Biodegradability, QSAR

Cowan, C.E., T.W. Federle, R.J. Larson, and T.C.J. Feijtel. 1996. Impact of biodegradation test methods on the development and applicability of biodegradation QSARs. SAR QSAR Environ. Res. 5 37-49. 

Pavan, M. and Worth, A.P. (2008) Review of estimation models for biodegradation. QSAR Comb. Sci., 27, 32-40. 

In summary, optimization of the environmental profile of APIs starts from a new or already known lead structure. During the pharmaceutical optimization process, which involves systematic variation of parts of the molecule, the biodegradability of the resulting structures is also monitored. Candidates that possess both better pharmaceutical and environmental properties advance to the next round of optimization. With the help of modem in silico methods (e.g., QSARs, expert systems) this can be done systematically, quickly, and cheaply, without the need to synthesize all the molecules of interest [132]. In a similar way, we were able to improve the biodegradability of a new lead structure by systematically modifying the lead molecule while retaining the necessary low octanol-water partition coefficient. As... 

Extensive investigations have shown that molecular structure quantitatively affects the biodegradability of a compound. Table 3.3 summarizes quantitative structure-activity relationship (QSAR) studies in biodegradability. 

Mudder s (1981) work, which was a pioneer effort in the area of environmental QSARs, was based on real biodegradation data and used 25 molecular descriptors as described by Hansch and Leo. 

Roberts, D.W., Application of QSAR to biodegradation of linear alkylbenzene sul-phonate (LAS) isomers and homologues, Sci. Total Environ., 109/110, 301-306, 1991. 

Dearden, J.C. and R.M. Nicholson. 1987. Correlation of biodegradability with atomic charge difference and superdelocalizability. In K.L.E. Kaiser, ed., QSAR Environmental Toxicology - II, pp. 83-89. Reidel, Dordrecht, The Netherlands. 

Devillers, J. 1993. Neural modelling of the biodegradability of benzene derivatives. SAR and QSAR in Environ. Res. 1 161-167. 

Punch, W.F., L.J. Forney, A. Patton, K. Wright, P. Masscheleyn, and R.J. Larson. 1996. BESS, A computerized system for predicting the biodegradation potential of new and existing chemicals. 7th International Workshop on QSARs in Environmental Science. June 24—28, Elsinore, Denmark. 

Walker, J.D., Knaebel, D., Mayo, K., Tunkel, J. and Gray, D.A. (2004) Use of QSARs to promote more cost-effective use of chemical monitoring resources. 1. Screening industrial chemicals and pesticides, direct food additives, indirect food additives and pharmaceuticals for biodegradation, bioconcentration and aquatic toxicity potential, Water Quality Research Journal of Canada 39, 35-39. 

The fundamentals and background of QSAR modeling and predictions have been detailed previously (e.g., Nendza, 1998). Regarding the different physicochemical bases of transformation processes, different approaches to their estimation have been taken. The intention should always be to use process-related models. Thermodynamic principles underlie the relationships between abiotic one-step reaction rates and physicochemical descriptors of the structures. Mechanistic modeling is much more intricate for multistep biodegradations, where the (varying) rate-limiting... 

To test the applicability of published QSARs for biodegradation, several validation exercises have been conducted. The most comprehensive validation exercise (Degner, 1991 Organization for... 

From the literature, 64 regression models for specific compound classes were retrieved, of which 35 could be tested with the MITI-I data, but only 7 QSARs were successfully validated. These models were derived with four to eight homologous substances and, because of their specificity, they are suitable for application to corresponding substances only. The number of validated QSAR models for specific compound classes is too low to make predictions solely on this basis in the MITI-I data set they were applicable for estimating the biodegradability of only 3% of the chemicals. 

Dimitrov, S., Breton, R., MacDonald, D., Walker, J.D., and Mekenyan, O., Quantitative prediction of biodegradability, metabolite distribution and toxicity of stable metabolites, SAR QSAR Environ. Res., 13, 445 155, 2002. 

Parsons, J.R. and Govers, H.A.J., Quantitative-structure activity relationships (QSARs) for biodegradation, Ecotoxicology Environ. Saf, 19, 212-227, 1990. 

Degner, P., Nendza, M., and Klein, W., Predictive QSAR models for estimating biodegradation of aromatic compounds, Sci. Total Environ., 109, 253-259, 1991. 

Okey, R.W. and Stensel, H.D., A QSAR-based biodegradability model a QSBR, Water Res., 30, 2206-2214, 1996. 

Calculation of log Krjw — recommended methods and limitations Calculation of soil and sediment sorption — recommended QSARs Calculation of Henry s law constant — recommended QSARs Calculation of bioconcentration factor (aquatic and terrestrial organisms) — recommended QSARs Calculation of biodegradation — recommended QSARs Calculation of photolysis in air and water, hydrolysis — recommended QSARs No (Q)SARs recommended... 

The TGD provides recommendations for the use of QSARs to predict long term toxicity to fish (no observed effect concentration [NOEC], 28 days) and to Daphnia (NOEC, 21 days). In particular QSARs are provided for chemicals acting by non-polar narcosis and polar narcosis mechanisms of action. No QSARs have been recommended for substances that act by more specific modes of action. For persistence, the TGD recommends two of the SRC BIOWIN models, namely the BIOWIN2 nonlinear model and the BIOWIN3 survey model for ultimate biodegradation. The exact cutoff points for these models have been calibrated on the basis of the model score for 1,2,4-trichlorobenzene — a substance that is known to be relatively persistent under environmental... 

Structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs), referred to collectively as QSARs, can be used for the prediction of physicochemical properties, environmental fate parameters (e.g., accumulation and biodegradation), human health effects, and ecotoxicological effects. A SAR is a (qualitative) association between a chemical substructure and the potential of a chemical containing the substructure to exhibit a certain physical or biological effect. A QS AR is a mathematical model that relates a quantitative measure of chemical structure (e.g., a physicochemical property) to a physical property or to a biological effect (e.g., a toxicological endpoint). 

Willie J. G. M. Peijnenburg and Jiri Damborsky, Biodegradability Prediction. Proceedings of the NATO Advanced Research Workshop on QSAR Biodegradation II QSARs for Biotransformation and Biodegradation, Luhacovice, Czech Republic, 2-3 May 1996, in NATO ASI Series, Ser. 2, Vol. 23, Kluwer, Dordrecht, 1996. 

Posthumus R, Traas TP, Peijnenburg W, Hulzebos EM. 2005. External validation of EPIWIN biodegradation models. SAR QSAR Environ Res 16 135-148. 

Nirmalakhandan, N.N., Speece, R.E. (1988b) QSAR model for predicting Henry s constant. Environ. Sci. Technol. 22(11), 1349-1357. Novak, J.T., Goldsmith, C.D., Benoit, R.E., O Brien, J.H. (1985) Biodegradation of methanol and tertiary butyl alcohol in subsurface systems. Water Sci. Technol. 17, 71-85. 

While experimentally derived test data are preferred, where no experimental data are available, validated Quantitative Structure Activity Relationships (QSARs) for aquatic toxicity and log Kqw may be used in the classification process. Such validated QSARs may be used without modification to the agreed criteria, if restricted to chemicals for which their mode of action and applicability are well characterized. Reliable calculated toxicity and log Kow values should be valuable in the safety net context. QSARs for predicting ready biodegradation are not yet sufficiently accurate to predict rapid degradation. 

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