Literature DB >> 26053589

UVCB substances: methodology for structural description and application to fate and hazard assessment.

Sabcho D Dimitrov1, Denitsa G Georgieva1, Todor S Pavlov1, Yordan H Karakolev1, Panagiotis G Karamertzanis2, Mike Rasenberg2, Ovanes G Mekenyan1.   

Abstract

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.
© 2015 SETAC.

Keywords:  G SMILES; Hazard/risk assessment; Mixture, UVCBs; Representative constituent; Structure-activity relationships (SARs)

Mesh:

Substances:

Year:  2015        PMID: 26053589     DOI: 10.1002/etc.3100

Source DB:  PubMed          Journal:  Environ Toxicol Chem        ISSN: 0730-7268            Impact factor:   3.742


  5 in total

1.  Grouping of Petroleum Substances as Example UVCBs by Ion Mobility-Mass Spectrometry to Enable Chemical Composition-Based Read-Across.

Authors:  Fabian A Grimm; William K Russell; Yu-Syuan Luo; Yasuhiro Iwata; Weihsueh A Chiu; Tim Roy; Peter J Boogaard; Hans B Ketelslegers; Ivan Rusyn
Journal:  Environ Sci Technol       Date:  2017-05-26       Impact factor: 9.028

2.  In Vitro Bioavailability of the Hydrocarbon Fractions of Dimethyl Sulfoxide Extracts of Petroleum Substances.

Authors:  Yu-Syuan Luo; Kyle C Ferguson; Ivan Rusyn; Weihsueh A Chiu
Journal:  Toxicol Sci       Date:  2020-04-01       Impact factor: 4.849

3.  Grouping of complex substances using analytical chemistry data: A framework for quantitative evaluation and visualization.

Authors:  Melis Onel; Burcu Beykal; Kyle Ferguson; Weihsueh A Chiu; Thomas J McDonald; Lan Zhou; John S House; Fred A Wright; David A Sheen; Ivan Rusyn; Efstratios N Pistikopoulos
Journal:  PLoS One       Date:  2019-10-10       Impact factor: 3.240

Review 4.  Improving the Environmental Risk Assessment of Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials.

Authors:  Daniel Salvito; Marc Fernandez; Karen Jenner; Delina Y Lyon; Joop de Knecht; Philipp Mayer; Matthew MacLeod; Karen Eisenreich; Pim Leonards; Romanas Cesnaitis; Miriam León-Paumen; Michelle Embry; Sandrine E Déglin
Journal:  Environ Toxicol Chem       Date:  2020-09-16       Impact factor: 3.742

5.  Grouping of UVCB substances with new approach methodologies (NAMs) data.

Authors:  John S House; Fabian A Grimm; William D Klaren; Abigail Dalzell; Srikeerthana Kuchi; Shu-Dong Zhang; Klaus Lenz; Peter J Boogaard; Hans B Ketelslegers; Timothy W Gant; Fred A Wright; Ivan Rusyn
Journal:  ALTEX       Date:  2020-10-09       Impact factor: 6.043

  5 in total

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