Suitable maps of the electrostatic potential were plotted based o

Suitable maps of the electrostatic potential were plotted based on the electronic and nuclear charge distribution obtained from the energy calculations results. The Gaussian suite of programs calculates the electrostatic potential maps and surfaces as the distribution of the CX-6258 chemical structure potential energy of unit positive

charge in a given molecular space, with a resolution controlled by the grid density. In Fig. A in the Supplementary file representative plots for extreme difference in the charge distribution pattern are shown (Frisch et al., 1998; Leach, 2001).   (3) For the calculation of the SYN-117 nmr descriptors the Talete srl, DRAGON for Windows Version 5.5-2007 package was used. Dragon descriptors include 22 different logical blocks. The total number of calculated descriptors was 3224. Several criteria were used to reduce this number while optimizing the information content of the descriptors set. First, descriptors for which no value was available for all the compounds were disregarded. Second, descriptors of which the value is constant (or near-constant) inside each group of descriptors were excluded. For the remaining descriptors, if two descriptors showed a correlation coefficient greater than 0.9, the one showing of the highest pair correlation with the others descriptors was removed. After these automatic screening procedures, a set of

385 descriptors was obtained for further analysis. To reduce the vast number of descriptors to the 50 that correlated ADP ribosylation factor best with the experimental data, the “Feature Selection and Variable Screening” methods available in Statistica® (version 8.0) (2008) software were applied. Then, the chosen descriptors were used as regressors of the model: they are collected in Table A in the Supplementary file and a detailed description of these descriptors can be found in the

literature (Todeschini and Consonni, 2002).   Statistical analysis The Multiple Linear Regression (MLR) (Allison, 1999) and correlation analyses were carried out using the Statistica® (version 8.0) (2008) software. The forward stepwise regression analysis yielded a three-parametric model describing the biological activity as a function of molecular descriptors. The statistical quality of the regression equations was evaluated by parameters such as the correlation coefficient R, the squared correlation coefficient R 2, the adjusted squared correlation coefficient R adj 2 , the Root Mean Squared Errors (RMSE) and the variance ratio F. The statistical significance (P level) of a result was determined as P ≤ 0.01 (Bland, 2000). The model obtained in this study was validated by calculations of the validated squared correlation coefficient (Q 2) values and prediction error sum of squares (called SPRES) values. The Q 2 values were calculated from the general internal cross-validation procedures “leave-one-out” test (LOO) and “leave-many-out” test (LMO) and external tests (EXT) (Baumann, 2005; Golbraikh and Tropsha, 2002; Hawkins, et al.

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