Environmental Science and Pollution Research

, Volume 21, Issue 4, pp 2955–2965 | Cite as

Modeling bioconcentration factor (BCF) using mechanistically interpretable descriptors computed from open source tool “PaDEL-Descriptor”

Research Article

Abstract

Predictive regression-based models for bioconcentration factor (BCF) have been developed using mechanistically interpretable descriptors computed from open source tool PaDEL-Descriptor (http://padel.nus.edu.sg/software/padeldescriptor/). A data set of 522 diverse chemicals has been used for this modeling study, and extended topochemical atom (ETA) indices developed by the present authors’ group were chosen as the descriptors. Due to the importance of lipohilicity in modeling BCF, XLogP (computed partition coefficient) was also tried as an additional descriptor. Genetic function approximation followed by multiple linear regression algorithm was applied to select descriptors, and subsequent partial least squares analyses were performed to establish mathematical equations for BCF prediction. The model generated from only ETA indices shows importance of seven descriptors in model development, while the model generated from ETA descriptors along with XlogP shows importance of four descriptors in model development. In general, BCF depends on lipophilicity, presence of heteroatoms, presence of halogens, fused ring system, hydrogen bonding groups, etc. The developed models show excellent statistical qualities and predictive ability. The developed models were used also for prediction of an external data set available from the literature, and good quality of predictions (R2pred = 0.812 and 0.826) was demonstrated. Thus, BCF can be predicted using ETA and XlogP descriptors calculated from open source PaDEL-Descriptor software in the context of aquatic chemical toxicity management.

Keywords

QSAR BCF PaDEL-Descriptor Mathematical modeling ETA XlogP 

Supplementary material

11356_2013_2247_MOESM1_ESM.doc (56 kb)
ESM 1(DOC 56 kb)
11356_2013_2247_MOESM2_ESM.doc (18.6 mb)
Table S1(DOC 19037 kb)
11356_2013_2247_MOESM3_ESM.xls (1.5 mb)
Table S2(XLS 1545 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Drug Theoretics and Cheminformatics Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical TechnologyJadavpur UniversityKolkataIndia

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