Binding Mechanism of Riboswitch to Natural Ligand Elucidated by McMD-Based Dynamic Docking Simulations

Flavin mononucleotide riboswitches are common among many pathogenic bacteria and are therefore considered to be an attractive target for antibiotics development. The riboswitch binds riboflavin (RBF, also known as vitamin B2), and although an experimental structure of their complex has been solved with the ligand bound deep inside the RNA molecule in a seemingly unreachable state, the binding mechanism between these molecules is not yet known. We have therefore used our Multicanonical Molecular Dynamics (McMD)-based dynamic docking protocol to analyze their binding mechanism by simulating the binding process between the riboswitch aptamer domain and the RBF, starting from the apo state of the riboswitch. Here, the refinement stage was crucial to identify the native binding configuration, as several other binding configurations were also found by McMD-based docking simulations. RBF initially binds the interface between P4 and P6 including U61 and G62, which forms a gateway where the ligand lingers until this gateway opens sufficiently to allow the ligand to pass through and slip into the hidden binding site including A48, A49, and A85.

A cutoff-based method with charge-distribution-data driven pair potentials for efficiently estimating electrostatic interactions in molecular systems

We introduce a simple cutoff-based method for precise electrostatic energy calculations in the molecular dynamics (MD) simulations of point-particle systems. Our method employs a theoretically derived smooth pair potential function to define electrostatic energy, offering stability and computational efficiency in MD simulations. Instead of imposing specific physical conditions, such as dielectric environments or charge neutrality, we focus on the relationship represented by a single summation formula of charge-weighted pair potentials. This approach allows an accurate energy approximation for each particle, enabling a straightforward error analysis. The resulting particle-dependent pair potential captures the charge distribution information, making it suitable for heterogeneous systems and ensuring an enhanced accuracy through distant information inclusion. Numerical investigations of the Madelung constants of crystalline systems validate the method's accuracy.

Computer simulation of molecular recognition in biomolecular system: from in silico screening to generalized ensembles

Prediction of ligand-receptor complex structure is important in both the basic science and the industry such as drug discovery. We report various computation molecular docking methods: fundamental in silico (virtual) screening, ensemble docking, enhanced sampling (generalized ensemble) methods, and other methods to improve the accuracy of the complex structure. We explain not only the merits of these methods but also their limits of application and discuss some interaction terms which are not considered in the in silico methods. In silico screening and ensemble docking are useful when one focuses on obtaining the native complex structure (the most thermodynamically stable complex). Generalized ensemble method provides a free-energy landscape, which shows the distribution of the most stable complex structure and semi-stable ones in a conformational space. Also, barriers separating those stable structures are identified. A researcher should select one of the methods according to the research aim and depending on complexity of the molecular system to be studied.

Generalized-ensemble method study: A helix-mimetic compound inhibits protein-protein interaction by long-range and short-range intermolecular interactions

A heterocyclic compound mS-11 is a helix-mimetic designed to inhibit binding of an intrinsic disordered protein neural restrictive silence factor/repressor element 1 silencing factor (NRSF/REST) to a receptor protein mSin3B. We apply a generalized ensemble method, multi-dimensional virtual-system coupled molecular dynamics developed by ourselves recently, to a system consisting of mS-11 and mSin3B, and obtain a thermally equilibrated distribution, which is comprised of the bound and unbound states extensively. The lowest free-energy position of mS-11 coincides with the NRSF/REST position in the experimentally-determined NRSF/REST-mSin3B complex. Importantly, the molecular orientation of mS-11 is ordering in a wide region around mSin3B. The resultant binding scenario is: When mS-11 is distant from the binding site of mSin3B, mS-11 descends the free-energy slope toward the binding site maintaining the molecular orientation to be advantageous for binding. Then, finally a long and flexible hydrophobic sidechain of mS-11 fits into the binding site, which is the lowest-free-energy complex structure inhibiting NRSF/REST binding to mSin3B.

Flexibility and Cell Permeability of Cyclic Ras-Inhibitor Peptides Revealed by the Coupled Nosé-Hoover Equation

Quantifying the cell permeability of cyclic peptides is crucial for their rational drug design. However, the reasons remain unclear why a minor chemical modification, such as the difference between Ras inhibitors cyclorasin 9A5 and 9A54, can substantially change a peptide's permeability. To address this question, we performed enhanced sampling simulations of these two 11-mer peptides using the coupled Nosé-Hoover equation (cNH) we recently developed. The present cNH simulations realized temperature fluctuations over a wide range (240-600 K) in a dynamic manner, allowing structural samplings that were well validated by nuclear Overhauser effect measurements. The derived structural ensembles were comprehensively analyzed by all-atom structural clustering, mapping the derived clusters onto principal components (PCs) that characterize the cyclic structure, and calculating cluster-dependent geometric and chemical properties. The planar-open conformation was dominant in aqueous solvent, owing to inclusion of the Trp side chain in the main-chain ring, while the compact-closed conformation, which favors cell permeation due to its compactness and high polarity, was also accessible. Conformation-dependent cell permeability was observed in one of the derived PCs, demonstrating that decreased cell permeability in 9A54 is due to the high free energy barrier separating the two conformations. The origin of the change in free energy surface was determined to be loss of flexibility in the modified residues 2-3, resulting from the increased bulkiness of their side chains. The derived molecular mechanism of cell permeability highlights the significance of complete structural dynamics surveys for accelerating drug development with cyclic peptides.

Molecular Dynamics Simulation Study on Allosteric Regulation of CD44-Hyaluronan Binding as a Force Sensing Mechanism

CD44 protein exists on surfaces of a variety of human cells, acts as a receptor for the hyaluronan (HA) molecule, and mediates cell adhesion via the HA binding in leukocyte trafficking, cell rolling, and so on. The molecular structures of both CD44 and HA are well known, and the previous work shows that the external-mechanical force induces the partially disordered (PD) conformation from the ordered (O) conformation of CD44. The PD conformation has the higher HA affinity compared to the O conformation. However, the details of force-sensing mechanics have remained unclear. This study provides new insights into allosteric regulation of HA binding by conformational shift from the O to the PD conformation of the CD44 HA binding domain by using the classical molecular dynamics simulations. The O conformation was more favorable than the PD conformation under the equilibrium state, and the O conformation showed weak HA-binding affinity. Our simulation suggests that the PD conformation induced by the external force can refold to a compact structure similar to the O conformation keeping the bound HA. This new conformation showed a higher affinity than the O and PD conformations. Our results show that the unfolding of a remote disordered region from the ligand binding site by the external force allosterically regulates the HA affinity. This study promotes understanding not only the mechanism of CD44-mediated cell rolling but also the allosteric regulation induced by the external mechanical force.

Cryptic-site binding mechanism of medium-sized Bcl-xL inhibiting compounds elucidated by McMD-based dynamic docking simulations

We have performed multicanonical molecular dynamics (McMD) based dynamic docking simulations to study and compare the binding mechanism between two medium-sized inhibitors (ABT-737 and WEHI-539) that bind to the cryptic site of Bcl-xL, by exhaustively sampling the conformational and configurational space. Cryptic sites are binding pockets that are transiently formed in the apo state or are induced upon ligand binding. Bcl-xL, a pro-survival protein involved in cancer progression, is known to have a cryptic site, whereby the shape of the pocket depends on which ligand is bound to it. Starting from the apo-structure, we have performed two independent McMD-based dynamic docking simulations for each ligand, and were able to obtain near-native complex structures in both cases. In addition, we have also studied their interactions along their respective binding pathways by using path sampling simulations, which showed that the ligands form stable binding configurations via predominantly hydrophobic interactions. Although the protein started from the apo state, both ligands modulated the pocket in different ways, shifting the conformational preference of the sub-pockets of Bcl-xL. We demonstrate that McMD-based dynamic docking is a powerful tool that can be effectively used to study binding mechanisms involving a cryptic site, where ligand binding requires a large conformational change in the protein to occur.

GA-guided mD-VcMD: A genetic-algorithm-guided method for multi-dimensional virtual-system coupled molecular dynamics

We introduced a conformational sampling method in an earlier report: The multi-dimensional virtual-system coupled molecular dynamics (mD-VcMD) enhances conformational sampling of a biomolecular system by computer simulations. Herein, new sampling method, a subzone-based mD-VcMD, is presented as an extension of mD-VcMD. Then, the subzone-based method is extended further using a genetic algorithm (GA) named the GA-guided mD-VcMD. In these methods, iterative simulation runs are performed to increase the sampled region gradually. The new methods have the following benefits: (1) They are free from a production run: i.e., all snapshots from all iterations are useful for analyses. (2) They are free from fine tuning of a weight function (probability distribution function or potential of mean force). (3) A canonical ensemble (i.e., a thermally equilibrated ensemble) is generated from a simple procedure. A thermodynamic weight is assigned to each snapshot. (4) Selective sampling can be performed for particularly addressing a poorly sampled region without breaking the proportion of the canonical ensemble if the poorly sampled conformational region emerges in sampling. By applying the methods to a simple system that involves an energy barrier between potential-energy minima, we demonstrated that the new methods have considerably higher sampling efficiency than the original mD-VcMD does.

Asymmetric dynamics of dimeric SARS-CoV-2 and SARS-CoV main proteases in an apo form: Molecular dynamics study on fluctuations of active site, catalytic dyad, and hydration water

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been widely spread around the world. It is necessary to examine the viral proteins that play a notorious role in the invasion of our body. The main protease (3CL^pro) facilitates the maturation of the coronavirus. It is thought that the dimerization of 3CL^pro leads to its catalytic activity; the detailed mechanism has, however, not been suggested. Furthermore, the structural differences between the predecessor SARS-CoV 3CL^pro and SARS-CoV-2 3CL^pro have not been fully understood. Here, we show the structural and dynamical differences between the two main proteases, and demonstrate the relationship between the dimerization and the activity via atomistic molecular dynamics simulations. Simulating monomeric and dimeric 3CL^pro systems for each protease, we show that (i) global dynamics between the two different proteases are not conserved, (ii) the dimerization stabilizes the catalytic dyad and hydration water molecules behind the dyad, and (iii) the substrate-binding site (active site) and hydration water molecules in each protomer fluctuate asymmetrically. We then speculate the roles of hydration water molecules in their catalytic activity.

Structural Fluctuations of Aromatic Residues in an Apo-Form Reveal Cryptic Binding Sites: Implications for Fragment-Based Drug Design

Cryptic sites are binding pockets that are transiently formed in an apo form or that are induced by ligand binding. The investigation of cryptic sites is crucial for drug discovery, since these sites are ubiquitous in disease-related human proteins, and targeting them expands the number of drug targets greatly. However, although many computational studies have attempted to identify cryptic sites, the detection remains challenging. Here, we aimed to characterize and detect cryptic sites in terms of structural fluctuations in an apo form, investigating proteins each of which possesses a cryptic site. From their X-ray structures, we saw that aromatic residues tended to be found in cryptic sites. To examine structural fluctuations of the apo forms, we performed molecular dynamics (MD) simulations, producing probability distributions of the solvent-accessible surface area per aromatic residue. To detect aromatic residues in cryptic sites, we have proposed a "cryptic-site index" based on the distribution, demonstrating the performance via several measures, such as recall and specificity. Besides, we found that high-ranking aromatic residues were likely to probe concaves in a cryptic site. This implies that such fluctuations provide a profile of scaffolds of compounds with the potential to bind to a particular cryptic site.

Molecular Interaction Mechanism of a 14-3-3 Protein with a Phosphorylated Peptide Elucidated by Enhanced Conformational Sampling

Enhanced conformational sampling, a genetic-algorithm-guided multidimensional virtual-system coupled molecular dynamics, can provide equilibrated conformational distributions of a receptor protein and a flexible ligand at room temperature. The distributions provide not only the most stable but also semistable complex structures and propose a ligand-receptor binding process. This method was applied to a system consisting of a receptor protein, 14-3-3ε, and a flexible peptide, phosphorylated myeloid leukemia factor 1 (pMLF1). The results present comprehensive binding pathways of pMLF1 to 14-3-3ε. We identified four thermodynamically stable clusters of MLF1 on the 14-3-3ε surface and free-energy barriers among some clusters. The most stable cluster includes two high-density spots connected by a narrow corridor. When pMLF1 passes the corridor, a salt-bridge relay (switching) related to the phosphorylated residue of pMLF1 occurs. Conformations in one high-density spot are similar to the experimentally determined complex structure. Three-dimensional distributions of residues in the intermolecular interface rationally explain the binding constant changes resulting from the alanine mutation experiment for the residues. We also performed a simulation of nonphosphorylated peptide and 14-3-3ε, which demonstrated that the complex structure was unstable, suggesting that phosphorylation of the peptide is crucially important for binding to 14-3-3ε.

A2B adenosine receptor inhibition by the dihydropyridine calcium channel blocker nifedipine involves colonic fluid secretion

The adenosine A_2B receptor is a critical protein in intestinal water secretion. In the present study, we screened compound libraries to identify inhibitors of the A_2B receptor and evaluated their effect on adenosine-induced intestinal fluid secretion. The screening identified the dihydropyridine calcium antagonists nifedipine and nisoldipine. Their respective affinities for the A_2B receptor (K_i value) were 886 and 1,399 nM. Nifedipine and nisoldipine, but not amlodipine or nitrendipine, inhibited both calcium mobilization and adenosine-induced cAMP accumulation in cell lines. Moreover, adenosine injection into the lumen significantly increased fluid volume in the colonic loop of wild-type mice but not A_2B receptor-deficient mice. PSB-1115, a selective A_2B receptor antagonist, and nifedipine prevented elevated adenosine-stimulated fluid secretion in mice. Our results may provide useful insights into the structure–activity relationship of dihydropyridines for A_2B receptor. As colonic fluid secretion by adenosine seems to rely predominantly on the A_2B receptor, nifedipine could be a therapeutic candidate for diarrhoea-related diseases.

Prediction of Passive Membrane Permeability by Semi-Empirical Method Considering Viscous and Inertial Resistances and Different Rates of Conformational Change and Diffusion

Membrane permeability is an important property of drugs in adsorption. Many prediction methods work well for small molecules, but the prediction of middle-molecule permeability is still difficult. In the present study, we modified a classical permeability model based on Fick's law to study passive membrane permeability. The model consisted of the distribution of solute from water to membrane and the diffusion of solute in each solvent. The diffusion coefficient is the inverse of the resistance, and we examined the inertial resistance in addition to the viscous resistance, the latter of which has been widely used in permeability prediction. Also, we examined three models changing the balance between the diffusion of solute in membrane and the conformational change of solute. The inertial resistance improved the prediction results in addition to the viscous resistance. The models worked well not only for small molecules but also for middle molecules, whose structures have more conformational freedom.

Free-energy landscape of molecular interactions between endothelin 1 and human endothelin type B receptor: fly-casting mechanism

The free-energy landscape of interaction between a medium-sized peptide, endothelin 1 (ET1), and its receptor, human endothelin type B receptor (hETB), was computed using multidimensional virtual-system coupled molecular dynamics, which controls the system's motions by introducing multiple reaction coordinates. The hETB embedded in lipid bilayer was immersed in explicit solvent. All molecules were expressed as all-atom models. The resultant free-energy landscape had five ranges with decreasing ET1-hETB distance: completely dissociative, outside-gate, gate, binding pocket, and genuine-bound ranges. In the completely dissociative range, no ET1-hETB interaction appeared. In the outside-gate range, an ET1-hETB attractive interaction was the fly-casting mechanism. In the gate range, the ET1 orientational variety decreased rapidly. In the binding pocket range, ET1 was in a narrow pathway with a steep free-energy slope. In the genuine-bound range, ET1 was in a stable free-energy basin. A G-protein-coupled receptor (GPCR) might capture its ligand from a distant place.

Chemical modification-mediated optimisation of bronchodilatory activity of mepenzolate, a muscarinic receptor antagonist with anti-inflammatory activity

The treatment for patients with chronic obstructive pulmonary disease (COPD) usually involves a combination of anti-inflammatory and bronchodilatory drugs. We recently found that mepenzolate bromide (1) and its derivative, 3-(2-hydroxy-2, 2-diphenylacetoxy)-1-(3-phenoxypropyl)-1-azoniabicyclo[2.2.2]octane bromide (5), have both anti-inflammatory and bronchodilatory activities. We chemically modified 5 with a view to obtain derivatives with both anti-inflammatory and longer-lasting bronchodilatory activities. Among the synthesized compounds, (R)-(-)-12 ((R)-3-(2-hydroxy-2,2-diphenylacetoxy)-1-(3-phenylpropyl)-1-azoniabicyclo[2.2.2]octane bromide) showed the highest affinity in vitro for the human muscarinic M3 receptor (hM₃R). Compared to 1 and 5, (R)-(-)-12 exhibited longer-lasting bronchodilatory activity and equivalent anti-inflammatory effect in mice. The long-term intratracheal administration of (R)-(-)-12 suppressed porcine pancreatic elastase-induced pulmonary emphysema in mice, whereas the same procedure with a long-acting muscarinic antagonist used clinically (tiotropium bromide) did not. These results suggest that (R)-(-)-12 might be therapeutically beneficial for use with COPD patients given the improved effects seen against both inflammatory pulmonary emphysema and airflow limitation in this animal model.

Prediction of Protein-compound Binding Energies from Known Activity Data: Docking-score-based Method and its Applications

We used protein-compound docking simulations to develop a structure-based quantitative structure-activity relationship (QSAR) model. The prediction model used docking scores as descriptors. The binding free energy was approximated by a weighted average of docking scores for multiple proteins. This approximation was based on a pharmacophore model of receptor pockets and compounds. The weights of the docking scores were restricted to small values to avoid unrealistic weights by a regularization term. Additional outlier elimination improved the results. We applied this method to two groups of targets. The first target was the kinase family. The cross-validation results of 107 kinase proteins showed that the RMSE of predicted binding free energies was 1.1 kcal/mol. The second target was the matrix metalloproteinase (MMP) family, which has been difficult for docking programs. MMPs require metal-binding groups in their inhibitor structures in many cases. A quantum effect contributes to the metal-ligand interaction. Despite this difficulty, the present method worked well for the MMPs. This method showed that the RMSE of predicted binding free energies was 1.1 kcal/mol. In comparison, with the original docking method the RMSE was 1.7 kcal/mol. The results suggest that the present QSAR model should be applied to general target proteins.

Identification of Mepenzolate Derivatives With Long-Acting Bronchodilatory Activity

The standard treatment for chronic obstructive pulmonary disease is a combination of anti-inflammatory drugs and bronchodilators. We recently found that mepenzolate bromide (MP), an antagonist for human muscarinic M3 receptor (hM₃R), has both anti-inflammatory and short-acting bronchodilatory activities. To obtain MP derivatives with longer-lasting bronchodilatory activity, we synthesized hybrid compounds based on MP and two other muscarinic antagonists with long-acting bronchodilatory activity glycopyrronium bromide (GC) and aclidinium bromide (AD). Of these three synthesized hybrid compounds (MP-GC, GC-MP, MP-AD) and MP, MP-AD showed the highest affinity for hM₃R and had the longest lasting bronchodilatory activity, which was equivalent to that of GC and AD. Both MP-GC and MP-AD exhibited an anti-inflammatory effect equivalent to that of MP, whereas, in line with GC and AD, GC-MP did not show this effect. We also confirmed that administration of MP-AD suppressed elastase-induced pulmonary emphysema in a mouse model. These findings provide important information about the structure-activity relationship of MP for both bronchodilatory and anti-inflammatory activities.

Quantitative Structure-activity Relationship (QSAR) Models for Docking Score Correction

In order to improve docking score correction, we developed several structure-based quantitative structure activity relationship (QSAR) models by protein-drug docking simulations and applied these models to public affinity data. The prediction models used descriptor-based regression, and the compound descriptor was a set of docking scores against multiple (∼600) proteins including nontargets. The binding free energy that corresponded to the docking score was approximated by a weighted average of docking scores for multiple proteins, and we tried linear, weighted linear and polynomial regression models considering the compound similarities. In addition, we tried a combination of these regression models for individual data sets such as IC50 , Ki , and %inhibition values. The cross-validation results showed that the weighted linear model was more accurate than the simple linear regression model. Thus, the QSAR approaches based on the affinity data of public databases should improve docking scores.

Variation of free-energy landscape of the p53 C-terminal domain induced by acetylation: Enhanced conformational sampling

The C-terminal domain (CTD) of tumor suppressor protein p53 is an intrinsically disordered region that binds to various partner proteins, where lysine of CTD is acetylated/nonacetylated and histidine neutralized/non-neutralized. Because of the flexibility of the unbound CTD, a free-energy landscape (FEL) is a useful quantity for determining its statistical properties. We conducted enhanced conformational sampling of CTD in the unbound state via virtual system coupled multicanonical molecular dynamics, in which the lysine was acetylated or nonacetylated and histidine was charged or neutralized. The fragments were expressed by an all-atom model and were immersed in an explicit solvent. The acetylation and charge-neutralization varied FEL greatly, which might be convenient to exert a hub property. The acetylation slightly enhanced alpha-helix structures that are more compact than sheet/loop conformations. The charge-neutralization produced hairpins. Additionally, circular dichroism experiments confirmed the computational results. We propose possible binding mechanisms of CTD to partners by investigating FEL. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Visual Interpretation Compared with Caliper and Computerized Measurements in Experimental Vessel Stenosis

To explain visual interpretation errors on angiograms, visual interpretation, caliper measurement, and computerized measurement of cine film were compared using each of 10 graphic models and 10 acrylic models with “stenotic vessels”. Stenosis > 40% was overestimated and stenosis < 40% underestimated by visual interpretation. In caliper measurement, stenosis > 40% at exposure of 90 kV was greatly overestimated by a degree similar to the estimation by visual interpretation, and stenosis > 40% at exposures of 74 kV and 58 kV was slightly overestimated. In computerized measurement, the estimation was consistent with the actual degree of stenosis. Therefore, visual interpretation was not reliable for estimation, and computerized measurement was indispensable for estimation of vessel stenosis. Moreover, we consider the most common cause of error in visual interpretation to be optical illusions.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics

BACKGROUND

Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.

Bongkrekic acid as a selective activator of the peroxisome proliferator-activated receptor γ (PPARγ) isoform

Bongkrekic acid (BKA), an antibiotic isolated from Pseudomonas cocovenans, is an inhibitory molecule of adenine nucleotide translocase. Since this translocase is a core component of the mitochondrial permeability transition pore (MPTP) formed by apoptotic stimuli, BKA has been used as a tool to abrogate apoptosis. However, the other biochemical properties of BKA have not yet been resolved. Although the definition of a fatty acid is a carboxylic acid (-COOH) with a long hydrocarbon chain (tail), when focused on the chemical structure of BKA, the molecule was revealed to be a branched unsaturated tricarboxylic acid that resembled the structure of polyunsaturated fatty acids (PUFAs). Peroxisome proliferator-activated receptors (PPARs) consist of a subfamily of three isoforms: α, β, and γ, the ligands of which include PUFAs. Using completely synthesized BKA together with simplified BKA derivatives (purity: > 98%), we herein demonstrated the utility of BKA as a selective activator of the human PPARγ isoform, which may not be associated with the anti-apoptotic nature of BKA. We also discussed the possible usefulness of BKA.

Structure-Based Development of a Protein-Protein Interaction Inhibitor Targeting Tumor Necrosis Factor Receptor-Associated Factor 6

The interactions between tumor necrosis factor (TNF) receptor-associated factor 6 (TRAF6) and TNF superfamily receptors (TNFRSFs) are promising targets for rheumatoid arthritis (RA) treatment. However, due to the challenging nature of protein-protein interactions (PPIs), a potent inhibitor that surpasses the affinity of the TRAF6-TNFRSF interactions has not been developed. We developed a small-molecule PPI inhibitor of TRAF6-TNFRSF interactions using NMR and in silico techniques. The most potent compound, TRI4, exhibited an affinity higher than those of TNFRSFs and competitively inhibited a TRAF6-TNFRSF interaction. Structural characterization of the TRAF6-TRI4 complex revealed that TRI4 supplants key interactions in the TRAF6-TNFRSF interfaces. In addition, some TRAF6-TRI4 interactions extend beyond the TRAF6-TNFRSF interfaces and increase the binding affinity. Our successful development of TRI4 provides a new opportunity for RA treatment and implications for structure-guided development of PPI inhibitors.

Prediction of synthetic accessibility based on commercially available compound databases

A compound's synthetic accessibility (SA) is an important aspect of drug design, since in some cases computer-designed compounds cannot be synthesized. There have been several reports on SA prediction, most of which have focused on the difficulties of synthetic reactions based on retro-synthesis analyses, reaction databases and the availability of starting materials. We developed a new method of predicting SA using commercially available compound databases and molecular descriptors. SA was estimated from the probability of existence of substructures consisting of the compound in question, the number of symmetry atoms, the graph complexity, and the number of chiral centers of the compound. The probabilities of the existence of given substructures were estimated based on a compound library. The predicted SA results reproduced the expert manual assessments with a Pearson correlation coefficient of 0.56. Since our method required a compound database and not a reaction database, it should be easy to customize the prediction for compound vendors. The correlation between the sales price of approved drugs and the SA values was also examined and found to be weak. The price most likely depends on the total cost of development and other factors.

Synthesis and biological comparison of enantiomers of mepenzolate bromide, a muscarinic receptor antagonist with bronchodilatory and anti-inflammatory activities

Chronic obstructive pulmonary disease (COPD) is characterized by abnormal inflammatory responses and airflow limitations. We recently proposed that the muscarinic antagonist mepenzolate bromide (mepenzolate) would be therapeutically effective against COPD due to its muscarinic receptor-dependent bronchodilatory activity as well as anti-inflammatory properties. Mepenzolate has an asymmetric carbon atom, thus providing us with the opportunity to synthesize both of its enantiomers ((R)- and (S)-mepenzolate) and to examine their biochemical and pharmacological activities. (R)- or (S)-mepenzolate was synthesized by condensation of benzilic acid with (R)- or (S)-alcohol, respectively, followed by quaternization of the tertiary amine. As predicted by computational simulation, a filter-binding assay in vitro revealed that (R)-mepenzolate showed a higher affinity for the muscarinic M3 receptor than (S)-mepenzolate. In vivo, the bronchodilatory activity of (R)-mepenzolate was superior to that of (S)-mepenzolate, whereas anti-inflammatory activity was indistinguishable between the two enantiomers. We confirmed that each mepenzolate maintained its original stereochemistry in the lung when administered intratracheally. These results suggest that (R)-mepenzolate may have superior properties to (S)-mepenzolate as a drug to treat COPD patients given that the former has more potent bronchodilatory activity than the latter.

Molecular Dynamics Simulations Accelerated by GPU for Biological Macromolecules with a Non-Ewald Scheme for Electrostatic Interactions

A molecular dynamics (MD) simulation program for biological macromolecules was implemented with a non-Ewald scheme for long-ranged electrostatic interactions and run on a general purpose graphics processing unit (GPU). We recently developed several non-Ewald methods to compute the electrostatic energies with high precision. In particular, the zero-dipole summation (ZD) method, which takes into account the neutralities of charges and dipoles in a truncated subset, enables the calculation of electrostatic interactions with high accuracy and low computational cost, and its algorithm is simple enough to be implemented in a GPU. We developed an MD program with the space decomposition algorithm, myPresto/psygene, and applied it to several biological macromolecular systems with GPUs implementing the ZD method. Rapid computing performance with high accuracy was obtained.

LigandBox: A database for 3D structures of chemical compounds

A database for the 3D structures of available compounds is essential for the virtual screening by molecular docking. We have developed the LigandBox database (http://ligandbox.protein.osaka-u.ac.jp/ligandbox/) containing four million available compounds, collected from the catalogues of 37 commercial suppliers, and approved drugs and biochemical compounds taken from KEGG_DRUG, KEGG_COMPOUND and PDB databases. Each chemical compound in the database has several 3D conformers with hydrogen atoms and atomic charges, which are ready to be docked into receptors using docking programs. The 3D conformations were generated using our molecular simulation program package, myPresto. Various physical properties, such as aqueous solubility (LogS) and carcinogenicity have also been calculated to characterize the ADME-Tox properties of the compounds. The Web database provides two services for compound searches: a property/chemical ID search and a chemical structure search. The chemical structure search is performed by a descriptor search and a maximum common substructure (MCS) search combination, using our program kcombu. By specifying a query chemical structure, users can find similar compounds among the millions of compounds in the database within a few minutes. Our database is expected to assist a wide range of researchers, in the fields of medical science, chemical biology, and biochemistry, who are seeking to discover active chemical compounds by the virtual screening.

Molecular modeling of vasopressin receptor and in silico screening of V1b receptor antagonists

INTRODUCTION

G protein-coupled receptors (GPCRs) are integral membrane proteins which contain seven-transmembrane-spanning alpha-helices. GPCR-mediated signaling has been associated with various human diseases, positioning GPCRs as attractive targets in the drug discovery field. Recently, through advances in protein engineering and crystallography, the number of resolved GPCR structures has increased dramatically. This growing availability of GPCR structures has greatly accelerated structure-based drug design (SBDD) and in silico screening for GPCR-targeted drug discovery.

AREAS COVERED

The authors introduce the current status of X-ray crystallography of GPCRs and what has been revealed from the resolved crystal structures. They also review the recent advances in SBDD and in silico screening for GPCR-targeted drug discovery and discuss a docking study, using homology modeling, with the discovery of potent antagonists of the vasopressin 1b receptor.

EXPERT OPINION

Several innovative protein engineering techniques and crystallographic methods have greatly accelerated SBDD, not only for already-resolved GPCRs but also for those structures which remain unclear. These technological advances are expected to enable the determination of GPCR-fragment complexes, making it practical to perform fragment-based drug discovery. This paves the way for a new era of GPCR-targeted drug discovery.

Improved estimation of protein-ligand binding free energy by using the ligand-entropy and mobility of water molecules

We previously developed the direct interaction approximation (DIA) method to estimate the protein-ligand binding free energy (DG). The DIA method estimates the DG value based on the direct van der Waals and electrostatic interaction energies between the protein and the ligand. In the current study, the effect of the entropy of the ligand was introduced with protein dynamic properties by molecular dynamics simulations, and the interaction between each residue of the protein and the ligand was also weighted considering the hydration of each residue. The molecular dynamics simulation of the apo target protein gave the hydration effect of each residue, under the assumption that the residues, which strongly bind the water molecules, are important in the protein-ligand binding. These two effects improved the reliability of the DIA method. In fact, the parameters used in the DIA became independent of the target protein. The averaged error of DG estimation was 1.3 kcal/mol and the correlation coefficient between the experimental DG value and the calculated DG value was 0.75.

Integration of ligand-based drug screening with structure-based drug screening by combining maximum volume overlapping score with ligand docking

Ligand-based and structure-based drug screening methods were integrated for in silico drug development by combining the maximum-volume overlap (MVO) method with a protein-compound docking program. The MVO method is used to select reliable docking poses by calculating volume overlaps between the docking pose in question and the known ligand docking pose, if at least a single protein-ligand complex structure is known. In the present study, the compounds in a database were docked onto a target protein that had a known protein-ligand complex structure. The new score is the summation of the docking score and the MVO score, which is the measure of the volume overlap between the docking poses of the compound in question and the known ligand. The compounds were sorted according to the new score. The in silico screening results were improved by comparing the MVO score to the original docking score only. The present method was also applied to some target proteins with known ligands, and the results demonstrated that it worked well.

Statistical estimation of the protein-ligand binding free energy based on direct protein-ligand interaction obtained by molecular dynamics simulation

We have developed a method for estimating protein-ligand binding free energy (DG) based on the direct protein-ligand interaction obtained by a molecular dynamics simulation. Using this method, we estimated the DG value statistically by the average values of the van der Waals and electrostatic interactions between each amino acid of the target protein and the ligand molecule. In addition, we introduced fluctuations in the accessible surface area (ASA) and dihedral angles of the protein-ligand complex system as the entropy terms of the DG estimation. The present method included the fluctuation term of structural change of the protein and the effective dielectric constant. We applied this method to 34 protein-ligand complex structures. As a result, the correlation coefficient between the experimental and calculated DG values was 0.81, and the average error of DG was 1.2 kcal/mol with the use of the fixed parameters. These results were obtained from a 2 nsec molecular dynamics simulation.

The in silico screening and X-ray structure analysis of the inhibitor complex of Plasmodium falciparum orotidine 5'-monophosphate decarboxylase

Orotidine 5'-monophosphate decarboxylase from Plasmodium falciparum (PfOMPDC) catalyses the final step in the de novo synthesis of uridine 5'-monophosphate (UMP) from orotidine 5'-monophosphate (OMP). A defective PfOMPDC enzyme is lethal to the parasite. Novel in silico screening methods were performed to select 14 inhibitors against PfOMPDC, with a high hit rate of 9%. X-ray structure analysis of PfOMPDC in complex with one of the inhibitors, 4-(2-hydroxy-4-methoxyphenyl)-4-oxobutanoic acid, was carried out to at 2.1 Å resolution. The crystal structure revealed that the inhibitor molecule occupied a part of the active site that overlaps with the phosphate-binding region in the OMP- or UMP-bound complexes. Space occupied by the pyrimidine and ribose rings of OMP or UMP was not occupied by this inhibitor. The carboxyl group of the inhibitor caused a dramatic movement of the L1 and L2 loops that play a role in the recognition of the substrate and product molecules. Combining part of the inhibitor molecule with moieties of the pyrimidine and ribose rings of OMP and UMP represents a suitable avenue for further development of anti-malarial drugs.

Crystallization and preliminary X-ray diffraction analysis of mouse prostaglandin F2α synthase, AKR1B3

Aldo-keto reductase 1B3 (AKR1B3) catalyzes the NADPH-dependent reduction of prostaglandin H(2) (PGH(2)), which is a common intermediate of various prostanoids, to form PGF(2α). AKR1B3 also reduces PGH(2) to PGD(2) in the absence of NADPH. AKR1B3 produced in Escherichia coli was crystallized in complex with NADPH by the sitting-drop vapour-diffusion method. The crystal was tetragonal, belonging to space group P4(1)2(1)2 or P4(3)2(1)2, with unit-cell parameters a = b = 107.62, c = 120.76 Å. X-ray diffraction data were collected to 2.4 Å resolution at 100 K using a synchrotron-radiation source.

Selection of in silico drug screening results for G-protein-coupled receptors by using universal active probes

We developed a new protocol for in silico drug screening for G-protein-coupled receptors (GPCRs) using a set of "universal active probes" (UAPs) with an ensemble docking procedure. UAPs are drug-like compounds, which are actual active compounds of a variety of known proteins. The current targets were nine human GPCRs whose three-dimensional (3D) structures are unknown, plus three GPCRs, namely β(2)-adrenergic receptor (ADRB2), A(2A) adenosine receptor (A(2A)), and dopamine D3 receptor (D(3)), whose 3D structures are known. Homology-based models of the GPCRs were constructed based on the crystal structures with careful sequence inspection. After subsequent molecular dynamics (MD) simulation taking into account the explicit lipid membrane molecules with periodic boundary conditions, we obtained multiple model structures of the GPCRs. For each target structure, docking-screening calculations were carried out via the ensemble docking procedure, using both true active compounds of the target proteins and the UAPs with the multiple target screening (MTS) method. Consequently, the multiple model structures showed various screening results with both poor and high hit ratios, the latter of which could be identified as promising for use in in silico screening to find candidate compounds to interact with the proteins. We found that the hit ratio of true active compounds showed a positive correlation to that of the UAPs. Thus, we could retrieve appropriate target structures from the GPCR models by applying the UAPs, even if no active compound is known for the GPCRs. Namely, the screening result that showed a high hit ratio for the UAPs could be used to identify actual hit compounds for the target GPCRs.

Prediction of Positions of Active Compounds Makes It Possible To Increase Activity in Fragment-Based Drug Development

We have developed a computational method that predicts the positions of active compounds, making it possible to increase activity as a fragment evolution strategy. We refer to the positions of these compounds as the active position. When an active fragment compound is found, the following lead generation process is performed, primarily to increase activity. In the current method, to predict the location of the active position, hydrogen atoms are replaced by small side chains, generating virtual compounds. These virtual compounds are docked to a target protein, and the docking scores (affinities) are examined. The hydrogen atom that gives the virtual compound with good affinity should correspond to the active position and it should be replaced to generate a lead compound. This method was found to work well, with the prediction of the active position being 2 times more efficient than random synthesis. In the current study, 15 examples of lead generation were examined. The probability of finding active positions among all hydrogen atoms was 26%, and the current method accurately predicted 60% of the active positions.

Prediction of ligand-binding sites of proteins by molecular docking calculation for a random ligand library

A new approach to predicting the ligand-binding sites of proteins was developed, using protein-ligand docking computation. In this method, many compounds in a random library are docked onto the whole protein surface. We assumed that the true ligand-binding site would exhibit stronger affinity to the compounds in the random library than the other sites, even if the random library did not include the ligand corresponding to the true binding site. We also assumed that the affinity of the true ligand-binding site would be correlated to the docking scores of the compounds in the random library, if the ligand-binding site was correctly predicted. We call this method the molecular-docking binding-site finding (MolSite) method. The MolSite method was applied to 89 known protein-ligand complex structures extracted from the Protein Data Bank, and it predicted the correct binding sites with about 80-99% accuracy, when only the single top-ranked site was adopted. In addition, the average docking score was weakly correlated to the experimental protein-ligand binding free energy, with a correlation coefficient of 0.44.

Catalytic mechanism of the primary human prostaglandin F2α synthase, aldo-keto reductase 1B1--prostaglandin D2 synthase activity in the absence of NADP(H)

Aldo-keto reductase 1B1 and 1B3 (AKR1B1 and AKR1B3) are the primary human and mouse prostaglandin F(2α) (PGF(2α)) synthases, respectively, which catalyze the NADPH-dependent reduction of PGH(2), a common intermediate of various prostanoids, to form PGF(2α). In this study, we found that AKR1B1 and AKR1B3, but not AKR1B7 and AKR1C3, also catalyzed the isomerization of PGH(2) to PGD(2) in the absence of NADPH or NADP(+). Both PGD(2) and PGF(2α) synthase activities of AKR1B1 and AKR1B3 completely disappeared in the presence of NADP(+) or after heat treatment of these enzymes at 100 °C for 5 min. The K(m), V(max), pK and optimum pH values of the PGD(2) synthase activities of AKR1B1 and AKR1B3 were 23 and 18 μM, 151 and 57 nmol·min(-1)·(mg protein)(-1), 7.9 and 7.6, and pH 8.5 for both AKRs, respectively, and those of PGF(2α) synthase activity were 29 and 33 μM, 169 and 240 nmol·min(-1)·(mg protein)(-1), 6.2 and 5.4, and pH 5.5 and pH 5.0, respectively, in the presence of 0.5 mm NADPH. Site-directed mutagenesis of the catalytic tetrad of AKR1B1, composed of Tyr, Lys, His and Asp, revealed that the triad of Asp43, Lys77 and His110, but not Tyr48, acts as a proton donor in most AKR activities, and is crucial for PGD(2) and PGF(2α) synthase activities. These results, together with molecular docking simulation of PGH(2) to the crystallographic structure of AKR1B1, indicate that His110 acts as a base in concert with Asp43 and Lys77 and as an acid to generate PGD(2) and PGF(2α) in the absence of NADPH or NADP(+) and in the presence of NADPH, respectively.

Structural ensemble in computational drug screening

IMPORTANCE OF THE FIELD

Structure-based in silico drug screening is now widely used in drug development projects. Structure-based in silico drug screening is generally performed using a protein-compound docking program and docking scoring function. Many docking programs have been developed over the last 2 decades, but their prediction accuracy remains insufficient.

AREAS COVERED IN THIS REVIEW

This review highlights the recent progress of the post-processing of protein-compound complexes after docking.

WHAT THE READER WILL GAIN

These methods utilize ensembles of docking poses of compounds to improve the prediction accuracy for the ligand-docking pose and screening results. While the individual docking poses are not reliable, the free energy surface or the most probable docking pose can be estimated from the ensemble of docking poses.

TAKE HOME MESSAGE

The protein-compound docking program provides an arbitral rather than a canonical ensemble of docking poses. When the ensemble of docking poses satisfies the canonical ensemble, we can discuss how these post-docking analysis methods work and fail. Thus, improvements to the docking software will be needed in order to generate well-defined ensembles of docking poses.

Cannabidiol-2',6'-dimethyl ether as an effective protector of 15-lipoxygenase-mediated low-density lipoprotein oxidation in vitro

15-Lipoxygenase (15-LOX) is one of the key enzymes responsible for the formation of oxidized low-density lipoprotein (ox-LDL), a major causal factor for atherosclerosis. Both enzymatic (15-LOX) and non-enzymatic (Cu(2+)) mechanisms have been proposed for the production of ox-LDL. We have recently reported that cannabidiol-2',6'-dimethyl ether (CBDD) is a selective and potent inhibitor of 15-LOX-catalyzed linoleic acid oxygenation (Takeda et al., Drug Metab. Dispos., 37, 1733-1737 (2009)). In the LDL, linoleic acid is present as cholesteryl linoleate, the major fatty acid esterified to cholesterol, and is susceptible to oxidative modification by 15-LOX or Cu(2+). In this investigation, we examined the efficacy of CBDD on i) 15-LOX-catalyzed oxygenation of cholesteryl linoleate, and ii) ox-LDL formation catalyzed by 15-LOX versus Cu(2+)-mediated non-enzymatic generation of this important mediator. The results obtained demonstrate that CBDD is a potent and selective inhibitor of ox-LDL formation generated by the 15-LOX pathway. These studies establish CBDD as both an important experimental tool for characterizing 15-LOX-mediated ox-LDL formation, and as a potentially useful therapeutic agent for treatment of atherosclerosis.

Structure determination of a protein assembly by amino acid selective cross-saturation

Amino acid selective cross-saturation (ASCS) method not only provides information about the interface of a protein assembly by the spin relaxation experiment, but also identifies the amino acid residues in the acceptor protein, which are located close to the selectively labeled amino acid residues in the donor protein. Here, a new method was developed to build a precise structural model of a protein assembly, which satisfies the experimental ASCS values, using simulated annealing computation. This method was applied to the ubiquitin-yeast ubiquitin hydrolase 1 (Ub-YUH1) complex to build a precise complex structure compatible with that determined by X-ray crystallography.