UVCB substances: Methodology for structural description and application to fate and hazard assessment. (8th October 2015)

• Record Type: Journal Article
• Authors: Dimitrov, Sabcho D.; Georgieva, Denitsa G.; Pavlov, Todor S.; Karakolev, Yordan H.; Karamertzanis, Panagiotis G.; Rasenberg, Mike; Mekenyan, Ovanes G.
• Is Part Of: Environmental toxicology and chemistry. Volume 34:Number 11(2015:Nov.)
• Page Start: 2450
• Page End: 2462
• Publication Date: 2015-10-08
• Subjects: Pollution -- Environmental aspects -- Periodicals; Environmental chemistry -- Periodicals; 615.902
• DOI: 10.1002/etc.3100
• Languages: English
• ISSNs: 0730-7268

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <sec id="etc3100-sec-0001" sec-type="section"> <p>Substances of unknown or variable composition, complex reaction products, or biological materials (UVCBs) have been conventionally described in generic terms. Commonly used substance identifiers are generic names of chemical classes, generic structural formulas, reaction steps, physical–chemical properties, or spectral data. Lack of well‐defined structural information has significantly restricted in silico fate and hazard assessment of UVCB substances. A methodology for the structural description of UVCB substances has been developed that allows use of known identifiers for coding, generation, and selection of representative constituents. The developed formats, Generic Simplified Molecular‐Input Line‐Entry System (G SMILES) and Generic Graph (G Graph), address the need to code, generate, and select representative UVCB constituents; G SMILES is a SMILES‐based single line notation coding fixed and variable structural features of UVCBs, whereas G Graph is based on a workflow paradigm that allows generation of constituents coded in G SMILES and end point–specific or nonspecific selection of representative constituents. Structural description of UVCB substances as afforded by the developed methodology is essential for in silico fate and hazard assessment. Data gap filling approaches such as read‐across, trend analysis, or quantitative structure–activity relationship modeling can be applied to the generated constituents, and the results can be used to assess the substance as a whole. The methodology also advances the application of category‐based data gap filling approaches to UVCB substances. <italic>Environ Toxicol Chem</italic> 2015;34:2450–2462. © 2015 SETAC</p> </sec> </abstract>