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Structural Descriptors (structural + descriptor)
Selected AbstractsQSAR Study of 2,3-Benzodiazepin-4(thi)one- and 1,2-Phthalazine-Related Negative Allosteric Modulators of the AMPA Receptor: A Structural Descriptors-Based ReassessmentMOLECULAR INFORMATICS, Issue 3 2005Peter Buchwald Abstract In an attempt to establish statistically more rigorous and chemically more meaningful quantitative structure-activity relationship (QSAR) equations, a reassessment of a recent study of in vivo anticonvulsant activity for a set of 2,3-benzodiazepin-4(thi)one- and 1,2-phthalazine-related allosteric AMPA antagonists (n=61) is presented. Contrary to the original, relatively nonspecific descriptor set, which included, for example, a number of topological descriptors, specific structural descriptors that are much easier to interpret from a medicinal chemical point of view are used in this multiple linear regression-based approach. Only statistically significant descriptors have been retained in the final equation, and whereas they give about the same correlation as those of the original paper on the training set (r2 of 0.79 vs. 0.76, n=49), they perform much better on the test set (predictive r of 0.73 vs. 0.05; r2 of 0.78 vs. 0.08, n=12). Descriptors found to be relevant are clearly related to substitutions at known pharmacophore positions, such as those corresponding to the 2,3-, 7,8- and 4,-positions of the benzodiazepine skeleton. Therefore, by a more careful selection of the descriptor set, both an improved prediction and a more intuitive quantitative interpretation could be achieved for this set of allosteric AMPA antagonists. [source] A new biodegradation prediction model specific to petroleum hydrocarbonsENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 8 2005Philip Howard Abstract A new predictive model for determining quantitative primary biodegradation half-lives of individual petroleum hydrocarbons has been developed. This model uses a fragment-based approach similar to that of several other biodegradation models, such as those within the Biodegradation Probability Program (BIOWIN) estimation program. In the present study, a half-life in days is estimated using multiple linear regression against counts of 31 distinct molecular fragments. The model was developed using a data set consisting of 175 compounds with environmentally relevant experimental data that was divided into training and validation sets. The original fragments from the Ministry of International Trade and Industry BIOWIN model were used initially as structural descriptors and additional fragments were then added to better describe the ring systems found in petroleum hydrocarbons and to adjust for nonlinearity within the experimental data. The training and validation sets had r2 values of 0.91 and 0.81, respectively. [source] Neural network modeling of physical properties of chemical compoundsINTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, Issue 1 2001J. Kozio Abstract Three different models relating structural descriptors to normal boiling points, melting points, and refractive indexes of organic compounds have been developed using artificial neural networks. A newly elaborated set of molecular descriptors was evaluated to determine their utility in quantitative structure,property relationship (QSPR) studies. Applying two data sets containing 190 amines and 393 amides, neural networks were trained to predict physical properties with close to experimental accuracy, using the conjugated gradient algorithm. Obtained results have shown a high predictive ability of learned neural networks models. The fit error for the predicted properties values compared to experimental data is relatively small. © 2001 John Wiley & Sons, Inc. Int J Quant Chem 84: 117,126, 2001 [source] Leichhardt's maps: 100 years of change in vegetation structure in inland QueenslandJOURNAL OF BIOGEOGRAPHY, Issue 1 2008R. J. Fensham Abstract Aim, To address the hypothesis that there has been a substantial increase in woody vegetation cover (,vegetation thickening') during the 100 years after the burning practices of aboriginal hunter-gatherers were abruptly replaced by the management activities associated with pastoralism in north-east Australia. Location, Three hundred and eighty-three sites on 3000 km transect, inland Queensland, Australia. Methods, Vegetation structure descriptions from the route notes of the first European exploration of the location by Ludwig Leichhardt in 1844,45 were georeferenced and compiled. Leichhardt's application of structural descriptors (e.g. ,scrub', ,open forest', ,plain') was interpreted as domains within a matrix of tall stratum and low stratum woody cover. Woody cover was also interpreted for the same locations using aerial photography that largely pre-dates extensive land clearing (1940s,1970s) and compared with their structural domain in 1844,45. The fire-sensitive tree, cypress-pine (Callitris glaucophylla) was singled out for case study because it has been widely proposed that the density of this tree has substantially increased under European pastoral management. Results, The coarse resolution of this analysis indicates that the structure of the vegetation has been stable over the first 100 years of pastoralism. For example treeless or sparsely treed plains described by Leichhardt (1844,45) had the same character on the aerial photography (1945,78). Leichhardt typically described vegetation that includes cypress-pine as having a ,thicket' structure suggesting dense regenerating stands of small trees, consistent with the signature typical on the aerial photography. Main conclusions, A large data set of geographically located descriptions of vegetation structure from the first European traverse of inland Australia compared with vegetation structure determined from aerial photography does not support the hypothesis that vegetation thickening has been extensive and substantial. On the contrary the study suggests that the structure of the vegetation has been relatively stable for the first 100 years of European settlement and pastoralism except for those areas that have been affected by broad-scale clearing. [source] Nonlinear quantitative structure-property relationship modeling of skin permeation coefficientJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 11 2009Brian J. Neely Abstract The permeation coefficient characterizes the ability of a chemical to penetrate the dermis, and the current study describes our efforts to develop structure-based models for the permeation coefficient. Specifically, we have integrated nonlinear, quantitative structure-property relationship (QSPR) models, genetic algorithms (GAs), and neural networks to develop a reliable model. Case studies were conducted to investigate the effects of structural attributes on permeation using a carefully characterized database. Upon careful evaluation, a permeation coefficient data set consisting of 333 data points for 258 molecules was identified, and these data were added to our extensive thermophysical database. Of these data, permeation values for 160 molecular structures were deemed suitable for our modeling efforts. We employed established descriptors and constructed new descriptors to aid the development of a reliable QSPR model for the permeation coefficient. Overall, our new nonlinear QSPR model had an absolute-average percentage deviation, root-mean-square error, and correlation coefficient of 8.0%, 0.34, and 0.93, respectively. Cause-and-effect analysis of the structural descriptors obtained in this study indicates that that three size/shape and two polarity descriptors accounted for ,70% of the permeation information conveyed by the descriptors. © 2009 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:4069,4084, 2009 [source] Estimation of the aqueous solubility of organic compounds using molecular connectivity indicesJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 11 2003Chongli Zhong Abstract A correlation for estimation of the aqueous solubility of organic compounds that is based on a training set of 120 chemicals is proposed. The new model proposed is predictive and requires only molecular connectivity indices in the calculations. The calculated results of the new model are comparable to those from the existing general solubility equation (GSE) and the Klopman,Zhu models. The new model was also applied to a testing set of 80 compounds, and the predictions show that the new model is reliable with good predictive accuracy. Because the new model does not require any experimental physicochemical properties in the calculation, it is simple and easy to apply. This work shows again that molecular connectivity indices are useful structural descriptors in quantitative structure,property (QSPR) studies in pharmaceutical research. © 2003 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 92:2284,2294, 2003 [source] QSAR Study of 2,3-Benzodiazepin-4(thi)one- and 1,2-Phthalazine-Related Negative Allosteric Modulators of the AMPA Receptor: A Structural Descriptors-Based ReassessmentMOLECULAR INFORMATICS, Issue 3 2005Peter Buchwald Abstract In an attempt to establish statistically more rigorous and chemically more meaningful quantitative structure-activity relationship (QSAR) equations, a reassessment of a recent study of in vivo anticonvulsant activity for a set of 2,3-benzodiazepin-4(thi)one- and 1,2-phthalazine-related allosteric AMPA antagonists (n=61) is presented. Contrary to the original, relatively nonspecific descriptor set, which included, for example, a number of topological descriptors, specific structural descriptors that are much easier to interpret from a medicinal chemical point of view are used in this multiple linear regression-based approach. Only statistically significant descriptors have been retained in the final equation, and whereas they give about the same correlation as those of the original paper on the training set (r2 of 0.79 vs. 0.76, n=49), they perform much better on the test set (predictive r of 0.73 vs. 0.05; r2 of 0.78 vs. 0.08, n=12). Descriptors found to be relevant are clearly related to substitutions at known pharmacophore positions, such as those corresponding to the 2,3-, 7,8- and 4,-positions of the benzodiazepine skeleton. Therefore, by a more careful selection of the descriptor set, both an improved prediction and a more intuitive quantitative interpretation could be achieved for this set of allosteric AMPA antagonists. [source] CP-MLR/PLS Directed Structure-Activity Modeling of the HIV-1 RT Inhibitory Activity of 2,3-Diaryl-1,3-thiazolidin-4-onesMOLECULAR INFORMATICS, Issue 4 2004Yenamandra Abstract A detailed structure-activity relationship study of the HIV-1 Reverse Transcriptase (RT) inhibitory activity of two series of compounds, 2-(2,6-dihalo phenyl)-3-(substituted pyridin-2-yl)-thiazolidin-4-ones and 2-(2,6-Dihalophenyl)-3-(substituted phenyl)-thiazolidin-4-ones, belonging to 2,3-diaryl-thiazolidin-4-ones in terms of physicochemical and structural descriptors have been carried out using combinatorial protocol interfaced multiple linear regression (CP-MLR) and partial least squares (PLS) analysis. The models developed in the study indicate a preference for hydrophobic compounds for better inhibitory activity. Also, a positive regression coefficient of I2,3, an indicator descriptor meant for the joint disposition of substituents of 2,3-diaryl moieties of thiazolidinones to address their ability in taking a butterfly like conformation, is in agreement with all earlier observations that compounds having the ability to take butterfly like conformation will be showing better inhibitory activity. The identified models suggest that the meta-positions of 3-aryl moiety has the ability to accommodate hydrophobic/ steric groups. The replacement of C2, of 3-phenyl by nitrogen resulted in 3-pyridyl variants of these analogues. Even though from geometry point of view, the phenyls and pyridyls span almost the same structural space and steric features, presence of nitrogen in pyridyls gave them a blend of polarity, electronic features and a different hydrophobicity profile when compared to corresponding phenyl analogue. Furthermore the PLS models, developed from those descriptors took part in CP-MLR models, indicate that most of the descriptors have almost equal influence in accounting for the variation in the activity of these compounds. This suggests that the factors responsible for the variation in the activity have been uniformly distributed across the varying centers of the molecule. The study suggests that thiazolidinones with 3-(pyridin-2-yl) moiety provide scope for further substituent variation to modulate the HIV-1 RT inhibitory activity. [source] Epothilones: Quantitative Structure Activity Relations Studied by Support Vector Machines and Artificial Neural NetworksMOLECULAR INFORMATICS, Issue 7 2003Annalen Bleckmann Abstract In this paper the relation between the structure of epothilones (a new class of anti-tumour agents) and their potential to influence the tubulin-microtubule equilibrium is investigated. Insights into the character of the tubulin-epothilone interactions are derived as the accuracy and reliability of support vector machines and artificial neural networks to model such relations quantitatively is compared. Both methods are well qualified to model relationships between the structure of epothilone derivatives and their anti-tumour activities. Artificial neural networks achieve lower residual standard deviations (22%) compared to support vector machines (25%) and better classification results (89% compared to 75%). However, the reproducibility of the results is greater for support vector machines, which suggests a stronger convergence. The mapping of the influence of individual structural descriptors on the three-dimensional epothilone structure suggests one side of the rather flat molecule to be more important for its activity. The "LIBSVM" software which is used for simulating the support vector machines is freely available from www.csie.ntu.edu.tw/~cjlin/libsvm. The Program "Smart" which is used for simulating artificial neural networks is free for academic use and can be obtained together with the database of epothilones and their activities from www.jens-meiler.de. [source] | ||||||||||