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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.

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.

Bipolar disorder is a major mental illness characterized by severe swings in mood and activity levels which occur with variable amplitude and frequency. Attempts have been made to identify mood states and biological features associated with mood changes to compensate for current clinical diagnosis, which is mainly based on patients’ subjective reports. Here, we used infradian (a cycle > 24 h) cyclic locomotor activity in a mouse model useful for the study of bipolar disorder as a proxy for mood changes. We show that metabolome patterns in peripheral blood could retrospectively predict the locomotor activity levels. We longitudinally monitored locomotor activity in the home cage, and subsequently collected peripheral blood and performed metabolomic analyses. We then constructed cross-validated linear regression models based on blood metabolome patterns to predict locomotor activity levels of individual mice. Our analysis revealed a significant correlation between actual and predicted activity levels, indicative of successful predictions. Pathway analysis of metabolites used for successful predictions showed enrichment in mitochondria metabolism-related terms, such as “Warburg effect” and “citric acid cycle.” In addition, we found that peripheral blood metabolome patterns predicted expression levels of genes implicated in bipolar disorder in the hippocampus, a brain region responsible for mood regulation, suggesting that the brain–periphery axis is related to mood-change-associated behaviors. Our results may serve as a basis for predicting individual mood states through blood metabolomics in bipolar disorder and other mood disorders and may provide potential insight into systemic metabolic activity in relation to mood changes.

Potential inhibitors of a target biomolecule, NAD-dependent deacetylase Sirtuin 1, were identified by a contest-based approach, in which participants were asked to propose a prioritized list of 400 compounds from a designated compound library containing 2.5 million compounds using in silico methods and scoring. Our aim was to identify target enzyme inhibitors and to benchmark computer-aided drug discovery methods under the same experimental conditions. Collecting compound lists derived from various methods is advantageous for aggregating compounds with structurally diversified properties compared with the use of a single method. The inhibitory action on Sirtuin 1 of approximately half of the proposed compounds was experimentally accessed. Ultimately, seven structurally diverse compounds were identified.

Influenza viruses have developed resistance to current drugs, creating a need for new antiviral targets and new drugs to treat influenza virus infections. In this study, computational and experimental screening of an extensive compound library identified THC19, which was able to suppress influenza virus replication. This compound had no cytotoxic effects and did not disrupt cell cycle progression or induce apoptosis in MDCK cells as confirmed by WST-1 assays, flow cytometry analysis, and caspase-3 assays. Time-of-addition experiments showed that THC19 acts at a relatively early stage of the viral lifecycle. Subsequent mini-genome assays revealed that THC19 inhibited viral genome replication and/or transcription, suggesting that it interferes with one or more of the viral components that form the ribonucleoprotein complexes, namely polymerase basic 2 (PB2), polymerase basic 1 (PB1), polymerase acidic (PA), nucleoprotein (NP) and viral RNA. Finally, mini-genome assays where PB2, PB1, PA or NP from A/WSN/33 (H1N1) virus were replaced with those from A/Udorn/307/1972 (H3N2) virus effectively demonstrated that THC19 inhibited viral multiplication in a manner dependent upon the PA subunit. Taken together, these results suggest that influenza virus PA protein is a potential target for, and may aid the development of, novel compounds that inhibit influenza A virus replication.

SummaryThe prion protein (PrP) resides in lipid rafts in vivo, and lipids modulate misfolding of the protein to infectious isoforms. Here we demonstrate that binding of recombinant PrP to model raft membranes requires the presence of ganglioside GM1. A combination of liquid- and solid-state NMR revealed the binding sites of PrP to the saccharide head group of GM1. The binding epitope for GM1 was mapped to the folded C-terminal domain of PrP, and docking simulations identified key residues in the C-terminal region of helix C and the loop between strand S2 and helix B. Crucially, this region of PrP is linked to prion resistance in vivo, and structural changes caused by lipid binding in this region may explain the requirement for lipids in the generation of infectious prions in vitro.

The generation of T cell receptor (TCR) sequence diversity can produce ‘forbidden’ clones able to recognize self-antigens. Here, the structure of the complex between a myelin basic protein peptide (MBP85–99), human leukocyte antigen (HLA)-DR2 (DRB1*1501/DRA) and TCR-Ob.2F3, the dominant autoimmune clone obtained from a multiple sclerosis (MS) patient, has been determined using structural docking simulation and dynamics in silico and compared to the structure of TCR-Ob.1A12 complexes with the same MHC/peptide determined by X-ray crystallography. The two TCRs differ by three amino acids in the CDR3 α and β loops. As the result different hydrogen bonds are formed between the two CDR3β loops and the peptide in the complexes of the simulated structures, with three hydrogen bonds seen in the TCR-Ob.2F3 complex and five in the TCR-Ob.1A12 complex. The two TCRs, each located near the N-terminal end of the HLA-DR2 binding groove and both had an orthogonal binding axis but they deviated by about 10°. Simulation methods, such as structural docking and molecular dynamics as used here, provide an avenue to understand molecular binding mode efficiently and more rapidly than obtaining multiple crystal structures when a large structural database is already available.

Since the first determination of structure of the HLA-A2 complex, >200 MHC/peptide structures have been recorded, whereas the available T cell receptor (TCR)/peptide/MHC complex structures now are

To construct a new model of the propagation mechanism of infectious scrapie-type prion protein (PrPSc), here we conducted a disruption simulation of a PrPSc nonamer using structure-based molecular dynamics simulation method based on a hypothetical PrPSc model structure. The simulation results showed that the nonamer disrupted in cooperative manners into monomers via two significant intermediate states: (1) a nonamer with a partially unfolded surface trimer and (2) a hexamer and three monomers. Dimers and trimers were rarely observed. Then, we propose a new PrPSc propagation mechanism where a hexamer plays an essential role as a minimum infectious unit.

Prion proteins are key molecules in transmissible spongiform encephalopathies (TSEs), but the precise mechanism of the conversion from the cellular form (PrP C ) to the scrapie form (PrP Sc ) is still unknown. Here we discovered a chemical chaperone to stabilize the PrP C conformation and identified the hot spots to stop the pathogenic conversion. We conducted in silico screening to find compounds that fitted into a “pocket” created by residues undergoing the conformational rearrangements between the native and the sparsely populated high-energy states (PrP*) and that directly bind to those residues. Forty-four selected compounds were tested in a TSE-infected cell culture model, among which one, 2-pyrrolidin-1-yl- N -[4-[4-(2-pyrrolidin-1-yl-acetylamino)-benzyl]-phenyl]-acetamide, termed GN8, efficiently reduced PrP Sc . Subsequently, administration of GN8 was found to prolong the survival of TSE-infected mice. Heteronuclear NMR and computer simulation showed that the specific binding sites are the A-S2 loop (N159) and the region from helix B (V189, T192, and K194) to B-C loop (E196), indicating that the intercalation of these distant regions (hot spots) hampers the pathogenic conversion process. Dynamics-based drug discovery strategy, demonstrated here focusing on the hot spots of PrP C , will open the way to the development of novel anti-prion drugs.

The src SH3 domain has been known to be a two-state folder near room temperature. However, in a previous study with an all-atom model simulation near room temperature, the transition state of this protein was not successfully detected on a free-energy profile using two axes: the radius of gyration (R(g)) and native contact reproduction ratio (Q value). In this study, we focused on an atom packing effect to characterize the transition state and tried another analysis to detect it. To explore the atom packing effect more efficiently, we introduced a charge-neutralized all-atom model, where all of the atoms in the protein and water molecules were treated explicitly, but their partial atomic charges were set to zero. Ten molecular dynamics simulations were performed starting from the native structure at 300 K, where the simulation length of each run was 90 ns, and the protein unfolded in all runs. The integrated trajectories (10 x 90 = 900 ns) were analyzed by a principal component analysis (PCA) and showed a clear free-energy barrier between folded- and unfolded-state conformational clusters in a conformational space generated by PCA. There were segments that largely deformed when the conformation passed through the free-energy barrier. These segments correlated well with the structural core regions characterized by large phi-values, and the atom-packing changes correlated with the conformational deformations. Interestingly, using the same simulation data, no significant barrier was found in a free-energy profile using the R(g) and Q values for the coordinate axes. These results suggest that the atom packing effect may be one of the most important determinants of the transition state.

We investigated whether the squeezed exponential kinetics, which was found in the previous Monte Carlo simulation of a lattice Go model for protein folding, can be observed as well in the molecular dynamics simulation (MD) of an off-lattice Go-like model. It was shown that the squeezed-exponential-type folding kinetics is indeed observed in the off-lattice Go-like model. Then, the effects of the native structure topology, the initial condition of the folding reaction, the employed observable to monitor folding reaction, and the time resolution of the kinetics data, on the observed squeezed exponential kinetics were investigated. The analysis of the time-resolution effect showed that the squeezed exponential kinetics can be attributed to the characteristics of the early stage of folding kinetics, suggesting that the squeezed exponential kinetics is most likely to be observed in experiment which focuses on the early stage of folding kinetics.

The all-atom and the Ising-based models have both played their own roles to help our understanding of helix–coil transition. In this study, we address to what degree these two theoretical models can be consistent with each other in the nonstationary regime, complementing the preceding equilibrium study. We conducted molecular dynamics simulations of an all-atom model polyalanine chain and Monte Carlo simulations of a corresponding kinetic Ising chain. Nonstationary properties of each model were characterized through power spectrum, Allan variance, and autocorrelation analyses regarding the time course of a system order parameter. A clear difference was indicated between the two models: the Ising-based model showed a Lorentzian spectrum in the frequency domain and a single exponential form in the time domain, whereas the all-atom model showed a 1/f spectrum and a stretched exponential form. The observed stretched exponential form is in agreement with a very recent T-jump experiment. The effect of viscous damping on helix–coil dynamics was also studied. A possible source of the observed difference between the two models is discussed by considering the potential energy landscape, and the idea of dynamical disorder was introduced into the original Glauber model in the hope of bridging the gap between the two models. Other possible sources, e.g., the limitations of the Ising framework and the validity of the Markovian dynamics assumption, are also discussed.

Non-exponential relaxation in a simplified lattice model of folding is studied with Monte Carlo (MC) calculation. As folding proceeds, population of the native conformation approaches its equilibrium value with the stretched exponential form. As temperature increases, relaxation becomes less stretched, and for 2 sequences out of 5 tested ones, the relaxation becomes faster than exponential at high temperature. Energy landscape of the model is analyzed and flow of trajectories is followed to explain temperature dependence of kinetics. Measurement of stretched or shrunken kinetics of folding should help to understand nature of intermediates and ruggedness of the landscape.

Schnurri-2 (Shn-2), an nuclear factor-κB site-binding protein, tightly binds to the enhancers of major histocompatibility complex class I genes and inflammatory cytokines, which have been shown to harbor common variant single-nucleotide polymorphisms associated with schizophrenia. Although genes related to immunity are implicated in schizophrenia, there has been no study showing that their mutation or knockout (KO) results in schizophrenia. Here, we show that Shn-2 KO mice have behavioral abnormalities that resemble those of schizophrenics. The mutant brain demonstrated multiple schizophrenia-related phenotypes, including transcriptome/proteome changes similar to those of postmortem schizophrenia patients, decreased parvalbumin and GAD67 levels, increased theta power on electroencephalograms, and a thinner cortex. Dentate gyrus granule cells failed to mature in mutants, a previously proposed endophenotype of schizophrenia. Shn-2 KO mice also exhibited mild chronic inflammation of the brain, as evidenced by increased inflammation markers (including GFAP and NADH/NADPH oxidase p22 phox), and genome-wide gene expression patterns similar to various inflammatory conditions. Chronic administration of anti-inflammatory drugs reduced hippocampal GFAP expression, and reversed deficits in working memory and nest-building behaviors in Shn-2 KO mice. These results suggest that genetically induced changes in immune system can be a predisposing factor in schizophrenia.

Thermal stability of p53 is crucial in preventing cancer proliferation. Critical mutations which significantly destabilize p53 conformation prevent normal interaction between p53 and DNA and consequently interfere with its inhibitory function against cancer proliferation. The purpose of this study was to discover the small compounds called 'chemical chaperons' that can efficiently stabilize the functional p53 conformation and restore the anti-cancer activity. To search for such compounds, we performed a docking simulation using the AutoDock program and the ZINC database. Simply based on the docking energy, we extracted 70 compounds (GJC1-GJC70) and examined their anti-cancer activity using the MTT assay of the human colon cancer cells, HCT116. We found that two compounds, GJC29 and GJC30, significantly inhibited the proliferation of cancer cells compared to the positive control staurosporine. Interaction between p53 and novel anti-cancer compounds were confirmed using SPR measurements. Intriguingly, in the simulated binding mode, both compounds bind to the pocket in the vicinity of the residue V143, one of the mutation hot-spots in p53. Finally, we injected each compound subcutaneously into the nude mice implanted with HCT116 and found that GJC29 has a strong suppressive effect against cancer proliferation in vivo. In conclusion, p53 is an appropriate target for the rational design of the chemical chaperon for cancer treatment.

Transmissible spongiform encephalopathies are associated with the conformational conversion of the prion protein from the cellular form (PrP C ) to the scrapie form. This process could be disrupted by stabilizing the PrP C conformation, using a specific ligand identified as a chemical chaperone. To discover such compounds, we employed an in silico screen that was based on the nuclear magnetic resonance structure of PrP C . In combination, we performed ex vivo screening using the Fukuoka-1 strain-infected neuronal mouse cell line at a compound concentration of 10 μM and surface plasmon resonance. Initially, we selected 590 compounds according to the calculated docked energy and finally discovered 24 efficient antiprion compounds, whose chemical structures are quite diverse. Surface plasmon resonance studies showed that the binding affinities of compounds for PrP C roughly correlated with the compounds' antiprion activities, indicating that the identification of chemical chaperones that bind to the PrP C structure and stabilize it is one efficient strategy for antiprion drug discovery. However, some compounds possessed antiprion activities with low affinities for PrP C , indicating a mechanism involving additional modulation factors. We classified the compounds roughly into five categories: (i) binding and effective, (ii) low binding and effective, (iii) binding and not effective, (iv) low binding and not effective, and (v) acceleration. In conclusion, we found a spectrum of compounds, many of which are able to modulate the pathogenic conversion reaction. The appropriate categorization of these diverse compounds would facilitate antiprion drug discovery and help to elucidate the pathogenic conversion mechanism.

Objective. Elderly people at nursing homes often suffer from malnutrition, which is characterized by a loss of muscle mass and hypoalbuminemia. This malnourished state is closely associated with an impaired activity of daily living (ADL). We analyzed the nutritional state of such elderly individuals longitudinally over 3 years by anthropometry, serum albumin, and muscle and fat volume as estimated by MRI. Patients and Methods. The subjects consisted of 16 elderly women aged 83 ± 7 (mean ± SD) years who resided at a nursing home in an urban area of central Japan. We determined their ADL levels using the Barthel Index (BI) at entry. Seven women belonged to group A (BI; 65-100), thus implying either a mild or no decline in ADL, while the other 9 were in group B (BI; 0-60) and they demonstrated a severe decline in ADL. We measured the following parameters every year from 2000 to 2003; anthropometry including height, body weight, arm circumference (AC), and arm muscle circumference (AMC), thigh muscle and fat volume as estimated by MRI [thigh muscle volume (TMV) and thigh fat volume (TFV)], serum albumin, and plasma amino acid levels by blood biochemistry. The anthropometric values were converted into percentages of the age-and sex-matched reference values for Japanese. Results. In all subjects, the TMV, %AMC, and serum albumin level decreased significantly during the three-year period (p

Patients with chronic liver disease (CLD) often develops glucose intolerance. We explored the prevalence of diabetes mellitus in viral CLD, and analyzed factors profoundly affecting the diabetic angiopathies. 229 CLD patients (124 chronic hepatitis and 105 liver cirrhosis) entered the study. The diagnosis of diabetes was made with the criteria by World Health Organization. Laboratory investigation included serum asparate aminotransferase, alanine aminotransferase, albumin, fasting blood sugar, hemoglobin A1c (HbA1c), fasting immunoreactive insulin, and HOMA-R (FBS*IRI/405). The incidence of macro- and microangiopathy were also examined. Forty (17.5%) CLD patients were diagnosed diabetes, giving a significantly higher incidence than that of general cohort (5.3%) (p

There is a controversy about the major determinants of the folding rate of small single-domain proteins. To shed light on this issue, we examined a possibility that the major determinants may change depending on temperature by conducting molecular dynamics simulations for 17 small single-domain proteins using an off-lattice Go-like model over a wide range of temperature. It was shown that the rank order of the folding rates is temperature dependent, which indicates that the major determinants are dependent on temperature. It was also found that as temperature is decreased, the correlation of the folding rate with the chain length becomes weakened, whereas that with the native topology becomes enhanced. Our simulation results, therefore, may provide a clue to reconcile the apparent controversy between the study by Plaxco et al. based on experimental data and the previous theoretical and subsequent simulation studies: the former showed that the folding rate of two-state folders does not correlate with the chain length but correlates well with the native topology, whereas the latter showed that the folding rate does correlate with the chain length. We propose a possible scenario reconciling the controversy, explaining the reason why the correlation of the folding rate with the chain length became weakened and that with the native topology became enhanced with decreasing temperature.

To make an inquiry into the mechanisms of biomolecular functions, particularly of protein molecule's, we conducted molecular dynamics (MD) simulations of protein molecules using coarse-grained models that preserve 3-dimensional native structure information, together with the hope of inquiring dynamical aspect of design principle of not only molecular machines but also biomolecular computing systems. In this preliminary report, we address to what extent the coarse-grained models, which reduce computational load dramatically, can reproduce collective, large-scale molecular motions essential for molecular functions. Complex structural dynamics were characterized through principal component analysis, and we showed that coarse-grained models can well reproduce collective, large-scale movements that were observed in more precise "all-atom" model simulations. An application of the coarse-grained model to a molecular motor system and a possible role for biomolecular computing will also be discussed.

We previously studied the so-called strange kinetics in the two-dimensional lattice HP model. To further study the strange kinetics, folding processes of a 27-mer cubic lattice protein model with Gō potential were investigated by simulating how the bundle of folding trajectories, consisting of a number of independent Monte Carlo simulations, evolves as the folding reaction proceeds, covering a wide range of temperature. Three realms of folding kinetics were observed depending on temperature. Although at temperatures where folding was two-state-like, the kinetics was conventional single exponential, we found that the time course data were well represented by a squeezed (or "shrunken") exponential function, exp [-(t/tau)beta] with beta > 1, at temperatures lower than the folding temperature, where folding was fastest and of a nonglassy downhill type. The squeezed exponential kinetics was found to pertain to the subdiffusion on the nonglassy downhill free energy surface and presents a marked contrast both to the single exponential kinetics and to the stretched exponential kinetics that was observed at lower temperatures where folding was also downhill but topological frustration came into effect. The observed temperature dependence of the folding kinetics suggests that some small single-domain proteins may follow the squeezed exponential kinetics at about the room temperature.

Recently, the evolutionary robotics (ER) approach has been attracting lots of concern in the fields of robotics and artificial life, since it can automatically synthesize controllers by taking the embodiment and the interaction dynamics between the robot and its environment. However, the ER approach still has serious problems that have to be solved. In this study, we particularly focus on one of the critical problems in the ER: plasticity vs. stability dilemma. In order to alleviate this problem, we investigate the effectiveness of the dynamically-rearranging neural networks by taking a peg-collecting task, which requires appropriate sequence of behavior to accomplish the task, as a practical example.

A simple lattice model of protein folding is studied in order to analyze the kinetic partitioning phenomena in the energy landscape perspective. By restricting the area of conformational space, it becomes possible to follow many Monte Carlo trajectories until they reach equilibrium. Alteration of population of trajectories is monitored and the relations between the energy landscape and kinetics are examined. Kinetic partitioning phenomena are categorized into different types in terms of characteristic time constants and partitioning ratio. In a specific partitioning process, refolding proceeds along the parallel pathways; the time constants have a temperature dependence similar to that observed in hen lysozyme. High-energy conformations are classified into groups according to the probability that the trajectories starting from those conformations will reach each energy valley. The partitioning ratio is determined by the way in which the conformational space is organized into these groups. Proteins 2001;43:280–291. © 2001 Wiley-Liss, Inc.

A continuous-wave probed laser-induced temperature jump system was constructed and applied to monitor the changes in tryptophan fluorescence of the β-lactoglobulin during its folding; the kinetic phases were traced from 300 ns to 10 ms after a temperature jump. Notably, an early phase with typical squeezed-exponential characteristics, [exp{−(kt)β}, β > 1.0], was observed around several tens of microseconds after the temperature jump, which is actually the earliest phase ever observed for β-lactoglobulin. This process can be explained by conformational shift occurring within the unfolded ensemble (U → U′), which is followed by the non-native intermediate (I) formation of this protein.

Background Synaptosomal-associated protein, 25 kDa (SNAP-25) regulates the exocytosis of neurotransmitters. Growing evidence suggests that SNAP-25 is involved in neuropsychiatric disorders, such as schizophrenia, attention-deficit/hyperactivity disorder, and epilepsy. Recently, increases in anxiety-related behaviors and epilepsy have been observed in SNAP-25 knock-in (KI) mice, which have a single amino acid substitution of Ala for Ser187. However, the molecular and cellular mechanisms underlying the abnormalities in this mutant remain unknown. Results In this study, we found that a significant number of dentate gyrus (DG) granule cells was histologically and electrophysiologically similar to immature DG neurons in the dentate gyrus of the adult mutants, a phenomenon termed the “immature DG” (iDG). SNAP-25 KI mice and other mice possessing the iDG phenotype, i.e., alpha-calcium/calmodulin-dependent protein kinase II heterozygous mice, Schnurri-2 knockout mice, and mice treated with the antidepressant fluoxetine, showed similar molecular expression patterns, with over 100 genes similarly altered. A working memory deficit was also identified in mutant mice during a spontaneous forced alternation task using a modified T-maze, a behavioral task known to be dependent on hippocampal function. Chronic treatments with the antiepileptic drug valproate abolished the iDG phenotype and the working memory deficit in mutants. Conclusions These findings suggest that the substitution of Ala for Ser187 in SNAP-25 induces the iDG phenotype, which can also be caused by epilepsy, and led to a severe working memory deficit. In addition, the iDG phenotype in adulthood is likely an endophenotype for at least a part of some common psychiatric disorders.