Acute Toxicity Hazards: Difference between revisions

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Acute Toxicity module performs rapid and accurate predictions of the tested compounds' LD50 values in rodents after various administration routes. The Acute Toxicity Hazards module is a knowledge-based expert system. It identifies hazardous fragments (toxicity alerts) that may be responsible for the high acute toxicity of compounds in rodents.
The Acute Toxicity Hazards module is a knowledge-based expert system. It identifies hazardous fragments (toxicity alerts) that may be responsible for the high acute toxicity of compounds in rodents.
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# Possible “Oral Acute Toxicity Hazard Categories” and corresponding oral acute toxicity labels. Chemicals can be allocated to one of five toxicity categories based on acute toxicity by oral route of administration according to numeric criteria expressed as LD50 (oral administration to rats). <br>[[File:acute_toxicity_categories_table.png]]<br>Hover over the label to see it more detailed:<br>[[File:acute_toxicity_categories_hint.png]]
# The highlighted part of molecule indicates the identified hazardous substructure that may be responsible for high acute toxicity of the compound.
# Probability table describes the probability that LD50 value is lower (greater) that the defined limit. This table is the basis for the definition of oral hazard categories.
# Click to select the different administration route.
# Up to 5 similar structures from training set with experimental LD50 values (oral administration to rats), corresponding oral acute toxicity categories and similarity indices to tested compound are provided by the model.
# Identified hazardous substructures are presented in the form of tab list. Click the corresponding tab to select a hazardous fragment. The name and short description of hazardous fragments are described. Intensity of red ‘dot’ shows the difference between the mean LD50 value in the entire training set and its sub-set possessing a hazardous fragment.
# Box-and-Whisker plot of acute toxicity in the training set and among compounds possessing the fragment. Median, 5%, 25%, 50%, 75%, 95% quantiles are presented.
# Acute toxicity distribution density plot displays relationship between frequency of compounds possessing certain acute toxicity values in the entire training set and the LD50 values for the compounds, containing the highlighted hazardous fragment, indicated by red points.
# Number of compounds, mean values and t-test for significance of difference between acute toxicity distribution density plots in the entire training set and the sub-set of compounds possessing hazardous fragment.
# Up to 5 most similar structures in training set possessing the hazardous fragment with structures names, experimental values of LD50 (mg/kg) and similarity index. This index is based on QSAR analysis of logLD50 data.<br />
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Box-and-Whisher plot of acute toxicity in the training set and
<div class="mw-collapsible">
among compounds possessing the fragment. Median, 5%,
25%, 50%, 75%, 95% quantiles presented.
 
Click to select the different
administration route
 
The highlighted part of molecule indicates the
identified hazardous substructure that may be responsible
for high acute toxicity of the compound
 
Acute toxicity distribution plots
 
List of identified hazardous substructures. Click the tab to
select a hazardous fragment
 
The name and a short description of the hazardous fragment
 
Up to 5 most similar structures in training set possessing the
hazardous fragment with structures names, experimental
values of LD50 (mg/kg) and similarity index. This index is
based on QSAR analysis of logLD50 data
 
Acute toxicity distribution density plot displays relationship
between frequency of compounds in the training set and
acute toxicity values. Red points – compounds containing
 
 
 
 
Identified hazardous substructures are presented in the form of tab list. Click the corresponding tab to select a hazardous fragment. The name and short description of hazardous fragments are described. Intensity of red ‘dot’ shows the difference between the mean LD50 value in the entire training set and its sub-set possessing a hazardous fragment. Two hazardous fragments are found in the analyzed molecule – “Aryloxy carbamate” and “Aryloxy N,N-dimethylcarbamate” (aryloxy carbamate moiety with good N-substitution for anticholinesterase activity). ‘More dangerous’ substructure (more intensive red color) is selected by default. Click the corresponding tab to select another hazardous fragment.
Selected hazardous fragment is highlighted in the Structure Pane.
Select toxicity system – oral administration to rats (usual system for the acute toxicity study of pesticides).
Toxicity distribution plots show significance of the identified hazardous fragments for acute toxicity: (a) Box-and-Whisker plot of acute toxicity values in the entire training set and among compounds possessing the fragment Median, 5%, 25%, 30%, 75%, 95% quantiles are presented. (b) Acute toxicity distribution density plot displays relationship between frequency of compounds possessing certain acute toxicity values in the entire training set and the LD50 values for the compounds, containing the highlighted hazardous fragment, indicated by red points.
Number of compounds, mean values and t-test for significance of difference between acute toxicity distribution density plots in the entire training set and the sub-set of compounds possessing hazardous fragment. As one can see in this particular example, mean LD50 value is significantly lower in the sub-set of compounds possessing hazardous fragment (46 mg/kg) compared to the entire training set (850 mg/kg).
Up to 5 most similar structures possessing selected hazardous fragment are displayed along with experimental data and Similarity Index to tested compound.
 
 
 
 
<div class="mw-collapsible mw-collapsed">


==Technical information==
==Technical information==
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A standard measure of acute toxicity is LD50 (lethal dose 50) defined as a dose that is lethal to 50% of the treated animals. It can be viewed as a “cumulative potential” to cause various acute effects and death of animals. To obtain a linear relationship with structural properties these data were converted to logarithmic form (pLD50) for modeling, but the final prediction results returned to the user are converted back to LD50 value (mg/kg).
A standard measure of acute toxicity is LD50 (lethal dose 50) defined as a dose that is lethal to 50% of the treated animals. It can be viewed as a “cumulative potential” to cause various acute effects and death of animals. To obtain a linear relationship with structural properties these data were converted to logarithmic form (pLD50) for modeling, but the final prediction results returned to the user are converted back to LD50 value (mg/kg).


In Tox Boxes LD50 is calculated for two different rodent species: toxicity for mice is estimated under oral, intraperitoneal, intravenous, subcutaneous administration, and for rats - under oral and intraperitoneal administration.
In ACD/Percepta LD50 is calculated for two different rodent species: toxicity for mice is estimated under oral, intraperitoneal, intravenous, subcutaneous administration, and for rats - under oral and intraperitoneal administration.


===Model Features & Prediction Accuracy===
===Model Features & Prediction Accuracy===
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Acute Toxicity predictor was built using critically evaluated experimental data for more than 100,000 compounds extracted from RTECS and ESIS databases.
Acute Toxicity predictor was built using critically evaluated experimental data for more than 100,000 compounds extracted from RTECS and ESIS databases.


Fragmental QSAR (quantitative structure-activity relationship) was used for the development of baseline LD50 prediction model. The predictions are corrected according to the analysis of experimental LD50 values for similar compounds. Predictions are supported by reliability estimation that takes into account:  
The predictive models of LD50 for all considered species and administration routes were derived using GALAS (Global, Adjusted Locally According to Similarity) modeling methodology (please refer to [http://www.ncbi.nlm.nih.gov/pubmed/20373217] for more details).
* Similarity of tested compound to the training set
 
* Difference between predicted LD50 for tested compound and experimental values for similar compounds
Each GALAS model consists of two parts:
* Consistence of experimental values for similar compounds.
* Global (baseline) statistical model that reflects general trends in the variation of the property of interest.
* Similarity-based routine that performs local correction of baseline predictions taking into account the differences between baseline and experimental LD50 values for the most similar training set compounds.
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GALAS methodology also provides the basis for estimating reliability of predictions by the means of calculated Reliability Index (''RI'') value that takes into account:
* Similarity of tested compound to the training set molecules.
* Consistence of experimental LD50 values and baseline model prediction for the most similar similar compounds from the training set.


Predictive models of LD50 in various systems have been validated on external data sets. Validation results show that the accuracy of prediction is proportional to the reliability index. The predictions with a high or moderate reliability index are accurate (average prediction error is about 0.5-0.7 log units). A high/moderate reliability index was reported for 20-50% of compounds in the validation sets.
Reliability Index ranges from 0 to 1, where 0 corresponds to a completely unreliable, and 1 - a highly reliable prediction. Compounds obtaining predictions ''RI'' < 0.3 are considered outside of the Applicability Domain of the model.
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Predictive models of LD50 in various systems have been validated on external data sets. Validation results show that the accuracy of prediction is proportional to the Reliability Index. The predictions with a high or moderate Reliability Index (''RI'' > 0.5) are accurate to RMSE of about 0.5-0.7 log units. Reliability Index values in this range were reported for 30-60% of compounds in the validation sets. More information regarding the modeling principles and validation results are available in our publication [http://www.ncbi.nlm.nih.gov/pubmed/20373217].


===OECD Ranges===
===OECD Ranges===

Latest revision as of 09:57, 15 June 2017

Overview


The Acute Toxicity Hazards module is a knowledge-based expert system. It identifies hazardous fragments (toxicity alerts) that may be responsible for the high acute toxicity of compounds in rodents.

Features

  • ACD/Percepta contains 86 “hazardous fragments”. These fragments were identified by analysis of toxicological literature and tested on acute toxicity data of more than 100,000 compounds.
  • The toxicity distribution plots show significance of the identified hazardous fragments on the acute toxicity.
  • Experimental LD50 value and similarity to test compound is shown for 5 most similar structures from the training set.


Interface


Acute toxicity hazards.png


  1. The highlighted part of molecule indicates the identified hazardous substructure that may be responsible for high acute toxicity of the compound.
  2. Click to select the different administration route.
  3. Identified hazardous substructures are presented in the form of tab list. Click the corresponding tab to select a hazardous fragment. The name and short description of hazardous fragments are described. Intensity of red ‘dot’ shows the difference between the mean LD50 value in the entire training set and its sub-set possessing a hazardous fragment.
  4. Box-and-Whisker plot of acute toxicity in the training set and among compounds possessing the fragment. Median, 5%, 25%, 50%, 75%, 95% quantiles are presented.
  5. Acute toxicity distribution density plot displays relationship between frequency of compounds possessing certain acute toxicity values in the entire training set and the LD50 values for the compounds, containing the highlighted hazardous fragment, indicated by red points.
  6. Number of compounds, mean values and t-test for significance of difference between acute toxicity distribution density plots in the entire training set and the sub-set of compounds possessing hazardous fragment.
  7. Up to 5 most similar structures in training set possessing the hazardous fragment with structures names, experimental values of LD50 (mg/kg) and similarity index. This index is based on QSAR analysis of logLD50 data.



Technical information


Calculated quantitative parameter

A standard measure of acute toxicity is LD50 (lethal dose 50) defined as a dose that is lethal to 50% of the treated animals. It can be viewed as a “cumulative potential” to cause various acute effects and death of animals. To obtain a linear relationship with structural properties these data were converted to logarithmic form (pLD50) for modeling, but the final prediction results returned to the user are converted back to LD50 value (mg/kg).

In ACD/Percepta LD50 is calculated for two different rodent species: toxicity for mice is estimated under oral, intraperitoneal, intravenous, subcutaneous administration, and for rats - under oral and intraperitoneal administration.

Model Features & Prediction Accuracy

Acute Toxicity predictor was built using critically evaluated experimental data for more than 100,000 compounds extracted from RTECS and ESIS databases.

The predictive models of LD50 for all considered species and administration routes were derived using GALAS (Global, Adjusted Locally According to Similarity) modeling methodology (please refer to [1] for more details).

Each GALAS model consists of two parts:

  • Global (baseline) statistical model that reflects general trends in the variation of the property of interest.
  • Similarity-based routine that performs local correction of baseline predictions taking into account the differences between baseline and experimental LD50 values for the most similar training set compounds.


GALAS methodology also provides the basis for estimating reliability of predictions by the means of calculated Reliability Index (RI) value that takes into account:

  • Similarity of tested compound to the training set molecules.
  • Consistence of experimental LD50 values and baseline model prediction for the most similar similar compounds from the training set.

Reliability Index ranges from 0 to 1, where 0 corresponds to a completely unreliable, and 1 - a highly reliable prediction. Compounds obtaining predictions RI < 0.3 are considered outside of the Applicability Domain of the model.

Predictive models of LD50 in various systems have been validated on external data sets. Validation results show that the accuracy of prediction is proportional to the Reliability Index. The predictions with a high or moderate Reliability Index (RI > 0.5) are accurate to RMSE of about 0.5-0.7 log units. Reliability Index values in this range were reported for 30-60% of compounds in the validation sets. More information regarding the modeling principles and validation results are available in our publication [2].

OECD Ranges

Chemicals are assigned to one of the five Oral Acute Toxicity Hazard Categories according to the numeric criteria expressed as LD50 (oral administration to rats). Categories were defined by OECD (Organization for Economic Cooperation and Development. A Guide to The Globally Harmonized System of Classification and Labeling of Chemicals (GHS)):

  • V – LD50 2000-5000 mg/kg (may be harmful if swallowed)
  • IV – 300-2000 mg/kg (harmful if swallowed)
  • III – 50-300 mg/kg (toxic if swallowed)
  • II – 5-50 mg/kg (fatal if swallowed)
  • I < 5 mg/kg (fatal if swallowed).

Toxicity hazards

Toxicity Hazards is a knowledge-based expert system that identifies and highlights structural elements that may be responsible high acute toxicity of compounds in rodents. Tox Hazards system contains a list of 86 predefined 'toxicophores' compiled after thorough analysis of toxicological literature. Significance of the defined hazardous fragments was verified on acute toxicity data set (more than 100,000 compounds).