#### CATALOGIC 301C

Endpoint

The biodegradation CATALOGIC 301C model simulates
aerobic biodegradation under MITI I (OECD 301C) test
conditions. The modeled endpoint is the percentage of
theoretical biological oxygen demand on
28^{th} day (*BOD*, %).

Data

The training set contains *BOD* data
for 1514 chemicals under MITI I
(OECD 301C) test conditions. Data for 745
chemicals were collected from the MITI I database
[1] and for other 769 chemicals were
provided by the NITE Japan [2]. The
training set includes 418 readily biodegradable and
1096 not readily biodegradable chemicals.

Another training database of catabolic pathways for more than 550 organic compounds and expert knowledge was used to determine the principal transformations and to train the system to simulate aerobic catabolism of training chemicals. The documented pathways of microbial catabolism were collected from scientific papers, monographs and databases accessible over the Internet.

Model

CATALOGIC 301C model consists of a metabolism simulator
and an endpoint model. The microbial metabolism is simulated
by the rule-based approach. The core parts of the
simulator are a set of hierarchically organized
transformations and a system of rules that control the
application of these transformations. Recursive
application of the transformations allows simulation of metabolism
and generation of biodegradation pathways. Calculation of the
modeled endpoint (*BOD*, %) is based on the simulated
catabolic tree and the material balance of transformations used to
build the tree.

The development of the model consists of: (i) generation of metabolic maps for the training set chemicals using the microbial metabolism simulator; (ii) estimation of probabilities of occurrence of the simulator transformations. Non-linear least square fitting was used to parameterize the model:

where RSS is the residual sum of squares,
*BOD ^{Obs}* and

*BOD*are observed and predicted

^{Calc}*BOD*data of training chemicals and

**P**is a vector of estimated probabilities of transformations. Further details on the mathematical formalism of the model can be reviewed in [3, 4].

The model is fitted to predict percentage of theoretical
biological oxygen demand on 28th day (*BOD*, %). Its
mathematical formalism allows also prediction of half-lives and
quantities of metabolites on 28^{th} day.

Domain

The stepwise approach [5] was used to define the applicability domain of the model. It consists of the following sub-domain levels:

- General parametric requirements - includes ranges of variation
of log
*K*_{OW}and*MW*, - Structural domain - based on atom-centered fragments (ACFs),
- Domain of simulator of metabolism - determines the reliability of the simulated metabolism.

A chemical is considered *In Domain* if its log
*K*_{OW} and *MW* are within the specified
ranges, its ACFs are presented in the training chemicals and if the
simulator contains transformations for its full
mineralization. The information implemented in the
applicability domain is extracted from the correctly predicted
training chemicals used to build the model and in this respect, the
applicability domain determines practically the interpolation space
of the model.

Performance

The goodness of fit evaluated by the squared coefficient of
correlation and adjusted Pearson's contingency
coefficient is *R ^{2}* = 0.72 and

*C*=0.79, respectively. The model correctly classified 87% of experimentally ready and 93% of not ready degradable training chemicals.

^{*}

Reporting

The model provides results for:

*BOD*, %,- Primary half-life, days,
- Ultimate half-life, days,
- Quantities of parent and biodegradation products, mol/mol parent,
- Applicability domain details.

References

1. Chemicals Inspection and Testing Institute, Biodegradation
and Bioaccumulation data of existing chemicals based on the CSCL
Japan, Chemical Industry Ecology-Toxicology & Information
Center, Japan, 1992, ISBN 4-98074-101-1.

2. NITE, Biodegradation and Bioconcentration of the Existing
Chemical Substances under the Chemical Substances Control Law, http://www.safe.nite.go.jp/english/db.html

3. S Dimitrov, T Pavlov, G Veith, O Mekenyan. SAR and QSAR
in Environ Res, 22, 2011, 699-718.

4. S Dimitrov, T Pavlov, N Dimitrova, D Georgieva, D Nedelcheva, A
Kesova, R Vasilev, O Mekenyan. SAR and QSAR in Environ Res, 22,
2011, 719-755.

5. S Dimitrov, G Dimitrova, T Pavlov, N Dimitrova, G Patlevisz, J
Niemela and O Mekenyan, J Chem Inf Model, 45, 2005, 839-849.

### CATALOGIC 301C

#### Model features

** **

*Click the images for a larger view*

** **

** **

**BOD, % **

** **

** **

**Biodegradation map **

**Quantity of metabolites**

** **

** **

** **

Model descriptions pdf