0000000000022419
AUTHOR
J.v. De Julián-ortiz
Application of molecular topology to the prediction of potency and selection of novel insecticides active against malaria vectors
Abstract A study on the basis of molecular topology has been carried out to predict the potency of insecticides active against malaria vectors (Culex) as well as to select novel compounds potentially active on those vectors. The results, performed over two sets of compounds, namely hormone-like and ‘common’ or wide-spectra insecticides, demonstrate that the adequate combination of topological charge indices and simple topological-geometric indices, yield very good results in both, the prediction of potency and the selection of new insecticides. Further development should be addressed in the future; however, the achievement described here is extremely encouraging.
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 Letters79, 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
A study is reported of the relationship between theR F 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 studi…
Topological Approach to Drug Design
In this paper we demonstrated that by an adequate combination of different topological indices it is possible to select and design new active compounds in different therapeutical scopes, with a very high efficiency level. Particularly successful in the search of new "lead drugs", the results show the surprising ability of the topological methods to describe molecular structures.
ChemInform Abstract: Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds.
In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.
New Analgesics Designed by Molecular Topology
Molecular topology has been applied to the design of new analgesic drugs, utilizing linear discriminant analysis and connectivity functions using different topological descriptors. Of a total of 26 compounds selected, 17 showed analgesic activity. The following stood out particularly, showing analgesic values greater than 75% regarding ASA (acetylsalicylic acid), the reference drug: 2-(1-propenyl)phenol, 2′4′ dimethylacetophenone, p-chlorobenzohydrazide, 1-(p-chlorophenyl) propanol and 4-benzoyl-3-methyl-1-phenyl-2-pyrazolin-5-one. The usefulness of the design method has been demonstrated in the search of new chemical structures having analgesic effects, some of which could become “lead dru…
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.
Prediction of Indices of Refraction and Glass Transition Temperatures of Linear Polymers by Using Graph Theoretical Indices
Graph theoretical indices were exclusively used in the prediction of indices of refraction, n, and glass transition temperatures, Tg, into a group of addition polymers. Models with 10 variables were selected for the prediction of n (r = 0.981, SEE = 0.0147) and Tg/M (r = 0.946, SEE = 0.439). The average errors in the predictions were 0.69% and 12.7% for n and Tg, respectively. The descriptors involved in these models were calculated from the structures of the monomers.
Prediction of properties of chiral compounds by molecular topology
Abstract 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 σ receptor for a group of 3-hydroxy phenyl piperidines are specifically pr…
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.
General topological patterns of known drugs.
Abstract Discriminating “drug-like” from “non-drug-like” compounds is a relatively emerging topic within the drug research. The basic assumption is that it is possible to obtain relevant information from structural features common to the known drugs, in order to discard a huge number of candidate chemical structures with low probability of becoming drugs. A graph-theoretical contribution to this subject is reported in this paper, by making exclusive use of linear relationships. The results suggest that it is possible to achieve a pattern of general pharmacological activity based on molecular topology. Conclusions are tentative pending verification of the results with larger compound librari…
Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds
In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.
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.
Internal Test Sets Studies in a Group of Antimalarials
Topological indices have been applied to build QSAR models for a set of 20 an- timalarial cyclic peroxy cetals. In order to evalua te the reliability of the proposed linear models leave-n-out and Internal Test Sets (ITS) approaches have b een considered. The pro- posed procedure resulted in a robust and consensued prediction equation and here it is shown why it is superior to the employed standard c ross-validation algorithms involving multilinear regression models.
Some Relationships between Molecular Energy-Topology and Symmetry
Molecular Topology (M.T.) has demonstrated its efficiency in the prediction of many experimental parameters. The application of the topological indices to the prediction of pharmacological properties, and, above all, to its inverse problem, the drug design, is particularly interesting [1,2]. Several attempts to explain the reasons of such efficiency have been carried out [3,4]. So far, we are not close to a definitive answer.
Equivalence of the Pecka–Ponec Correlation Probability and the Statistical F Significance for MLR Models
In an article of this journal Pecka and Ponec [J. Math. Chem. 27 (2000) 13] have proposed, by means of a probability calculation, a method to evaluate the statistical importance of correlations obtained from multilinear regression equations involving an arbitrary number of experimental points and parameters. Here, it is demonstrated how this probability exactly coincides with a more general concept: the confidence probability of an F distribution having the appropriate degrees of freedom.
Pharmacological studies of 1-(p-chlorophenyl)propanol and 2-(1-hydroxy-3-butenyl)phenol: Two new non-narcotic analgesics designed by molecular connectivity
Abstract Molecular topology has been applied to the design of new analgesic drugs. Linear discriminant analysis and connectivity functions were used to design two potentially suitable drugs which were synthesized and tested for analgesic properties by the acetic acid-induced abdominal constriction test in mice and the tail-flick test in rats. In mice, the compound 1-(p-chlorophenyl)propanol showed higher analgesic activity, both intraperitoneally and orally, than acetylsalicylic acid. 2-(1-Hydroxy-3-butenyl)phenol exhibited a lesser protective effect (70% of that shown by acetylsalicylic acid). In rats, acetylsalicylic acid gave the greatest protection against pain when administered intrape…
Virtual darwinian drug design: QSAR inverse problem, virtual combinatorial chemistry, and computational screening.
The generation of diversity and its further selection by an external system is a common mechanism for the evolution of the living species and for the current drug design methods. This assumption allows us to label the methods based on generation and selection of molecular diversity as "Darwinian" ones, and to distinguish them from the structure-based, structure-modulation approaches. An example of a Darwinian method is the inverse QSAR. It consists of the computational generation of candidate chemical structures and their selection according to a previously established QSAR model. New trends in the field of combinatorial chemical syntheses comprise the concepts of virtual combinatorial synt…
Use of molecular topology for the prediction of physico-chemical, pharmacokinetic and toxicological properties of a group of antihistaminic drugs
We used molecular connectivity to search mathematical models for predicting physico-chemical (e.g. the partition coefficient, P), pharmacokinetic (e.g. the time of maximum plasma level, and toxicological properties (lethal dose, LD) for a group of antihistaminic drugs. The results obtained clearly reveal the high efficiency of molecular topology for the prediction of these properties. Randomization and cross-validation by use of leave-one-out tests were also performed in order to assess the stability and the prediction ability of the connectivity functions selected.
Pharmacological distribution diagrams: a tool for de novo drug design.
Abstract 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 discrimianant function in which exists a good expectancy to find new active drugs. A set of β-blockers with contrasted activity has been selected to test the ability of PDDs as a visualizing technique, for the identification of n…