Abstract:A quantitative structure−spectrum relationship (QSSR) model was developed to simulate 13 C nuclear magnetic resonance (NMR) spectra of carbinol carbon atoms for 55 alcohols. The proposed model, using multiple linear regression, contained four descriptors solely extracted from the molecular structure of compounds. The statistical results of the final model show that R 2 = 0.982 4 and S=0.869 8 (where R is the correlation coefficient and S is the standard deviation). To test its predictive ability, the model was… Show more
“…When the group is a single atom, its group electro-negativity is Pauling electro-negativity of this atom. For a group with more than two levels, all the atoms or groups attached to “anchor atom” are weighted equally, which can be expressed as follows [ 22 ].…”
Novel group quantitative structure-property relationship (QSPR) models on the thermodynamic properties of PBXTHs were presented, by the multiple linear regression (MLR) analysis method. Four thermodynamic properties were studied: the entropy (Sθ), the standard enthalpy of formation (ΔfHθ), the standard Gibbs energy of formation (ΔfGθ), and the relative standard Gibbs energy of formation (ΔRGθ). The results by the formula indicate that the calculated and predicted data in this study are in good agreement with those in literature and the deviation is within the experimental errors. To validate the estimation reliability for internal samples and the predictive ability for other samples, leave-one-out (LOO) cross validation (CV) and external validation were performed, and the results show that the models are satisfactory.
“…When the group is a single atom, its group electro-negativity is Pauling electro-negativity of this atom. For a group with more than two levels, all the atoms or groups attached to “anchor atom” are weighted equally, which can be expressed as follows [ 22 ].…”
Novel group quantitative structure-property relationship (QSPR) models on the thermodynamic properties of PBXTHs were presented, by the multiple linear regression (MLR) analysis method. Four thermodynamic properties were studied: the entropy (Sθ), the standard enthalpy of formation (ΔfHθ), the standard Gibbs energy of formation (ΔfGθ), and the relative standard Gibbs energy of formation (ΔRGθ). The results by the formula indicate that the calculated and predicted data in this study are in good agreement with those in literature and the deviation is within the experimental errors. To validate the estimation reliability for internal samples and the predictive ability for other samples, leave-one-out (LOO) cross validation (CV) and external validation were performed, and the results show that the models are satisfactory.
The development of prodrugs with an ester bond is classical tool to enhance the bioavailability of pharmaceutical compounds including readily ionizable molecules, such as acids or phenols. In this work, we studied the introduction of a dichloroacetic acid fragment into a molecule as an approach to anticancer prodrug development. The metabolically released dichloroacetate will have an additional useful effect by altering the respiratory cycle of cancer cells and promoting their apoptosis. Derivatives of vitamins B1 and C, paracetamol, and salicylic acid, often used in concomitant cancer therapy, were prepared, and the possibility of selective modifi cation of other polyfunctional compounds was studied. The difference in the reactivity of hydroxy groups in tris(hydroxyphenyl)-substituted cis-imidazoline was studied.
A novel quantitative structure−property relationship (QSPR) model for estimating the solution surface tension of 92 organic compounds at 20 °C was developed based on newly introduced atom-type topological indices. The data set contained non-polar and polar liquids, and saturated and unsaturated compounds. The regression analysis shows that excellent result is obtained with multiple linear regression. The predictive power of the proposed model was discussed using the leave-one-out (LOO) cross-validated (CV) method. The correlation coefficient (R) and the leave-one-out cross-validation correlation coefficient (R CV ) of multiple linear regression model are 0.991 4 and 0.991 3, respectively. The new model gives the average absolute relative deviation of 1.81% for 92 substances. The result demonstrates that novel topological indices based on the equilibrium electro-negativity of atom and the relative bond length are useful model parameters for QSPR analysis of compounds.
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