Miscellaneous
http://qsardb.org/repository/handle/10967/107
2018-01-17T10:41:48ZKatritzky, A. R.; Kasemets, K.; Slavov, S.; Radzvilovits, M.; Tämm, K.; Karelson, M. Estimating the toxicities of organic chemicals in activated sludge process. Water Res. 2010, 44, 2451–2460.
http://qsardb.org/repository/handle/10967/200
The experimental log EC(50) toxicity values of 104 compounds causing bioluminescent repression of the bacterium strain Pseudomonas isolated from an industrial wastewater were studied. Using the Best Multilinear Regression method implemented in CODESSA PRO, models with up to 8 theoretical descriptors were obtained. Utilizing a rigorous descriptor selection and validation procedure a reliable QSAR model with four parameters was selected as best. The proposed model emphasizes the importance of the halogen atoms presented in each compound, the possibility of H-bond formation and the flexibility and degree of branching of the molecules. As pointed out by many researchers, the contribution of the octanol water partition coefficient to the explanation of the toxicity effect was also found to be significant. In addition, the model currently proposed was compared to those reported earlier and its advantages were discussed in detail.
2017-05-23T00:00:00ZClark, D. E. Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood–brain barrier penetration. J. Pharm. Sci. 1999, 88, 815–821.
http://qsardb.org/repository/handle/10967/199
This paper describes the derivation of a simple QSAR model for the prediction of log BB from a set of 55 diverse organic compounds. The model contains two variables: polar surface area (PSA) and calculated logP, both of which can be rapidly computed. It therefore permits the prediction of log BB for large compound sets, such as virtual combinatorial libraries. The performance of this QSAR on two test sets taken from the literature is illustrated and compared with results from other reported computational approaches to log BB prediction.
2017-05-18T00:00:00ZToropov, A. A.; Benfenati, E. QSAR models of quail dietary toxicity based on the graph of atomic orbitals. Bioorg. Med. Chem. Lett. 2006, 16, 1941–1943.
http://qsardb.org/repository/handle/10967/198
Graphs of atomic orbitals (GAOs) have been used to represent molecular structures. We describe rules to convert the labelled hydrogen-filled graphs (LHFGs) into GAOs. The GAO is one possible way of taking account of the structure of atoms (i.e., atomic orbitals, such as 1s1, 2p2 and 3d10) for QSPR/QSAR analyses. Optimization of correlation weights of local invariants (OCWLI) of the LHFGs and the GAOs was used to obtain a method of quail dietary toxicity modelling. Statistical characteristics of the models based on the OCWLI of GAO are better than those based on the OCWLI of the LHFGs.
2017-05-16T00:00:00ZGharagheizi, F. Prediction of upper flammability limit percent of pure compounds from their molecular structures. J. Hazard. Mater. 2009, 167, 507–510.
http://qsardb.org/repository/handle/10967/197
In this study, a quantitative structure–property relationship (QSPR) is presented to predict the upper flammability limit percent (UFLP) of pure compounds. The obtained model is a five parameters multi-linear equation. The parameters of the model are calculated only from chemical structure. The average absolute error and squared correlation coefficient of the obtained model over all 865 pure compounds used to develop the model are 9.7%, and 0.92, respectively.
2017-05-16T00:00:00Z