Abstract
Quantitative Structure-Activity Relationships based on molecular descriptors calculated with Correlation Weights of Local Graph Invariants were developed to model the toxicity of aliphatic compounds to the 50% population growth inhibition. The relationships were computed on the basis of Labeled Hydrogen- Filled Graphs and correlation weights were obtained by an optimization to render as large as possible correlation coefficients between log(IGC50-1) and descriptors calculated with correlation weights. Morgan extended connectivity indices of zero, first, and second orders, paths of lengths two and three and valence shells of second and third ranges have been tested as local invariants of the Labeled Hydrogen-Filled Graphs. The best quantitative relationship obtained from the optimization of correlation weights is that one based on the valence shell of range two. First, second, and third order fitting equations were determined and statistical results are better than other similar data for the same molecular set.
Highlights
The interface of computers and chemistry is characterized, among others, by the challenge of predictive toxicology
Quantitative Structure-Activity Relationships based on molecular descriptors calculated with Correlation Weights of Local Graph Invariants were developed to model the toxicity of aliphatic compounds to the 50% population growth inhibition
The relationships were computed on the basis of Labeled Hydrogen- Filled Graphs and correlation weights were obtained by an optimization to render as large as possible correlation coefficients between log(IGC50-1) and descriptors calculated with correlation weights
Summary
The interface of computers and chemistry is characterized, among others, by the challenge of predictive toxicology. Quantitative Structure-Activity Relationships (QSAR) are models that attempt to relate chemical structure to biological endpoints such as toxicity. 2003, 4 mechanism, differences in chemical structure for a set of known compounds are mapped to changes in toxicity. The QSAR is employed to extrapolate to new compounds, on the basis of a tacit assumption which can be expressed in terms of the following equation
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