. After obtaining representative solution structures by molecular dynamics (MD) simulations, hydration thermodynamics analyses using WaterMap™ were conducted. Consequently, we found for the first time that when Gibbs free energy of the hydrolytic water molecule was lower, logarithms of kcat were also lower. The hydrolytic water molecule with favorable Gibbs free energy may hydrolyze acylated serine slowly. Gibbs free energy of hydrolytic water molecule might be a useful descriptor for computer-aided discovery of mechanism-based reversible covalent inhibitors of hydrolytic enzymes.

In silico analyses of the effects of a point mutation and a pharmacological chaperone on the thermal fluctuation of phenylalanine hydroxylase.

Phenylketonuria (PKU) is an inborn error of phenylalanine metabolism due to mutations in phenylalanine hydroxylase (PAH). Recently, small compounds, known as pharmacological chaperones (PhCs), have been identified that restore the enzymatic activity of mutant PAHs. Understanding the mechanism of the reduction in enzymatic activity due to a point mutation in PAH and its restoration by PhC binding is important for the design of more effective PhC drugs. Thermal fluctuations of an enzyme can alter its activity. Here, molecular dynamics simulation show the thermal fluctuation of PAH is increased by introduction of the A313T mutation. Moreover, a simulation using the A313T-PhC complex model was also performed. Thermal fluctuation of the mutant was found to be reduced upon PhC binding, which contributes to restoring its enzymatic activity.

Long chain fatty acids alter the interactive binding of ligands to the two principal drug binding sites of human serum albumin.

A wide variety of drugs bind to human serum albumin (HSA) at its two principal sites, namely site I and site II. A number of reports indicate that drug binding to these two binding sites are not completely independent, and that interactions between ligands of these two discrete sites can play a role. In this study, the effect of the binding of long-chain fatty acids on the interactive binding between dansyl-L-asparagine (DNSA; site I ligand) and ibuprofen (site II ligand) at pH6.5 was examined. Binding experiments showed that the binding of sodium oleate (Ole) to HSA induces conformational changes in the molecule, which, in turn, changes the individual binding of DNSA and ibuprofen, as well as the mode of interaction between these two ligands from a 'competitive-like' allosteric interaction in the case of the defatted HSA conformer to a 'nearly independent' binding in the case of non-defatted HSA conformer. Circular dichroism measurements indicated that ibuprofen and Ole are likely to modify the spatial orientation of DNSA at its binding site. Docking simulations suggest that the long-distance electric repulsion between DNSA and ibuprofen on defatted HSA contributes to a 'competitive-like' allosteric interaction, whereas extending the distance between ligands and/or increasing the flexibility or size of the DNSA binding site in fatted HSA evokes a change in the interaction mode to 'nearly independent' binding. The present findings provide further insights into the structural dynamics of HSA upon the binding of fatty acids, and its effects on drug binding and drug-drug interactions that occur on HSA.

Investigation of substrate recognition for cytochrome P450 1A2 mediated by water molecules using docking and molecular dynamics simulations.

The role of water molecules in the active site of cytochrome P450 1A2 (CYP1A2) was investigated using an explicit water model to simulate biological environments. Moreover, differences in ligand recognition between the inhibitor α-naphthoflavone (ANF) and the substrate 7-ethoxyresorufin (7ER) in the CYP1A2 complex were examined. More than 200-ns molecular dynamics (MD) simulations were performed for each complex structure of CYP1A2. In the complex structure with 7ER obtained after MD simulation, some water molecules existed in the active site and formed hydrogen bonds between 7ER and some residues. However, in the complex structure with ANF, the hydrogen bond network differed. These results suggest that CYP1A2 requires water molecules in its active site for substrate recognition. The observed differences in the hydrogen bond network in the complex with ANF or 7ER may be due to the fact that ANF is an inhibitor.

Precise prediction of activators for the human constitutive androstane receptor using structure-based three-dimensional quantitative structure-activity relationship methods.

The constitutive androstane receptor (CAR, NR1I3) regulates the expression of numerous drug-metabolizing enzymes and transporters. The upregulation of various enzymes, including CYP2B6, by CAR activators is a critical problem leading to clinically severe drug-drug interactions (DDIs). To date, however, few effective computational approaches for identifying CAR activators exist. In this study, we aimed to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) models to predict the CAR activating potency of compounds emerging in the drug-discovery process. Models were constructed using comparative molecular field analysis (CoMFA) based on the molecular alignments of ligands binding to CAR, which were obtained from ensemble ligand-docking using 28 compounds as a training set. The CoMFA model, modified by adding a lipophilic parameter with calculated logD7.4 (S+logD7.4), demonstrated statistically good predictive ability (r2 = 0.99, q2 = 0.74). We also confirmed the excellent predictability of the 3D-QSAR model for CAR activation (r2pred = 0.71) using seven compounds as a test set for external validation. Collectively, our results indicate that the 3D-QSAR model developed in this study provides precise prediction of CAR activating potency and, thus, should be useful for selecting drug candidates with minimized DDI risk related to enzyme-induction in the early drug-discovery stage.

Multi-step virtual screening to develop selective DYRK1A inhibitors.

Developing selective inhibitors for a particular kinase remains a major challenge in kinase-targeted drug discovery. Here we performed a multi-step virtual screening for dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A) inhibitors by focusing on the selectivity for DYRK1A over cyclin-dependent kinase 5 (CDK5). To examine the key factors contributing to the selectivity, we constructed logistic regression models to discriminate between actives and inactives for DYRK1A and CDK5, respectively, using residue-based binding free energies. The residue-based parameters were calculated by molecular mechanics-generalized Born surface area (MM-GBSA) decomposition methods for kinase-ligand complexes modeled by computer ligand docking. Based on the findings from the logistic regression models, we built a three-dimensional (3D) pharmacophore model and chose filter criteria for the multi-step virtual screening. The virtual hit compounds obtained from the screening were assessed for their inhibitory activities against DYRK1A and CDK5 by in vitro assay. Our screening identified two novel selective DYRK1A inhibitors with IC50 values of several µM for DYRK1A and >100µM for CDK5, which can be further optimized to develop more potent selective DYRK1A inhibitors.

Prediction of three-dimensional structures and structural flexibilities of wild-type and mutant cytochrome P450 1A2 using molecular dynamics simulations.

In this study, we investigated the effect of genetic polymorphism on the three-dimensional (3D) conformation of cytochrome P450 1A2 (CYP1A2) using molecular dynamics (MD) simulations. CYP1A2, a major drug-metabolizing enzyme among cytochrome P450 enzymes (CYPs), is known to have many variant alleles. The genetic polymorphism of CYP1A2 may cause individual differences in the pharmacokinetics of medicines. By performing 100ns or longer MD simulations, we investigated the influence of amino acid mutation on the 3D structures and the dynamic properties of proteins. The results show that the static structures were changed by the mutations of amino acid residues, not only near the mutated residues but also in distant portions of the proteins. Moreover, the mutation of only one amino acid was shown to change the structural flexibility of proteins, which may influence the substrate recognition and enzymatic activity. Our results clearly suggest that it is necessary to investigate the dynamic property as well as the static 3D structure for understanding the change of the enzymatic activity of mutant CYP1A2.

Molecular Dynamics Simulations to Investigate the Influences of Amino Acid Mutations on Protein Three-Dimensional Structures of Cytochrome P450 2D6.1, 2, 10, 14A, 51, and 62.

Many natural mutants of the drug metabolizing enzyme cytochrome P450 (CYP) 2D6 have been reported. Because the enzymatic activities of many mutants are different from that of the wild type, the genetic polymorphism of CYP2D6 plays an important role in drug metabolism. In this study, the molecular dynamics simulations of the wild type and mutants of CYP2D6, CYP2D6.1, 2, 10, 14A, 51, and 62 were performed, and the predictions of static and dynamic structures within them were conducted. In the mutant CYP2D6.10, 14A, and 61, dynamic properties of the F-G loop, which is one of the components of the active site access channel of CYP2D6, were different from that of the wild type. The F-G loop acted as the "hatch" of the channel, which was closed in those mutants. The structure of CYP2D6.51 was not converged by the simulation, which indicated that the three-dimensional structure of CYP2D6.51 was largely different from that of the wild type. In addition, the intramolecular interaction network of CYP2D6.10, 14A, and 61 was different from that of the wild type, and it is considered that these structural changes are the reason for the decrease or loss of enzymatic activities. On the other hand, the static and dynamic properties of CYP2D6.2, whose activity was normal, were not considerably different from those of the wild type.

Identification of Novel D-Aspartate Oxidase Inhibitors by in Silico Screening and Their Functional and Structural Characterization in Vitro.

D-Aspartate oxidase (DDO) is a degradative enzyme that is stereospecific for acidic D-amino acids, including D-aspartate, a potential agonist of the N-methyl-D-aspartate (NMDA) receptor. Dysfunction of NMDA receptor-mediated neurotransmission has been implicated in the onset of various mental disorders, such as schizophrenia. Hence, a DDO inhibitor that increases the brain levels of D-aspartate and thereby activates NMDA receptor function is expected to be a useful compound. To search for potent DDO inhibitor(s), a large number of compounds were screened in silico, and several compounds were identified as candidates. They were then characterized and evaluated as novel DDO inhibitors in vitro (e.g., the inhibitor constant value of 5-aminonicotinic acid for human DDO was 3.80 µM). The present results indicate that some of these compounds may serve as lead compounds for the development of a clinically useful DDO inhibitor and as active site probes to elucidate the structure-function relationships of DDO.

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process.

Synthesis of a novel universal opioid receptor agonist with the 1,3,5-trioxazatriquinane skeleton and its pharmacologies.

We designed and synthesized of 1,3,5-trioxazatriquinanes with o- or p-hydroxyphenyl rings as analogs of the κ opioid receptor agonist SYK-146 with m-hydroxyphenyl groups. Although almost all tested compounds did not bind to the opioid receptors, only 17b (SYK-524) with two o-hydroxyphenyl rings showed moderate or potent binding affinities and exhibited agonistic activities for the three opioid receptor types. Because the basicity of the nitrogen atom in the 1,3,5-trioxazatriquinane structure was predicted to be very low due to the electron withdrawing effect of the three oxygen atoms, SYK-524 was a novel non-morphinan and nonpeptidic opioid universal agonist lacking a basic nitrogen atom.

Evaluation of influence of single nucleotide polymorphisms in cytochrome P450 2B6 on substrate recognition using computational docking and molecular dynamics simulation.

In this study, we investigated the influence of single nucleotide polymorphisms on the conformation of mutated cytochrome P450 (CYP) 2B6 proteins using molecular dynamics (MD) simulation. Some of these mutations influence drug metabolism activities, leading to individual variations in drug efficacy and pharmacokinetics. Using computational docking, we predicted the structure of the complex between the antimalarial agent artemether and CYP2B6 whose conformations were obtained by MD simulation. The simulation demonstrated that the entire structure of the protein changes even when a single residue is mutated. Moreover, the structural flexibility is affected by the mutations and it may influence the enzyme activity. The results suggest that some of the inactive mutants cannot recognize artemether due to structural changes caused by the mutation.