Estimation of microbial reductive transformation rates for chlorinated benzenes and phenols using a quantitative structure–activity relationship approach

Abstract

A set of literature data was used to derive several quantitative structure-activity relationships (QSARs) to predict the rate constants for the microbial reductive dehalogenation of chlorinated aromatics. Dechlorination rate constants for 25 chloroaromatics were corrected for the effects of hydrophobic partitioning and adjusted for the observed distribution of product species. A number of physicochemical properties and molecular parameters were considered for inclusion in the QSARs. Multivariate statistical analyses were used to select the optimal set of descriptors to minimize multicollinearity between the descriptors, as well as to minimize the p-value of the regression coefficients. The final QSAR included four descriptors: The logarithm of the octanol-water partition coefficient (Kow), the summation of the Hammett sigma constants, and the sigma induction constants in the ortho and meta positions relative to the transformation reaction center. The predictive ability of this QSAR was evaluated using 24 site-specific rate constants that were measured in five separate studies and were not used to derive the expression. The peer-reviewed literature was screened carefully to ensure that all rate constant data were representative of environmentally relevant conditions.

A universal free energy relationship for both hard and soft radical addition in water

“…[ 31,32,73,74 ] Typical measurement variability for solvent partitioning is a factor ~2, [ 75 ] indicative of variability in experimental results for kinetics using different co‐solvents. Adding 10% apolar solvent (octanol) to a ‘hydrophobic’ compound (e.g., K OW > 10) can influence its rate by >50% ( [ 76 ] ) by affecting the compounds hydration sphere. Therefore, the 5% solvent exclusion criterion (SI3) is not conservative.…”

Bioconcentration of Organotin Cations during Molting Inhibits Heterocypris incongruens Growth

“…We converted sediment (sed) concentrations to water (aq) concentrations via phase partitioning , wherein 0.2 represents the sediment to test volume ratio (1:5). Considering that the test medium is prescribed as moderately hard, we took the value for the solids-to-water partitioning coefficient K SW, local for NH 4 + /NH 3 and H 2 PO 4 – /HPO 4 2– to be 6.0(±3.0) − and 100 L/kg, , respectively, for field concentrations − representable for Flanders ,, and pH = 7.4.…”

“…Since those sediments are applied to the (aqueous) bioassay, we estimate in situ water concentrations from the total in sediment. We converted sediment (sed) concentrations to water (aq) concentrations via phase partitioning 60,61…”

Transition-state rate theory sheds light on ‘black-box’ biodegradation algorithms

“…3,22,[36][37][38] We can expect that after accounting for many such test-specific phenomena, the 'intrinsic biodegradability' of chemicals becomes apparent. 23,27,[39][40][41][42] Such an 'intrinsic biodegradation rate' might not entail information on microbial processes: adaptation, active transport, 43,44 the involvement of medium ( pH; organic carbon), nutrients, 45 and back-transformation 46 (i.e. the factors are either non-existent, or constant for all chemicals).…”