It is possible to create novel synthetic routes for compounds using synthesis route design systems (SRDS) such as TOSP and KOSP. We have been investigating an in silico screening protocol which makes it possible to reduce the number of SRDS experiments in developing new synthesis routes. However, there still remains a problem on how to rank synthesis routes for experiments. Experimental yields are considered to be one of the most important factors in determining which synthesis route is better. If we can predict experimental yields before starting experimental works, it should be very helpful to rank the synthesis routes. The present study describes an attempt towards predicting the trends of experimental yields for organic synthesis by fusing computational chemistry and cheminformatics. A PLS regression was used to correlate experimental yields with the calculated activation energies Ea(calc), together with experimental conditions such as the dielectric constants of the solvents, reaction times, and reaction temperature as explanatory variables. The method was applied to expect experimental yields of two types of reaction, Diels-Alder reaction and Curtius rearrangements.

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In industrial plants, soft sensors are widely used to estimate process variables that are difficult to measure online. Though regression models are reconstructed with new data in order to maintain their high accuracy, some problems remain in practice. Hence, it is attempted to construct soft sensor models based upon the time difference of an objective variable and that of explanatory variables for reducing the effects of deterioration with age such as the drift and gradual changes in the state of plants. However, the time difference model cannot account for the nonlinearity in process variables. Therefore, we have proposed to construct time difference models after modeling nonlinear relationship between and among process variables. Variables obtained by physical models or those calculated by statistical nonlinear regression methods are used to consider the nonlinearity, and then, a time difference model is constructed including these variables. We applied the proposed methods to the actual industrial data obtained during an industrial polymer process. The proposed models achieved high predictive accuracy and eased the bias of the prediction errors for both density and melt flow rate. We confirmed the usefulness of the proposed methods without reconstruction of soft sensor models.

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An azeotrope is a mixture of two or more liquids in such a ratio that its composition cannot be changed by simple distillation. An azeotropic phenomenon is a critical problem in the design of distillation processes. It is important to investigate azeotropes before designing a chemical process. In this study, we proposed a method to construct prediction model for azeotropes through a statistical learning of molecular descriptors and azeotropic data. Using this method,azeotropic properties are calculated very quickly without experimental data. Two statistical models were constructed, 1: predict the presence of an azeotropic point of any binary solution. 2: predict azeotropic composition of binary solution. Compared with the UNIFAC, the constructed models are proved to have comparable predictive accuracy and higher general applicability.

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Two bond distance 13C-1H Spin-Spin coupling constants, which obtained from the NMR analysis, strongly depend on the rotational isomerism of adjacent hydroxyl groups attached to hexapyraosyl ring, so it can be expected to elucidate hydrogen bonding network structure in chemical and biochemical environment and its change concerned with the sugar residue around active site in a protein. In this study, we have performed thorough conformational analysis about several unique conformers of alpha-galactose to identify predominant conformations in aqueous solution. As the result, some conformers which comparatively reproduced the experimental 2JCH values of alpha-galactose were found. However, these conformers were not predominance in evaluation of their distributions based on the Bolzmann law using conformational energies of ab initio calculation with PCM and SMD solvation models. Therefore, we have reminded the difficulty of the prediction of suger conformations in aqueous solution including the direction of the hydroxyl groups, even if using high-level ab initio calculation. The latest result of higher-level calculation suggests that application of IPCM model may give a good prediction for the NMR/2JCH values in comparison with the experimental but unstable convergence of SCF calculation simultaneously. We are now continuously trying to eliminate the causative factor.

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The mechanism of coloration of polyimides has been investigated theoretically and experimentally. Since light is considered to be absorbed by polyimides via the charge transfer excitation, we used the long-range-corrected time-dependent density functional theory recently developed by Tsuneda et al [J. Chem. Phys. 2004, 120, 8425] for the calculation of excitation energies and oscillator strengthes. Classical molecular dynamics simulations for packed chain models of polyimides were also performed to analyze the structural information of polyimides in condensed phase. In order to predict the transparency of polyimides film, we developed the theoretical method by combining the result of electronic structure calculation and that of molecular dynamics simulation. We compared our theoretical results with experimental ones and discussed the difference between them. As a result, we could clarify the new mechanism of coloration and obtain the reasonable results for the theoretical UV-visible spectra.

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We are doing research which harmless processes PCB(polychlorinated bihenyls) in transformer insulation oil a transformer with Pd metal catalyst. In it, processing equipment heats by irradiating 2.45GHz microwave. Then, mechanism analysis of the microwave effect in PCB processing is performed with quantum chemistry calculationsoft MOPAC and Gaussian03. Mechanism analysis of the heating effect of microwave is perfomed first. Consequently, the heating effect of solution is elucidated that the rotation mode of a PCB monomer, an insulating oil monomer, and dimer of isopropyl alcohol absorbs and heats owing to microwave. Moreover, the heating effect of Pd metal catalyst is elucidated that the vibrating mode of the graphite crystal which is the crystal portion of the activated carbon of a carrier absorbs and heats owing to microwave.

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In recent years, precision agriculture has been widely applied to farming practices in order to improve their productivity, and to reduce their environmental impacts. One of the important challenges in the precision agriculture is to determine the soil properties of an agricultural field accurately, and yet rapidly. Such evaluation is essential to executing well-timed, appropriate actions, which could improve farming efficiency. To this end, we have developed statistical models that are capable of predicting soil properties of a field, such as moisture, nitrogen, or carbon contents. These models are constructed from visible/near-infrared spectra data obtained by a real-time soil spectrometer. In this presentation we discuss a few approaches and methods to improve the predictive power of such models. Support vector regression (SVR) method allows us to obtain reasonably predictive models without explicit variable selection or wavelength selection models. Ensemble learning procedure could significantly improve the predictivity of partial least square (PLS) models. Furthermore the applicability domain of a model can be estimated through application of bootstrap technique in calculation of standard deviation of each predicted values.

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Consumers are more conscious of food quality because of recent terrible matters such as falsifying meat label or food poisoning by pesticide residue, while food factories are eager to check the quality of products quickly for good efficiency. However, in case of fruit, it is difficult to estimate its quality since it is so greatly influenced by inside conditions that it cannot be judged by appearance. In addition, many fruits are gathered into factories. In order to solve these problems, sorting machines with Near-Infrared spectroscopy become spread. But their predictive power is still low and it takes much time for measuring. We have chosen apple as a fruit, which is considered to be difficult for predicting inside quality. We constructed a regression model to predict sugar content by using Genetic Algorithm based Wavelength Selection (GAWLS) and classification models to diagnose water core and brown core by combining GAWLS with k-NN(k-nearest neighbor), based on Mahalanobis distance. Mahalanobis distance was expected to detect outlier samples and to increase predictive accuracy by reflecting similarity among spectra. Consequently, all proposed methods can extract wavelengths which are likely to be associated with each quality and achieve higher predictive accuracy.

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CH-NMR-NP is a C-13 and H-1 NMR database of organic natural products compiled from published papers. The building began in May, 2002. The present data are mainly compiled from papers in the important nine research journals issued mainly from 2000. The database is updated every half a year. The present total number of the data is 20,426 and 19,500 data were compiled from published research papers at August 2010. The DB includes the MF, MW, Name, Origin of the compound, Chemical structure with spectral assignment, Solvent, C-13 and H-H chemical shifts, H-1 splitting information, Reference and others. The DB can search by Atom numbers, MF, MW, Name, H-1 and C-13 shifts. The display of the C-13 spectrum made from the C-13 shift data is possible. The DB is available through http://www.las.jp.

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MART (Multiple Additive Regression Trees) is known as a tree type model for the classification and the regression. This is a kind of boosting, and it is well known that an individual tree is weak learner. Moreover, the paradox, " blazingly fast although it is ultra slow learning " consists. Therefore, the idea of this MART was applied to the study of the chemistry. Concretely, mind mapping and panorama was used for making illustration for the text of chemistry. When animation that used this illustration was used in the class of chemistry, the student's reaction was excellent. A great improvement was able to be achieved by the item with low evaluation point. It is guessed that tudents kept concentrating to the contents by watching the arranged animation and an individual content was comprehensible to them.

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Correlation diagrams of stereoisograms are proposed to discuss stereoisomerism of cyclobutane derivatives. An RS-stereoisomeric group for characterizing a cyclobutane skeleton is defined by starting from the point group D4h so that the global symmetry of each cyclobutane derivative is characterized to be its subgroup. Then, the corresponding stereoisogram is drawn. A tetrahedral promolecule for characterizing the local symmetry at each RS-stereogenic center is derived to belong to a subgroup of an RS-stereoisomeric group due to the point group Td. Then, the corresponding stereoisogram is drawn. Relationships between these stereoisograms are discussed by constructing the correlation diagram of stereoisograms.

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The interaction of small organic molecules with chrysotile asbestos surface, Si2Mg3O5(OH)4, was investigated by means of ab initio molecular orbital method, to reveal the specific property of molecular adsorptions on the inorganic surface. We used three kinds of chrysotile models; (i) periodic boundary conditions (PBC) system model, i.e., infinite repeat of Si2Mg3O5(OH)4, (ii) cluster model, i.e., part of PBC model, and (iii) brucite model, i.e., infinite repeat of Mg(OH)2. The geometry optimization for each model was performed by DFT and HF methods with 6-31G(d) basis set. The obtained structural parameters for PBC and cluster models compare well with the experimental data. We estimated the molecular adsorption energies by using the cluster model and small molecules, such as H2O, CH3OH and CH3NH2. We found that the interaction of those molecules with the inorganic surface (with OH group) was equivalent to organic hydrogen bonding: the interaction energy was about 6 kcal/mol for each. It is noteworthy that the electronegative atoms of adsorbing molecules are attractive above OH groups on the surface, while electropositive atoms of adsorbing molecules are attractive above the cavity between positive OH groups. As a result, electropositive as well as electronegative molecules adsorb on chrysotile by electrostatic interaction.

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Solid-state luminescence of organic compounds attracts much attention from the vewpoint organic emission device applications. Hydroxyphenylimidazopyridines(HPIP) shows tunable florescent properties in protic/aprotic solutions as well as in solid state, in which Excited State Intramolecular Protom Transfer (ESIPT) plays a significant role as seen for some organic compound bearing intramolecular hydrogen bonds. The detailed emission mechanism of the ESIPT-driven fluorescence turning machanism, however, still remains unclear. This study aims to explore the several low-lying excited state potential energy surfaces and conical intersections/seams in order to elucidate the machanism of HPIP, by means of semi-quantitative (TDDFT) and quantitative (MS-CASPT2) computations.

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This research consists of 2 subjects. The first is the development of SAR prediction system. New notation has been introduced to linear fragments, such as branching and variable chain length. Descriptor selection step uses Relief algorithm from a group of correlated fragments. Prediction model is based on the cascade model. A few rules have been selected based on the rule priority definition. No prediction has been done when no rules are applicable to a compound. Results are judged by AUC of ROC. Application to rodent carcinogenicity prediction showed better AUC than those given by Naive Bayes and Random Forests methods. The second part reveals the development of prediction system on KNIME environment. We have converted the above prediction system onto KNIME. The visual workflow has enabled easy understanding of the system. We could substitute a program to a KNIME node, and a python code has been implemented by a KNIME Jython node. The resulting system has given us a flexible SAR prediction environment and we can easily compare prediction results by a variety of methods.

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A sugar chain is composed of monosaccharide(s) such as glucose containing some chiral carbons. Without considering the stereochemistry of mannose, galactose or glucose, the chemical structures cannot be distinguished. The types of monosaccharide will vary when it include amido, amino and/or carboxyl groups in its chemical structure. Moreover, if a sugar chain includes similar chemical structure(s), the recognition of monosaccharide may not be easy. Besides, in the case of converting a two-dimensional chemical structure drawing into a chair conformer, the recognition of the monosaccharide becomes even more difficult. In this study, we have developed the monosaccharide recognition system which recognizes D-L notation, conformational isomer, 2D projection mode, in addition to the kind of monosaccharide, the anomeric configuration derived from 2D chemical structure expressed in chair type conformation. This system can recognize monosaccharide in most cases. However; the algorithm of this system cannot recognize some exceptional rotational structure of monosaccharide.

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In the fields of life sciences such as drug development, halting development of drug increases because of onset of toxicity recently. Therefore, rough toxicity prediction by using quantitative structure-activity relationship for ordered categorical data becomes more important. However we find difficulty in accurately analyzing ordered categorical data with existing methods because they treat their objective parameters as nominal instead of ordered. There are two analyses for ordered categorization: logistic regression analysis (LRA) and regression discriminant analysis (RDA). The RDA method has the following advantages over the liner discriminant analysis (LDA). 1) It provides important information in selecting explanatory variables. 2) It returns results more quickly. The RDA method, however, is not frequently utilized because of two weak points. In previous study, we refined the RDA method and developed the Evolved RDA method (ERDA). In this study, we tried to develop model supporting accuracy and generalization capability at the same time by using the ERDA method combined ensemble learning for ordered categorical data.

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Federation of Asian Chemical Societies (FACS) opens a chemical information portal site, ChIN (chemical information network) that is running as one of the FACS official projects. The ChIN is a web-based guide for chemical resources on Internet. Initially, the ChIN serviced in English and Chinese. We started a Japanese portal for domestic user in Japan 2008. Now we have implemented a subportal of the Japanese portal offering domestic resource of chemical database in Japan. It facilitates searching for the database resource and displaying the relevant information. The paper describes the state of art of the system.

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Despite poly(ethylene teraphthalate) (PET) has become one of the most important thermoplastics, the mechanism of the PET polycondensation reaction is poorly understood. In this work, we carried out a theoretical study on Diethylteraphthalate model molecule and Sb(OEt)3, Ge(OEt)4 and Ti(OEt)4 model catalysts by using the B3LYP level of theory, in order to investigate the mechanism of catalysis in the PET polycondensation reaction. We found that the metal center of metal alkoxides coodinates to the carbonyl oxygen atom of the ester, and the alkoxy oxygen atom of alkoxy ligands of attacks to the carbonyl carbon atom of the ester to form the four-centered transition satete. The activation energy for tetraethoxy titanium catalized reaction in vacuo is 15.47 kcal/mol; this is comparable to the experimental result of 11.2 kcal/mol for poly(buthylene teraphthalate)/Ti(OBu)4. Because other mechanism gave much higher activation energies, this is the most convincing mechanism of PET polycondensation catalysis by antimony, germanium and titanium alkoxides.

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In order to evaluate changes in the hydrogen-bond effects from the singlet state to the triplet state on aromaticity of the pi-conjugated system involving intramolecular so-called resonance-assisted hydrogen bonds DFT and MP2 calculations were carried out on 2-hydroxycyclohexa-2,5-dienones fused with m-membered (m=3,5,7) pi-conjugated rings. The m-dependence of the aromaticity indices, HOMA derived from the bond alternation and NICS(1) on the basis of the NMR chemical shifts, for the m-membered rings inverted from the singlet state to the triplet state. Especially the character of the 5-membered ring was anti-aromatic in the singlet state, but became aromatic in the triplet state. The (anti)-aromatic characters were enhanced with the presence of the hydrogen bonds, particularly in the transition state for the proton transfer along the hydrogen bonds. The potential energy curve for the proton transfer of the compound with the 5-membered ring in the singlet state crossed that in the triplet state, suggesting the existence of the low-energy path for the proton transfer.

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Although almost all kinds of drugs carry a certain level of risk of side-effects, because of the Japanese strict approval process, serious adverse reactions are rarely developed. However, especially when such serious and rare adverse reactions are developed, they tend to be late to be diagnosed as their side-effects. The Ministry of Health, Labor and Welfare made a manual of the serious adverse reaction since 2006. The ministry also has been prompting the research on the pathogenesis of such significant adverse reactions.After reporting Stevens-Johnson syndrome (SJS) by the two American pediatricians, A. M. Stevens and F. C. Johnson in 1922, the differences among SJS, erythema multiform (EM) and toxic epidermal necrosis (TEN) have been discussed. However, still, little chemical information, which can reveal the drugs developing SJS more often than erythema multiform (EM), is known. In this study, we aimed to find several partial structures as well as molecular properties which develop SJS more often than EM using logistic regression analysis with various kinds of molecular chemical descriptors. As the result, fairy good correct classification ratios were obtained and the numbers of quaternary carbon atoms was constantly remained as a significant descriptor of the discrimination analysis.

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The rotational symmetry boundary condition (RSBC) is a method to accelerate simulation of rotationally symmetric protein assembly. The RSBC has been applied to calculation of icosahedral virus capsids to investigate virus infection. Because an icosahedral capsid is composed of 60 identical asymmetric units, the unit has been adopted for computational cell of RSBC and the simulations have been accelerated by at least 60 times. However, it is not possible to include motion of ions or asymmetric deformation of protein around the 5fold axis in the present RSBC program. Therefore, use of a pentamer composed of 5 asymmetric units for compuational cell is expected to allow analysis on asymmetric properties around the 5fold axis. We reports further development of program of RSBC and details of related mathematical basis for use of pentamer computational cells.

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Large-scale density functional (DF) calculations were made possible by both high-performance computers and an efficient quantum chemical calculation algorithm. The exchange correlation (XC) term in the DF calculation is generally estimated by numerical integral scheme, and the accuracy and computational complexity depends on the combination of the various methods. Even though the accurate scheme is proposed for small molecules, the effectiveness is not verified enough for large-scale molecules. For the analysis of molecular properties such as chemical reaction, vibration spectrum, and so on, the integral scheme is demanded on 0.01~0.1 kcal/mol accuracy. The larger the molecule size is, the more the number of significant figures may be needed. In addition, not only the accuracy but also the feasibility is important for large-scale calculations. It is necessary to evaluate the balance of the accuracy and the computational complexity. In this study, we carried out large-scale DF calculations by using various numerical integral methods to estimate XC term and investigated these schemes and the feasibility.

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We have developed a system that automatically identifies the reaction models involved in the deposition of films on substrates with nanometer- or micrometer-sized trenches by Chemical Vapor Deposition (CVD) processes. The reaction models, which comprise various deposition species and surface reactions with different values of sticking coefficient, were determined both quantitatively and qualitatively on the basis of chemical kinetics. Automatic modeling is achieved by the system through the analysis of the experimental data of the cross-sectional shapes of the deposited films. The system consists of three components, that is, a user interface, an inference engine, and a process simulator based on Simplified Monte Carlo (SMC) method that reproduce film shapes. The inference engine proposes a reaction model, examines its validity by comparing the experimental results with the predicted ones obtained by using the simulator, and then corrects it using simple Genetic Algorithms (GA), or Real-Coded GA (RCGA). We investigated the three GA methods, that is, simple GA, BLX-alpha, and REX/JGG. REX/JGG showed the best overall performance with regard to accuracy, cost, and robustness of the calculation.

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Fast and accurate calculation of the predicted results of Chemical Vapor Depositions (CVD) is very helpful to the R&D of the CVD processes. Therefore, we have developed a novel calculation method, by which accurate calculations along with reduced computing cost were achieved, to reproduce deposition profiles in a macroscopic cavity (macrocavity). Boundary value problems for estimating diffusion-reaction equations by iterations of numerical integrations were changed into problems of synthesizing a few basis functions and then finding the linear combinations consisted of the functions. We optimized the coefficients of the linear combinations by Real-Coded Genetic Algorithms (RCGA). We investigated three methods of RCGA, that is, BLX-alpha, REX, REX star. REX star showed the best performance with regard to both the cost and accuracy of the calculation.

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The chitin is a raw material of N-acetylglucosamine. We proposed the process of manufacturing it with few negative environmental impacts. The process of manufacture that used the hydrochloric acid was used so far. Our method is characterized by the combining crushing with the saccharification method with the enzyme. In this method, the quality rating of the powder by crushing becomes an important point. The presumption accuracy of the degree of crystallinity that used the near-infrared spectrum was able to be improved more by using the genetic algorithm-PLS (GA-PLS). This is a prediction model by the variable selection by GA and the application of PLS regression models. The degree of crystallinity of sample powders were measured by XRD, beforehand. Moreover, the examination of the presumption of the particle size distribution is advanced.

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In modern drug discovery research, it is very important to rapidly specify the position and structure around the active site of a protein and to develop high speed and high accurate score function. So, in this paper, we propose a new strategy for computational molecular screening method. Our strategy is consist of four stepwise approaches grounded in a solvent accessible area calculation (DefPol), Delaunay triangulation, four-body potential evaluation, and active site exploring algorithm. Integrated computer program is tested for a prediction of the known active site and ligand conformation in a protein-peptide complex. Results in prediction accuracy will be discussed at poster session.

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Potential energy surfaces of H2, H2+ and H2- molecules calculated by B3LYP with 6-311G** basis set are compared with those by Hartree-Fock (HF). H2+ has no exchange correlation and electron correlation. H2 has exchange correlation and electron correlation. H2- has larger exchange correlation and electron correlation than H2. In the case of H2, potential surfaces of HF and B3LYP are almost the same not only in equilibrium region but also in long inter-atomic distance region. However, potential surfaces of H2+ and H2- generated by B3LYP are different from those of HFs, especially in long inter-atomic distance region. The potential surfaces have maximum at about 3Å and are qualitatively wrong at long distance.

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The many-body interaction energies between nucleobases of DNA were calculated by means of ab initio MO method. We performed ab initio MO calculations for 2 and 3 base-pair steps in the conformation of B-DNA. To construct the stacking conformation for a base-pair in B-DNA, the geometry optimization was performed for each base-pair (A-T and G-C). All the stacked base-pairs were assumed to be parallel, with Rise 3.5 Å between them and Twist 36 degrees. Each many-body term in the interaction between nucleobases was obtained in the conformation of the stacked base-pairs. All the calculations were done with the theoretical level of MP2/6-31G(d). As for the interaction between bases, we found that the two-body term is dominant and each many-body term value depends on the base-sequence. The calculated interaction energies, the hydrogen bonding between the bases and the stacking interaction between the base-pairs, were used to estimate the stability of DNA oligomers (ΔE) with various base-sequences. Good correlation was found between the estimated ΔE values and the experimental ΔG values. This indicates that the internal energy of DNA oligomer can be estimated from summing-up of the constituent hydrogen bonding and the stacking interaction energies according to the base-sequence.

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Prion protein is known as a cause of the prion diseases: BSE, CJD, scrapie, and so on. It is also considered that a structural change from PrPc to PrPSc may cause the diseases, although the three-dimensional structure of PrPSc is not known yet. It is speculated that PrPSc has a structure of left-handed parallel beta helix. In that helix, several triangular rungs are stacked, in which around 18 amino acids are included. In this study, we focus on the origin of the stability of a left-handed parallel beta helix. We estimate the stability of the helix as a sum of the backbone conformational energy, the backbone hydrogen bonding energy, the side chain hydrogen bonding energy and the side chain van der Waals interaction energy. To estimate the backbone conformational energy, we calculated the phi-psi map of alanine model molecule by optimizing all other geometrical parameters. It was found that the backbone conformational energy of a left-handed parallel beta helix is lower than that of an alpha helix. We also calculated the van der Waals interaction energy between the hydrophobic amino acid residues. We found that the van der Waals interaction energy between two rungs is about -10kcal/mol: it plays an important role in forming the beta helix structure.

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It is well known that molecular properties, including biological functions, are closely related not only to the atomic connectivity but also to the 3D spatial arrangements of the atoms. In the present work, we have developed a computer program to identify the maximal 3D common substructures between a pair of molecular structures based on a graph theoretical clique-finding algorithm. It is applied for the 3D structural similarity search for a given data set. A query molecule and each molecule in the data set are compared using the program, and the number of atoms of the identified 3D common substructure is defined as a similarity measurement. A relative measurement such as Tanimoto coefficient is also used. Then, the feature fragments are extracted from the identified substructures for an every pair of structures in the database. Each atom (or atomic group) of a reference molecule is weighted by the frequency of appearance, and selected as constitute atoms of the feature fragment. Molecular properties such as an activity class are used to construct a 3D feature fragment dictionary.

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