New public QSAR model for carcinogenicity

Abstract

BackgroundOne of the main goals of the new chemical regulation REACH (Registration, Evaluation and Authorization of Chemicals) is to fulfill the gaps in data concerned with properties of chemicals affecting the human health. (Q)SAR models are accepted as a suitable source of information. The EU funded CAESAR project aimed to develop models for prediction of 5 endpoints for regulatory purposes. Carcinogenicity is one of the endpoints under consideration.ResultsModels for prediction of carcinogenic potency according to specific requirements of Chemical regulation were developed. The dataset of 805 non-congeneric chemicals extracted from Carcinogenic Potency Database (CPDBAS) was used. Counter Propagation Artificial Neural Network (CP ANN) algorithm was implemented. In the article two alternative models for prediction carcinogenicity are described. The first model employed eight MDL descriptors (model A) and the second one twelve Dragon descriptors (model B). CAESAR's models have been assessed according to the OECD principles for the validation of QSAR. For the model validity we used a wide series of statistical checks. Models A and B yielded accuracy of training set (644 compounds) equal to 91% and 89% correspondingly; the accuracy of the test set (161 compounds) was 73% and 69%, while the specificity was 69% and 61%, respectively. Sensitivity in both cases was equal to 75%. The accuracy of the leave 20% out cross validation for the training set of models A and B was equal to 66% and 62% respectively. To verify if the models perform correctly on new compounds the external validation was carried out. The external test set was composed of 738 compounds. We obtained accuracy of external validation equal to 61.4% and 60.0%, sensitivity 64.0% and 61.8% and specificity equal to 58.9% and 58.4% respectively for models A and B.ConclusionCarcinogenicity is a particularly important endpoint and it is expected that QSAR models will not replace the human experts opinions and conventional methods. However, we believe that combination of several methods will provide useful support to the overall evaluation of carcinogenicity. In present paper models for classification of carcinogenic compounds using MDL and Dragon descriptors were developed. Models could be used to set priorities among chemicals for further testing. The models at the CAESAR site were implemented in java and are publicly accessible.

Rodent Carcinogenicity Dataset

“…External validation of models was performed using external validation set of 738 chemicals different from those in our dataset of 805 compounds described earlier [4]. ChemFinder Ultra 10.0 soware was used [18].…”

“…It combines the Genetic Algorithm (GA) concepts and a stepwise regression [26]. In this way, the descriptors' space was reduced from 254 to 8 MDL descriptors [4]. us, we used topological descriptors, including atom-type and group-type, E-State and hydrogen E-state indices, molecular connectivity, Chi indices, and topological polarity to obtain the molecular structure information, which is correlated with carcinogenic potency.…”

“…Models for prediction of carcinogenicity using rodent carcinogenicity database were described [4][5][6][7][8]. State of the art and perspectives of predictive models for carcinogenicity are discussed in the paper by Benfenati et al [9].…”

International regulatory needs for development ofan IATA for non-genotoxic carcinogenic chemical substances

“…Multiple computational models have been established for identifying a chemical's genotoxic potential, triggered over 25 years ago by the publication of the Ashby-Tennant alerts in 1991 (Ashby and Tennant, 1991), followed by software such as VEGA (Fjodorova et al, 2010), ToxTree (Patlewicz et al, 2008), the OECD QSAR Toolbox (OECD, 2015c) and LAZAR (Maunz et al, 2013;Lo Piparo et al, 2014), which are all available free of charge. Other, (semi)commercial, models include MultiCASE 5 , TOPKAT 6 , HazardExpert 7 , LeadScope 8 and DEREK-Nexus 3 .…”

Prediction of mutagenicity, carcinogenicity, developmental toxicity, and skin sensitisation with Caesar program for a set of conazoles

“…Details of the CAESAR carcinogenicity model are given in reference (19). The model was built on a set of 805 non-congeneric compounds extracted from the Carcinogenic Potency Database (CPDBAS).…”