J.V. de Julián-Ortiz

Pharmacological distribution diagrams: A tool for de novo drug design

Discriminant analysis applied to SAR studies using topological descriptors allows us to plot frequency distribution diagrams: a function of the number of drugs within an interval of values of discriminant function vs. these values. We make use of these representations, pharmacological distribution diagrams (PDDs), in structurally heterogeneous groups where generally they adopt skewed Gaussian shapes or present several maxima. The maxima afford intervals of discriminant function in which exists a good expectancy to find new active drugs. A set of beta-blockers with contrasted activity has been selected to test the ability of PDDs as a visualizing technique, for the identification of new beta-blocker active compounds.

Prediction of properties of chiral compounds by molecular topology

A common assumption in chemistry is that chiral behavior is associated with 3-D geometry. However, chiral information is related to symmetry, which allows the topological handling of chiral atoms by weighted graphs and the calculation of new descriptors that give a weight to the corresponding entry in the main diagonal of the topological matrix. In this study, it is demonstrated that, operating in this way, chiral topological indices are obtained that can differentiate the pharmacological activity between pairs of enantiomers. The 50% inhibitory concentration (IC50) values of the D2 dopamine receptor and the sigma receptor for a group of 3-hydroxy phenyl piperidines are specifically predicted. Moreover, the sedative character of a group of chiral barbiturates can be identified.

Use of topological descriptiors in chromatographic chiral separations

Abstract Studies of enantiomeric separations are reported, specifically the direct chromatographic separation of enantiomers using a chiral stationary phase by molecular topology. The results obtained show good correlation equations for the capacity factor, k ′, and the separation factor, α, for different set of compounds (hydantoins, aromatic α-amino acids and arylamides). Such equations may be useful for the selection of the optimum stationary and mobile phases for the separation of enantiomers. Futher, the correlation between topological descriptors and performance in chiral separations opens up a new approach to the design of chiral stationary phases.

Molecular connectivity to find β-blockers with low toxicity

Abstract Molecular connectivity has been used to find new β-blocker drugs using linear discriminant analysis and connectivity functions with different topological descriptors. Among the selected compounds stands out the probucol and the β-carotene. Both of them interact with β adrenoceptors.

Search of a topological pattern to evaluate toxicity of heterogeneous compounds.

Abstract Molecular connectivity has been applied to the search of mathematical models able to predict the carcinogenic and teratogenic activity of a wide group of structurally heterogeneous compounds. Through the linear discriminant analysis and the diagrams of distribution of pharmacological activity, the classification criteria that minimizes the percentage of error are established. The easiness and speed of the calculation of the descriptors used in this work make the models developed useful in data bases containing a huge number of compounds.

Prediction of chromatographic properties for a group of natural phenolic derivatives by molecular topology

A study was made of the relationship between the RM values obtained by thin-layer chromatography for a group of phenols and connectivity indices proposed by Kier and Hall. By using multivariate regression the corresponding connectivity functions were obtained, which were selected based on their respective statistical parameters. Regression analysis of the connectivity functions showed a correct prediction of the experimental elution sequence for this group of molecules using silica gel stationary phases and mobile phases of different polarity. Random and stability studies of the different prediction models selected were carried out, and good stability and null randomness were obtained in all cases.

True prediction of lowest observed adverse effect levels

SummaryA database of structurally heterogeneous chemical structures with their experimental values of Lowest Observed Adverse Effect Levels (LOAELs) was modeled using graph theoretical descriptors. Variable selection for multiple linear regression (MLR) and linear discriminant analysis (LDA) was accomplished by the Internal Test Set (ITS) method in order to achieve true predicted LOAEL values. The results obtained can be considered good if we take in count the structural diversity of the training set.

Predictability and prediction of lowest observed adverse effect levels in a structurally heterogeneous set of chemicals

A database of chronic lowest observed adverse effect levels (LOAELs) for 234 compounds, previously compiled from different sources (Toxicology Letters 79, 131–143 (1995)), was modelled using graph theoretical descriptors. This study reveals that data are not homogeneous. Only those data originating from the U.S. Environmental Protection Agency (EPA) reports could be well modelled by multilinear regression (MLR) and linear discriminant analysis (LDA). In contrast, data available from the specific procedures of the National Toxicology Program (NTP) database introduced noise and did not render good models either alone, or in combination with the EPA data.

Prediction of chromatographic properties of organophosphorus insecticides by molecular connectivity

SummaryA study is reported of the relationship between theRF values for a group of organophosphorus insecticides obtained by thin layer chromatography and a series of topological descriptors. By using multivariate regression, the corresponding connectivity functions were obtained, which had been selected on the basis of their respective statistical parameters: multiple correlation coefficient (r), standard error of estimate (s), F-Snedecor values and statistical significance (Student’s t). Regression analysis of the connectivity functions can predict the elution behaviour of any structurally similar derivative of this group of compounds with different stationary and mobile phases. Stability studies of the prediction models selected were carried out and yielded good stability in all cases. These results demonstrate the ability of Molecular Topology to identify and predict different structural features that determine theRF values of organophosphorus insecticides obtained by TLC.

Structural invariants for the prediction of relative toxicities of polychloro dibenzo-p-dioxins and dibenzofurans.

Multivariate models are reported that can predict the relative toxicity of compounds with severe environmental impact, namely polychloro dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). Multiple linear regression analysis (MLR) and partial least square projections of latent variables (PLS) show the usefulness of graph-theoretical descriptors, mainly topological charge indices (TCIs), in these series. The general trends of the group are correctly reproduced and better results are presented than have previously been published. In general, the more toxic compounds exhibit more symmetric molecular structures.