Literature DB >> 11406306

A review of structure-based biodegradation estimation methods.

J W Raymond1, T N Rogers, D R Shonnard, A A Kline.   

Abstract

Biodegradation, being the principal abatement process in the environment, is the most important parameter influencing the toxicity, persistence, and ultimate fate in aquatic and terrestrial ecosystems. Biodegradation of an organic chemical in natural systems may be classified as primary (alteration of molecular integrity), ultimate (complete mineralization; i.e. conversion to inorganic compounds and/or normal metabolic processes), or acceptable (toxicity ameliorated). Most of the biodegradation correlations presented in the literature focus on the characterization of primary or ultimate, aerobic degradation. The US Environmental Protection Agency (USEPA) is charged with determining the risks associated with the thousands of chemicals employed in commerce, an effort that is being facilitated through much research aimed at reliable structure-activity relationships (SAR) to predict biodegradation of chemicals in natural systems. To this end, models are needed to understand the mechanisms of biodegradation, to classify chemicals according to relative biodegradability, and to develop reliable biodegradation estimation methods for new chemicals. Frequently, published correlations associating molecular structure to biodegradation will attempt to quantify the degradability of a limited set of homologous chemicals. These correlations have been dubbed quantitative structure biodegradability relationships (QSBRs). More scarce and valuable to researchers are those models that predict the biodegradability of compounds possessing a wide variety of chemical structures. The latter may use any of several techniques and molecular descriptors to correlate biodegradability: QSBRs, pattern recognition, discriminant analysis, and principle component analysis (PCA), to name several. Generally, models either predict the propensity of a chemical to biodegrade using Boolean-type logic (i.e. whether a chemical will "readily biodegrade" or not), or else they quantify the degree of biodegradation by providing information such as rate constants. Such quantitative predictions of biodegradability come in a diversity of parameters, including half-lives, various biodegradation rates and rates constants, theoretical oxygen demand (ThOD), biological oxygen demand (BOD), and others. In this paper, after describing the advantages and disadvantages of the various biodegradation estimation methods found in the literature, the best models are compared to conclude which provide the greatest utility for determining the biodegradability of chemicals with widely varying structures. The group contribution technique presented by Boethling et al. [Environmen. Sci. Technol. 28 (1994) 459] appears to be the most advantageous for use in broad screening for tendency to biodegrade. The model is simple to use, calculating a probability of biodegrading ranging from 0 (none) to 1 (certain), and has proven to be accurate for a wide range of chemical structures, as established by the large, high-quality data set (BIODEG evaluated biodegradation database, Syracuse Research Corporation, Merrill Lane, Syracuse, NY 13210) used to develop this correlation. The authors, therefore, recommend the method of Boethling et al. [Environ. Sci. Technol. 28 (1994) 459] for the initial screening of chemicals to aid in determining whether additional information is necessary to establish relative biodegradability. For readers with applications requiring more quantitative results, such as biodegradation rate constants, enough model details are presented in this paper to allow the reader to pick a suitable correlation, although the reader is cautioned to consult the original, primary reference for the complete method description, equations, and limitations.

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Year:  2001        PMID: 11406306     DOI: 10.1016/s0304-3894(01)00207-2

Source DB:  PubMed          Journal:  J Hazard Mater        ISSN: 0304-3894            Impact factor:   10.588


  10 in total

Review 1.  Evaluation of artificial intelligence based models for chemical biodegradability prediction.

Authors:  James R Baker; Dragan Gamberger; James R Mihelcic; Aleksandar Sabljić
Journal:  Molecules       Date:  2004-12-31       Impact factor: 4.411

2.  Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review.

Authors:  Laure Mamy; Dominique Patureau; Enrique Barriuso; Carole Bedos; Fabienne Bessac; Xavier Louchart; Fabrice Martin-Laurent; Cecile Miege; Pierre Benoit
Journal:  Crit Rev Environ Sci Technol       Date:  2015-06-18       Impact factor: 12.561

3.  From laboratory to environmental conditions: a new approach for chemical's biodegradability assessment.

Authors:  Brillet François; Maul Armand; Durand Marie-José; Gérald Thouand
Journal:  Environ Sci Pollut Res Int       Date:  2016-06-16       Impact factor: 4.223

Review 4.  Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances.

Authors:  Mark T D Cronin; John D Walker; Joanna S Jaworska; Michael H I Comber; Christopher D Watts; Andrew P Worth
Journal:  Environ Health Perspect       Date:  2003-08       Impact factor: 9.031

Review 5.  Peroxidase(s) in environment protection.

Authors:  Neelam Bansal; Shamsher S Kanwar
Journal:  ScientificWorldJournal       Date:  2013-12-24

Review 6.  In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts.

Authors:  Hongbin Yang; Lixia Sun; Weihua Li; Guixia Liu; Yun Tang
Journal:  Front Chem       Date:  2018-02-20       Impact factor: 5.221

7.  Development and Long-Term Stability of a Novel Microbial Fuel Cell BOD Sensor with MnO₂ Catalyst.

Authors:  Shailesh Kharkwal; Yi Chao Tan; Min Lu; How Yong Ng
Journal:  Int J Mol Sci       Date:  2017-01-28       Impact factor: 5.923

8.  Dissipation Behavior of Three Pesticides in Prickly Pear (Opuntia ficus-indica (L.) Mill.) Pads in Morelos, Mexico.

Authors:  Irene Iliana Ramírez-Bustos; Hugo Saldarriaga-Noreña; Ernesto Fernández-Herrera; Porfirio Juárez-López; Iran Alia-Tejacal; Dagoberto Guillén-Sánchez; Ismael Rivera-León; Víctor López-Martínez
Journal:  Int J Environ Res Public Health       Date:  2019-08-15       Impact factor: 3.390

9.  Biodegradation of Organophosphorus Compounds Predicted by Enzymatic Process Using Molecular Modelling and Observed in Soil Samples Through Analytical Techniques and Microbiological Analysis: A Comparison.

Authors:  Monique Cardozo; Joyce S F D de Almeida; Samir F de A Cavalcante; Jacqueline R S Salgado; Arlan S Gonçalves; Tanos C C França; Kamil Kuca; Humberto R Bizzo
Journal:  Molecules       Date:  2019-12-23       Impact factor: 4.411

Review 10.  A Review of Recent Advances towards the Development of (Quantitative) Structure-Activity Relationships for Metallic Nanomaterials.

Authors:  Guangchao Chen; Martina G Vijver; Yinlong Xiao; Willie J G M Peijnenburg
Journal:  Materials (Basel)       Date:  2017-08-31       Impact factor: 3.623

  10 in total

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