In Silico Assessment of Chemical Biodegradability

Biodegradation is the principal environmental dissipation
process.
Due to a lack of comprehensive experimental data, high study cost
and time-consuming, in silico approaches for assessing the biodegradable
profiles of chemicals are encouraged and is an active current research
topic. Here we developed in silico methods to estimate chemical biodegradability
in the environment. At first 1440 diverse compounds tested under the
Japanese Ministry of International Trade and Industry (MITI) protocol
were used. Four different methods, namely support vector machine, k-nearest neighbor, naïve Bayes, and C4.5 decision
tree, were used to build the combinatorial classification probability
models of ready versus not ready biodegradability using physicochemical
descriptors and fingerprints separately. The overall predictive accuracies
of the best models were more than 80% for the external test set of
164 diverse compounds. Some privileged substructures were further
identified for ready or not ready biodegradable chemicals by combining
information gain and substructure fragment analysis. Moreover, 27
new predicted chemicals were selected for experimental assay through
the Japanese MITI test protocols, which validated that all 27 compounds
were predicted correctly. The predictive accuracies of our models
outperform the commonly used software of the EPI Suite. Our study
provided critical tools for early assessment of biodegradability of
new organic chemicals in environmental hazard assessment.