Home About us Contact
|
Home About us Contact | ||
|
|
||
Chemical Interpretation (chemical + interpretation)
Selected AbstractsHow the choice of a computational model could rule the chemical interpretation: The Ni(II) catalyzed ethylene dimerization as a case studyJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 5 2010Vincent Tognetti Abstract In this article, we present a critical study of the theoretical protocol used for the determination of the nickel(II) catalyzed ethylene dimerization mechanism, considered as a representative example of the various problems related to the modeling a catalytic cycle. The choice of an appropriate computational procedure is indeed crucial for the validity of the conclusions that will be drawn from the computational process. The influence of the exchange-correlation functional on energetic profiles and geometries, the role of the basis set describing the metal atom, as well as the importance of the chosen molecular model, have been thus examined in details. From the obtained results, some general conclusions and guidelines are presented, which could constitute useful warnings in modeling homogenous catalysis. Besides, the database constituted by our high-level calculations can be used within benchmarking procedures to assess the performances of new computational methods based on density functional theory. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010 [source] Computational modeling of tetrahydroimidazo-[4,5,1-jk][1,4]-benzodiazepinone derivatives: An atomistic drug design approach using Kier-Hall electrotopological state (E-state) indicesJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 11 2008Nitin S. Sapre Abstract Quantitative structure-activity relationships (QSAR), based on E-state indices have been developed for a series of tetrahydroimidazo-[4,5,1-jk]-benzodiazepinone derivatives against HIV-1 reverse transcriptase (HIV-1 RT). Statistical modeling using multiple linear regression technique in predicting the anti-HIV activity yielded a good correlation for the training set (R2 = 0.913, R = 0.897, Q2 = 0.849, MSE = 0.190, F -ratio = 59.97, PRESS = 18.05, SSE = 0.926, and p value = 0.00). Leave-one-out cross-validation also reaffirmed the predictions (R2 = 0.850, R = 0.824, Q2 = 0.849, MSE = 0.328, and PRESS = 18.05). The predictive ability of the training set was also cross-validated by a test set (R2 = 0.812, R = 0.799, Q2 = 0.765, MSE = 0.347, F -ratio = 64.69, PRESS = 7.37, SSE = 0.975, and p value = 0.00), which ascertained a satisfactory quality of fit. The results reflect the substitution pattern and suggest that the presence of a bulky and electropositive group in the five-member ring and electron withdrawing groups in the seven-member ring will have a positive impact on the antiviral activity of the derivatives. Bulky groups in the six-member ring do not show an activity-enhancing impact. Outlier analysis too reconfirms our findings. The E-state descriptors indicate their importance in quantifying the electronic characteristics of a molecule and thus can be used in chemical interpretation of electronic and steric factors affecting the biological activity of compounds. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2008 [source] Quantitative Structure,Activity Relationship Study on Fish Toxicity of Substituted BenzenesMOLECULAR INFORMATICS, Issue 8 2008Zhiguo Gong Abstract Many chemicals cause latent harm, such as erratic diseases and change of climate, and therefore it is necessary to evaluate environmentally safe levels of dangerous chemicals. Quantitative Structure,Toxicity Relationship (QSTR) analysis has become an indispensable tool in ecotoxicological risk assessments. Our paper used QSTR to deal with the modeling of the acute toxicity of 92 substituted benzenes. The molecular descriptors representing the structural features of the compounds were calculated by CODESSA program. Heuristic Method (HM) and Radial Basis Function Neural Networks (RBFNNs) were utilized to construct the linear and the nonlinear QSTR models, respectively. The predictive results were in agreement with the experimental values. The optimal QSTR model which was established based on RBFNNs gave a correlation coefficient (R2) of 0.893, 0.876, 0.889 and Root-Mean-Square Error (RMSE) of 0.220, 0.205, 0.218 for the training set, the test set, and the whole set, respectively. RBFNNs proved to be a very good method to assess acute aquatic toxicity of these compounds, and more importantly, the RBFNNs model established in this paper has fewer descriptors and better results than other models reported in previous literatures. The current model allows a more transparent chemical interpretation of the acute toxicity in terms of intermolecular interactions. [source] On the effect of neglecting anharmonic nuclear motion in charge density studiesACTA CRYSTALLOGRAPHICA SECTION A, Issue 3 2010Kathrin Meindl The effect of neglecting anharmonic nuclear motion when it is definitely present is studied. To ensure the presence of anharmonic nuclear motion a model was used that was previously refined against experimental data including anharmonic nuclear motion, and these calculated structure factors were used as observed data for a multipole refinement. It was then studied how the neglect of anharmonic nuclear motion and noise in the data affects the usual crystallographic quality measure R, the density parameters and the residual density distribution. It is demonstrated that the neglect of anharmonic nuclear motion leads to a characteristic imprint onto the residual density distribution in terms of residual density peaks and holes, in terms of the whole residual density distribution and in terms of the number, location and strength of valence shell charge concentrations (VSCCs). These VSCCs differ from that of the input model in a way which heavily influences and misleads the chemical interpretation of the charge density. This imprint vanishes after taking anharmonic nuclear motion into account. Also the input model VSCCs are restored. The importance of modeling anharmonic nuclear motion is furthermore shown by the characteristic imprint on the residual density distribution, even in the case of a numerically almost unaffected R value. [source] Analysis of difference two-electron density matrix between two states of magnetic moleculesINTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, Issue 4-5 2001D. Yamaki Abstract Previously, a method based on the two-electron density matrix (2-DM) has been used to obtain chemical interpretations with electron correlations. In the method, a 2-DM is expanded by its natural geminals. These natural geminals are visualized to obtain their chemical interpretations. An electronic state is understood as the set of geminals that have various correlations of two electrons. In this work, a extension of previous 2-DM-based method is described to compare two states of a system. In this method, the difference 2-DM between the two states is used instead of 2-DM itself. The applications of the method to trans-butadiene and trimethylene methane are shown. © 2001 John Wiley & Sons, Inc. Int J Quantum Chem, 2001 [source] | ||||||||||