quantitative structure-activity relationships for biodegradation

ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 19,2 12-227 (1990)

Quantitative Structure-Activity Relationships for Biodegradation

J. R. PARSONS’ AND H. A. J. GOVERS

Laboratory ofEnvironmental and Toxicological Chemistry, University ofAmsterdam, Nieuwe Achtergracht 166. 1018 WVAmsterdam, The Netherlands

Received November 14. 1988

Quantitative structure-activity relationships (QSARs) between biodegradation rates of organic compounds and chemical structure parameters are reviewed. Although a number of such relationships have been developed, they in general only apply to restricted ranges ofcompounds, limiting their value as predictors of biodegradation rates. For many of these classes of chemicals relationships have been reported with different structural descriptors, varying from macroscopic physical properties to molecular structure parameters. More information on the mechanism and rate-determining steps of biodegradation, which can lead to a better-founded choice of descriptors, and more biodegradation rate data are required to further develop QSARs for biodegradation. 0 1990 Academic Press. Inc.

INTRODUCTION

Quantitative structure-activity relationships (QSARs) have become well estab- lished tools in environmental toxicology and chemistry (Nirmalakhandan and Speece, 1988). There has recently been increasing interest in the application of such relationships to the study of biodegradation. Biodegradation (metabolism by microorganisms) is one of the most important processes determining the fate of organic chemicals in the environment (Alexander, 198 1). Hence, biodegradation rates play an important role in the estimation of the environmental fate and hazard of chemicals. Quantitative relationships between the structure and biodegradability of chemicals should therefore assist the prediction of their biodegradation rates. Alternatively, such relationships may be used in mechanistic studies of the processes which determine biodegradation rates, for example by comparing correlations of biodegradation rates with different molecular descriptors.

Rates of biodegradation are a function of the rates of a series of processes. Corre- lations between biodegradation rates and structural parameters will be facilitated if one of these processes is rate determining. In general, these processes will be of two types. Biodegradation rates may be determined by transport rates, for example, rates of uptake by microbial cells or rates of transport within the cell to the relevant enzymes. Alternatively, biodegradation rates may be determined by the binding of compounds to enzymes or by the rates at which they undergo enzymatic transformation.

The application of quantitative structure-activity relationships to biodegradation kinetics is surveyed here, with particular attention to the general applicability of such relationships to predictions of biodegradation rates and to any information they may give on the mechanisms that determine these rates.

i To whom correspondence should be addressed.

0147-6513190 $3.00 Copyright Q 1990 by Academic Press, Inc. All rights of reproduction in any form reserved.

212

QSARs FOR BIODEGRADATION 213

BIODEGRADATION KINETICS

Biodegradation, in common with most biological reactions, follows Michaelis- Menten (saturation) kinetics of the form

-dS v,,, SB O=dt= K,+s’ (1)

where v is the rate of reaction at time t, vmax the maximum rate of reaction, S the substrate concentration, B the bacteria or biomass concentration, and KM the half- saturation constant for the reaction, i.e., the concentration at which v = iv,,, (Lehn- inger, 1970). As a special case for a compound which is utilized as a growth substrate, the rate of degradation can also be related to the growth rate in the Monod equation (Schlegel, 198 1).

Equation 1 simplifies to Eq. 2 if the substrate concentration is much higher than KM:

v=v B max > (2)

i.e., the rate of substrate disappearance is zero order with substrate concentration and first-order with biomass concentration.

If the substrate concentration is much lower than KM, Eq. 1 simplifies to

%m, SB v = ~ = ,&SB;

KM (3)

i.e., the rate of degradation of the substrate is first-order with respect to both substrate concentration and biomass concentration, and k,, is a second-order rate constant. If B is a constant, for example in a chemostat culture or in a nongrowing cell suspension, pseudo-first-order kinetics apply:

-ds = k&S. ‘= dt (4)

Under these conditions, the decrease in substrate concentration will be of the form

St = &e&b’, (5)

where S, and S, are the substrate concentrations initially added and at time t, respec- tively.

These simple models seem to describe the biodegradation of organic compounds quite well in both laboratory cultures and natural systems. For example, models based on Michaelis-Menten and Monod kinetics gave good descriptions of the biodegradation of m-cresol, chlorobenzene, nitrilotriacetic acid (NTA), and 1,2,4&-i- chlorobenzene in fresh, brackish, and marine water samples (Pfaender and Bartholo- mew, 1982), and benzoate, glucose, benzylamine, phenol, and p-nitrophenol in sew- age, pure cultures, and lake water (Simkins and Alexander, 1984; Simkins and Alexander, 1985; Jones and Alexander, 1986).

Paris et al. found that the degradation of the butoxyethyl ester of 2,4-dichlorophen- oxyacetic acid, malathion, and chlorpropan in natural water samples from a total of 40 sites followed first-order kinetics (Paris et al., 198 1). Division of the first-order rate constants by the concentrations of bacteria in each water sample gave reproducible

214 PARSONS AND GOVERS

second-order degradation rate constants. The compounds used in this study are readily hydrolyzed by most bacteria in the environment. In general, however, only a part of a microbial population is able to degrade a chemical to which it is exposed, and first-order rate constants have to be divided by the concentration of active bacteria.

Thus, second-order or pseudo-first-order rate constants would normally be required as biodegradation rate parameters in quantitative structure-biodegradability relationships. However, there is a limited number of such data available, which has led some authors to use biochemical oxygen demand (BOD) data from the standard- ized tests for biodegradability. However, such tests are noted for their poor reproduc- ibility (Gerike and Fischer, 1979; Gerike and Fischer, 198 1; Blok et al., 1985) and are limited to compounds which microorganisms can utilize as growth substrates. Furthermore, the BOD does not describe the rate of metabolism of a chemical, but quantifies the total amount of organic material oxidized within a particular period.

QUANTITATIVE STRUCTURE-BIODEGRADABILITY RELATIONSHIPS

General Approach

It has been known for some time that certain structural features, such as branching of alkyl chains and electron-withdrawing substituents on aromatic rings, can reduce the biodegradability of organic compounds (Alexander, 198 1; Klecka, 1985). Cluster analysis and other statistical techniques have been applied to biodegradation data to identify the structural features which influence biodegradability (Niemi et al., 1987). However, so far this approach has only been applied to BOD data.

The most usual approach to quantitative structure-biodegradability relationships is to correlate biodegradation rate data with molecular descriptors such as electronic or structural parameters (QSARs in the strictest sense) or, alternatively, with macroscopic parameters such as physical properties of the chemicals (physical property- activity relationships, PARS). Which descriptor gives the best correlation depends on the mechanism of the biodegradation rate-determining step. The biodegradation rate of a compound may be determined by its rate of uptake and transport, by its binding to the active site of an enzyme, or by the rate at which it is transformed.

In the absence of a specific uptake mechanism, synthetic organic chemicals are probably transported into bacterial cells by passive diffusion through the lipid membrane. The permeability coefficient for diffusion is proportional to the lipid-water partition coefficient if the concentrations just within the membrane are related to those in the adjacent aqueous phases by this partition coefficient (Stein, 1986). Sim- ilar relationships are found between permeability coefficients and other parameters describing hydrophobicity, or lipophilicity, such as the octanol-water partition coefficient, Kd,Oa (Nikaido and Vaara, 1985; Stein, 1986). Therefore, if biodegradation rates are limited by the rates of uptake by diffusion through the cell envelope, one would expect to find correlations between biodegradation rate constants and macroscopic hydrophobic parameters such as octanol-water partition coefficients.

The enzyme-catalyzed transformation of a compound is preceded by its binding to the active site of the enzyme by the formation of hydrogen or covalent bonds (Alberts et al., 1983). The strength of this interaction is influenced by the electronic structure of the compound, as well as by steric effects on the fit of the compound on the active site. The reactivity of the bound compound will also be determined by its electronic and steric properties. Consequently, if enzyme binding or transformation


rates determine biodegradation rates, correlations would be expected between biodegradation rate constants and molecular factors influencing the binding or the reactivity of the chemicals, i.e., with steric or electronic parameters. However, it is not always possible to distinguish between these possibilities. For example, steric factors will not only influence the enzyme binding and reactivity, but also the hydrophobicity of a compound. The biodegradation rate parameters and the chemical structure parameters (descriptors) used so far in QSARs for biodegradation are summarized in Table 1.

Relationships between Biodegradation Rates and Macroscopic Parameters

As is generally the case for QSARs in environmental toxicology, the most com- monly used structural descriptors are macroscopic parameters that describe hydrophobicity, in particular octanol-water partition coefficients. Other macroscopic descriptors include abiotic reaction rate constants. Yonezawa and Urushigawa studied the relationships between the first-order biodegradation rate constants in activated sludge of aliphatic alcohols and their octanol-water partition coefficients (Yonezawa and Urushigawa, 1979) and those of di-n-alkyl phthalate esters and their reversed- phase HPLC retention times (Urushigawa and Yonezawa, 1979). Reversed-phase HPLC retention correlates quite well with partition between water and organic phases such as octanol and is sometimes used as an alternative hydrophobicity parameter (e.g., Braumann, 1986; Opperhuizen, 1987; de Voogd et al., 1988). In the first case, biodegradation rate constants decreased with increasing partition coefficients and then started to increase for alcohols with partition coefficients greater than ca. 100. These results were interpreted as indicating that uptake of these compounds by diffusion was the process determining their biodegradation rate. A similar interpretation was given to the rather different results obtained in the second study, showing a decrease in biodegradation rate for the most hydrophobic compound (Fig. 1). However, one would in general expect increasing hydrophobicity to lead to increasing uptake rates, and thus increasing biodegradation rates if uptake is the rate-determining step.

First-order biodegradation rate constants of 12 pesticides of various structures, determined in mixed microbial cultures, were correlated parabolically with their octanol-water partition coefficients (Fig. 2a) and linearly with their alkaline hydrolysis rate constants (Fig. 2b) (Kanazawa, 1987). However, these relationships had such poor correlation coefficients (r2 = 0.697 and 0.454, resp.) that their value is uncertain.

Second-order biodegradation rate constants of esters of carboxylic acids containing chlorinated aromatic groups have been correlated with both their second-order alkaline hydrolysis rate constants (Wolfe et al., 1980) and their octanol-water partition coefficients (Paris et al., 1984). In the latter study, a good correlation was found between log k,, and log Kd,oct for alkyl esters of 2,4-D (Eq. 6) but not for a series of ethyl esters of chlorinated phenoxyacetic acids (Eq. 7):

log k,, = (0.799 t- 0.098)log Kd,oct - (11.643 & 0.204) (n = 6; r2 = 0.944) (6)

log k,, = (0.135 + 0.082)log Kd,oct - (10.865 + 0.3 13) (n = 5; r2 = 0.473). (7)

These results demonstrate the strong dependence of such relationships on the structural class of the chemicals.

Banerjee et al. measured the relative second-order biodegradation rate constants (kb,J of chlorinated phenols, anisoles, and resorcinols in pure cultures and in sam-


TABLE 1

QUANTITATIVESTRUCTUREACTIVITYRELATIONSHIPSFORBIODEGRADATION

Compound. P.r.l..t.r. in WAR Fl.i.r.nc.

FM..* D..criptorb r2= II

kid.

Br.“cb.d .cid.

Br.nch.d .nd 1in..r =.Sid.

C.rboxylic acid.

C.rboxylic .cid.

Sub.tit”t.d b.nro.t..

Amino .cid.

Acid. .lld .lcohol.

Lin..r .lcohol.

Alcohol.

Alcohol.

Glysol.

Alicyclic k.ton., .nd .lcohol.

Alicyclic k.ton.. .nd alcohol.

Alicyclic k.ton.. .nd .lcohol.

*cyclic b*t.ml..

Acyclic Leton*.

Ald.hyd..

Ald.hyd..

T?*t.lV

Phth.1.t. ..t.r.

Phth.1.t. ..t.r.

Phth.1.t. ..t.r.

E-Aminob.n.o.t. ..t.r.

2.4-D ..t.r.

2.4-D ..t.r.

C.rb.m.t..

Eth.r.

hi"..

g-?.ub.t. .nilin..

g-.Sub.t. .nilin..

g-Sub.t. .nilin..

Bo.thlins. la.36

Bo.tblins. 1986

Bo.thlin~. 1088

D..rd.n .nd Richo1.m. 1986

D..rd.n .nd RIeho~.on, l987b

R.in.k. .nd Kn.ckmu... 1878

D..rd.n .nd “ish.l.on, 1986

Bo.thlin8. 1800

“.i.hn.v .t .I.. 19.37

Bo.tblin~. 1906

Ion...“. .nd “ru.hia.r.. 1979

D..rd.a .nd I(icbol.on. 1987b

“.,.hz,.v .t .l.. 1987

“.i.hn.v .t .l.. 1987

“.i.hn.v .t .l.. 1987

“.i.hn.v .t .l.. 1987

“.i.hn.v .t .l.. 1987

D..rd.n .nd Hicho1.m. 1986

D..rd.n .nd Ilicho1.m. 1987b

D..rd.n .nd “ishol..“. 1987b

“ru.hi8.r. .nd Yen...“.. 1979

Bo.thlins. 1986

no1i. .t .l., 19.50

p.r.cIn. .t .l.. 1987

p.ri. .t .l., l98&

Bo.thlin&. 1986

Bo.thlins. 1986

Bo.thlin&. 1906

D..rd.n .nd RIcho1.m. 1986

pitt.r, 1985

Pitt.r, ma5

Pitt.=, 19.35

ples of natural waters (Banerjee et al., 1984). The data showed a trend to decreasing biodegradation rate constants with increasing octanol-water partition coefficients (Fig. 3). This relationship between these rate constants and octanol-water partition

QSARs FOR BIODEGRADATION

TABLE I-Continued

217

D..rd.n and “iebolson. 1887b

K.n.r.r., 1887

K.“.r.r., 1667

Wolf. .t al.. 1660

coefficients was explained in terms of a kinetic model for biodegradation where uptake of compounds by bacteria is the rate-determining process. The model includes terms for sorption of compounds to the cell wall and uptake by diffusion through both hydrophilic pores and lipid layers. Banetjee et al. considered that rate constants for diffusion through the lipid layers would be inversely proportional to octanol- water partition coefficients. In a comment on this paper, Beltrame et al. proposed

218 PARSONS AND COVERS

-3.0

‘i E.

;n

B -3.5

-4D 0.5 log Rt (mid

FIG. 1. Correlation of first-order biodegradation rate constants (k)b) with reversed-phase HPLC retention times (R,) for di-n-alkyl phthalates (Urushigawa and Yonezawa, 1979).

that decreasing reactivity of the enzyme-chlorophenol complexes with increasing log Kd,OCt may have been responsible for the observed trend in biodegradation rates (Bel- trame et al., 1985).

Five-day BOD values of 17 alcohols and 11 ketones, expressed as log(% theoretical oxygen demand, %ThOD), gave different relationships when plotted against log Kd,& (Vaishnav et al., 1987). For the alcohols, log(%ThOD) remained constant with increasing log Kd,oct until a value of ca. 4; for the more hydrophobic compounds log(%ThOD) decreased with increasing log K d,oct. In contrast, the ketones gave a parabolic relationship between log(%ThOD) and log Kd,oct, with a maximum log(%ThOD) at log Kd,oct ca. 1. Similar treatment by Vaishnav et al. of the data reported by Pitter for a series of alicyclic compounds (Pitter, 1976) gave results similar to those for the alcohols. The results for the alcohols and the alicyclic compounds were interpreted by these authors in terms of the uptake rate-limited model of Ban- erjee et al. described above. However, no explanation was proposed for the different relationship obtained for the ketones.

The above relationships between biodegradation rate and hydrophobicity were taken as indicating that uptake of the compounds into the bacterial cells was the rate- determining step. However, there were differences in the actual relationships found for different classes of compounds. Since there are no independent data on the uptake kinetics of these chemicals or on their membrane permeation, these conclusions can- not be verified. In general, the rates of diffusion of organic compounds through lipid membranes increase with increasing hydrophobicity and decrease with increasing size (see above) (Stein, 1986).


log Kd,oct

log koH (h-l1

FIG. 2. Relationship between log kL and (a) log octanol-water partition coefficients (log Z&J and (b) log alkaline hydrolysis rate constants (log &,) for I2 pesticides: (1) propoxur, (2) carbaryl, (3) malathion, (4) diazinon; (5) BPMC, (6) fenitrothion. (7) thiobencarb, (8) chlornitrofen. (9) isoprothiolane, (10) fenval- erate, (11) cartap, and ( 12) oxadiazon (Kanazawa, 1987).

A class of compounds of which the membrane permeation has been studied is that of the alkyl esters of p-aminobenzoic acid. These esters were used by Flynn and Yalkowsky to develop a model for the diffusion of nonpolar compounds across a barrier consisting of a lipid membrane surrounded on each side by aqueous diffusion layers (Flynn and Yalkowsky, 1972). The rates of diffusion of the esters increased with increasing hydrophobicity (expressed as hexane-water partition coefficients) until a limiting value was reached. For the most hydrophobic compounds transport in the unstirred aqueous diffusion layers on each side of the membrane was the rate-determining step in the whole diffusion process; consequently diffusion rates of such compounds were independent of hydrophobicity. This model was also applied to the toxi- cokinetics of p-aminobenzoate esters and other hydrophobic compounds (Yalkow- sky and Morozowich, 1980).

The relative biodegradation rate constants of alkyl esters of p-aminobenzoic acid, with alkyl groups ranging from methyl to octyl, were determined in pure cultures (Parsons et al., 1987). The relationship between the biodegradation rate constants of the paminobenzoate esters and their hexane-water partition coefficients (Fig. 4) closely resembled that found by Flynn and Yalkowsky between their dithtsion coefficients and their partition coefficients. Both diffusion coefficients and biodegradation rate constants were independent of hexane-water partition coefficients for esters


2 L 6

‘og Kd,oct

FIG. 3. Relationship between log relative second-order biodegradation rate constants (log /Q,~,) of chlorophenols and related compounds and log K+, (Banejee et al., 1984).

with alkyl groups with more than five carbon atoms. This result indicates that for these compounds, which appear to initially undergo rapid hydrolysis of the ester bond, biodegradation rates are determined by the rates at which they are taken up by bacteria.

That biodegradation rates of hydrophobic compounds do not always correlate with octanol-water partition coefficients, can be seen from the data reported by Furukawa et al. for polychlorinated biphenyls (Furukawa et al., 1978). Furukawa et al. measured the rates of degradation of a number of congeners containing two to five chlorine substituents in cell suspensions of two bacterial strains: Alcaligenes sp. Y42 and Acinetobacter sp. P6. The pseudo-first-order rate constants for some of these congeners are plotted against their octanol-water partition coefficients (Shiu and Mackay, 1986) in Fig. 5. It is clear from this figure that for these compounds there is no simple relationship between biodegradation rates and hydrophobicity, in contrast to the compounds mentioned above. Furthermore, it is also clear that for some congeners there are significant differences in their rates of degradation by the two different strains. This would not be expected if uptake rates were rate determining, since large differences in diffusion coefficients for these compounds in membranes of different strains are unlikely.

These results suggest that for polychlorinated biphenyls, and presumably also for other poorly degradable hydrophobic compounds, their rates of degradation are not determined by their diffusion rates through cell membranes, but by the rates at which


log Kd,hex

FIG. 4. Relationship between log kL and log hexane-water partition coefficients (log Kd,hex) for n-alkyl p aminobenzoates (Parsons et al., 1987).

the compounds are transformed once they are in the bacterial cell. One might therefore expect for such compounds correlations between biodegradation rates and molecular descriptors such as steric or electronic parameters, describing transformation rates.

Relationships between Biodegradation Rates and Molecular Electronic Parameters

Pitter measured the degradation rates of substituted phenols and anilines in activated sludge (as the rate of removal of chemical oxygen demand) and related these to the substituents’ Hammett constants (Pitter, 1985). Correlations with negative slopes (indicating rate-limiting electrophilic attack) and r* between 0.88 and 0.98 were obtained for mono- and disubstituted phenols and monosubstituted anilines, but only if the NH2- and S03H-substituted compounds were omitted.

Other examples of correlations between biodegradation rates and electronic parameters have been reported by Dom and Knackmuss for the dioxygenation of substituted catechols (Dom and Knackmuss, 1978) by isolated bacterial enzymes. In the case of pyrocatechase II (catechol- 1,2-dioxygenase) from Pseudomonas sp. B 13, good correlations were obtained between log KM (Michaelis constant) or log Ki (inhibitor constant) and the substituents’ Hammett constants (u) (Hammett, 1940). Such correlations were not found for pyrocatechase I from strain B13 and the pyrocatechase from Alcaligenes eutrophus B9. Similarly, log v,,, (maximum reaction rate) values for pyrocatechase II correlated well with u and c+ (Okamoto and Brown, 1957) values, but log v,,, values for pyrocatechase I correlated very poorly. Since there is no difference in the mechanism of the reactions catalyzed by these enzymes, the different relationships are presumably the result of different substrate specificities of the enzymes. Pseudomonas sp. B 13 can grow on 3-chlorobenzoic acid and has a catechol- 1,2-dioxygenase with a very low specificity (referred to as pyrocatechase II). For other catechol- 1 ,Zdioxygenases, such as pyrocatechase I from this strain and that from the

222 PARSONS AND COVERS

-2 -

. 1 L . 7 0

8 .

L 5 6 7 “‘g Kd,oct

FIG. 5. Relationship between log kb and log K d,Wf for polychlorinated biphenyls. (m) Alcaligenes sp. Y42; (Cl) Acinetobacter sp. P6. (I) 2,2’-, (2) 2,4’-, (3) 4,4’-, (4) 2,4,6-, (5) 2,4’,5-, (6) 2,3,4,5-, (7) 2,2’,5,5’-, (8) 2,2’,4,5,5’-chlorinated biphenyls (Furukawa et al., 1978; Shiu and Mackay, 1986).

Alcaligenes strain, steric effects on substrate binding dominate electronic effects. The negative slope of the relationship for pyrocatechase II indicates that initial attack of the catechol is electrophilic and rate limiting.

The logarithms of the relative rates of oxygenation of substituted benzoic acids by whole cells of Pseudomonas putida mt-2 correlated well with the Hammett substituent constants (Reineke and Knackmuss, 1978), the negative slope again indicating an electrophilic mechanism (Fig. 6). In contrast, no such correlations were found for dioxygenation by Pseudomonas sp. B 13 and A. eutrophus B9, indicating that for these strains steric effects dominate the reaction rate. Such pronounced differences in the results for different strains would not be expected if uptake rates were degradation rate determining.

Dearden and Nicholson used a data set listing 5-day biological oxygen demand of 240 compounds to compare correlations with various structural parameters (Dear- den and Nicholson, 1986). The best results were obtained using the difference in modulus of atomic charge across one specific bond (A I 6 1 x-r) as descriptor. For example, for mixed aromatic and aliphatic amines

BOD = (1.004 X 103)A161c-N -0.106 (n = 15, r2 = 0.998); (8)

for carboxylic acids


a

0’ ’ -0.2 0 0.2 OX 0.6

0

2

5 >' 1

E c

b

0

0

0 0

0 0

0

-0.2 0 0.2 0.L 0.6 0

FIG. 6. Relationship between relative dioxygenation rates (log u,,) of substituted benzoic acids and Ham- mett substituent constants (u) for (a) Pseudomonas putidu mt-2 and (b) Pseudomonas sp. B13 (Reineke and Knackmuss, 1978).

BOD = (1 .OOO X 103)A 16 1 c-o + 2.794

and for halogenated hydrocarbons

(n = 36, r2 = 0.992); (9)

BOD = (1.009 X 103)A I 6 I c-ual + 0.204 (n = 9, r2 = 0.998). (10)

For eight amino acids, a correlation was obtained with the charge differences across the C-O bond (r2 = 0.990), but not with the charge differences across the C-N bond (r2 = 0.024).

It was possible to combine the data for each compound class into a single equation covering 15 amines, five phenols, six aldehydes, 36 carboxylic acids, nine halogenated hydrocarbons, and eight amino acids:

BOD = (1.1015 X 103)A~6~x-Y+ 1.193 (n = 79, r2 = 0.986). (11)

Recently, Dearden and Nicholson have extended this approach to other compounds in the BOD data set (Dearden and Nicholson, 1987a; Dearden and Nichol- son, 1987b) and have derived a correlation involving 197 out of the 240-compound data set:

BOD = (1.015 X 103)A16/x-r+ 1.523 (n = 197, y2 = 0.982). (12)

Interesting as these results are, it is difficult to judge what their significance is. They


appear to indicate that the biodegradation rates of a wide range of compounds are controlled by the electronic properties of a particular reactive center, which is not necessarily the site of attack. The fact that such good correlations were obtained with BOD as the rate parameter (see above) suggests that the initial attack on these compounds is rate determining for their complete degradation.

Relationships between Biodegradation Rates and Molecular Steric Parameters

Correlations of second-order biodegradation rate constants of para-substituted phenols in pure bacterial suspensions with different physicochemical parameters were compared by Paris et al. ( 1982). The physicochemical parameters included the pK,, the Hammett substituent parameter, the Taff s steric parameter, log Kd,oct, and the substituents’ van der Waals radii (yvdW). A very poor correlation was obtained with log Kd,Oct (r2 = 0.097), whereas the best results were obtained with the van der Waal’s radius (r2 = 0.956, Table 1).

Similar results were obtained for the biodegradation rate constants of these compounds by mixed populations in different samples of natural waters (Paris et al., 1983). Second-order biodegradation rate constants of meta-substituted anilines also correlated well with the substituents’ van der Waals radii (Paris and Wolfe, 1987).

The results of the three latter studies suggest that the biodegradation rates of these phenols and anilines are controlled by steric properties of the substituents, which may affect the binding of these compounds to enzymes. This is in apparent contrast to the correlations of biodegradation rate constants of substituted phenols and anilines with Hammett substituent constants reported by Pitter (see above) (Pitter, 1985). How- ever, since Paris et al. do not give correlation coefficients for their correlation with Hammett substituent constants (Paris et al., 1982), it is difficult to compare these studies directly. The difference in the relationships reported by these authors may result from differences in the sets of compounds, or from the different biodegradation rate parameters and microbial populations used.

Biodegradability data for different classes of compounds were correlated with molecular connectivity indices by Boethling (Boethling, 1986). Molecular connectivity indices are topological parameters which quantify molecular branching (Kier and Hall, 1976). Although this approach yielded good correlations for a wide range of compounds, the fact that for different structural classes different rate parameters and different order connectivity indices were used to obtain the best correlations limits their predictive utility and also makes it difficult to draw general conclusions concern- ing the influence of molecular structure on biodegradation rates. Furthermore, molecular connectivity indices themselves often correlate well with parameters express- ing hydrophobicity, such as octanol-water partition coefficients (e.g., Doucette and Andren, 1988) or soil sorption coefficients (e.g., Bahnick and Doucette, 1988). In fact, Boethling obtained good correlations for the pseudo-first-order rate constants for 12 phthalate esters not only with connectivity indices but also with molecular weight and log Kd,OCt.

CONCLUSIONS

Quantitative relationships between biodegradation rates and structural descriptors have been found for several classes of chemicals. The descriptors used in such relationships range from macroscopic physical properties, such as octanol-water parti-


tion coefficients, to molecular structure parameters, such as van der Waals radii of substituents, and parameters describing electron distribution. In general, these relationships are limited to structurally related compounds. There is no general relationship between biodegradability and chemical structure.

Interpretation of such relationships is sometimes made more difficult by the fact that for some classes of compounds biodegradation rates have been correlated successfully with different structural descriptors. For example, for phthalate esters correlations have been reported between biodegradation rate constants and reversed-phase HPLC retention times, molecular connectivities, and hydrolysis rate constants (Table 1). Similarly, for substituted phenols and anilines structural descriptors as diverse as Hammett substituent constants, substituents’ van der Waals radii, octanol-water partition coefficients, and electronic charge differences have been used. However, these structural parameters are themselves often related. A better understanding of the relationships between the different descriptors (Govers and de Voogt, 1988) and careful selection of the sets of compounds used in such studies is required to avoid this problem.

This rather confusing situation, which may be additionally caused by differences in the biodegradation rate parameters used and in the systems in which the data were measured, makes it difficult to identify the rate-determining step in the degradation of such compounds. It is possible to gain such information in those cases where com- parison is possible between correlations with different descriptors, although this is not always the primary objective of such studies.

The fact that quantitative relationships between biodegradation rate and chemical structure are in general specific to limited numbers of structurally related compounds does limit their general predictive utility. In fact, there are no reports of the use of such relationships to successfully predict biodegradation rates of compounds of unknown biodegradability. There is also little information on the use of QSARs based on biodegradability data from one system to predict biodegradation rates in other systems.

Despite their limitations, quantitative structure-biodegradability relationships appear to be a promising approach to understanding and predicting the influence of chemical structure on biodegradation. More reliable data on biodegradation rates and a better understanding of the mechanism and the rate-determining steps of biodegradation are required if QSARs for biodegradation are to be more than a “black box” tool.

ACKNOWLEDGMENT

We thank A. Opperhuizen, D. T. H. M. Sijm, and S. M. Schrap for their comments on this manuscript.

REFERENCES

ALBERTS, B., BRAY, D., LEWIS, J., RATT, M., ROBERTS, K., WATSON, J. D. (1983). Molecular Biology of the Cell, Chap. 3. Garland, New York.

ALEXANDER, M. (198 I). Biodegradation of organic chemicals of environmental concern. Science 211, 132-138.

BAHNICK, D. A., AND DOUCETTE, W. J. (1988). Use of molecular connectivity indices to estimate soil sortion coefficients for organic chemicals. Chemosphere 17, 1703- 17 1.5.

BANERJEE, S., HOWARD, P. H., ROSENBERG, A. M., DOMBROWSKI, A. E., SIKKA, H., AND TULLIS, D. L. (1984). Development of a general kinetic model for biodegradation and its application to chlorophenols and related compounds. Environ. Sci. Technol. 18,4 16-422.


BELTRAME, P., BELTRAME, P. L., AND CARNITI, P. (1985). Comment on “Development of a general kinetic model for biodegradation and its application to chlorophenols and related compounds.” Environ. Sci. Technol. 19,374-375.

BLOK, J., DE MORSIER, A., GERIKE, P., REYNOLDS, L., AND WELLENS, H. (1985). Harmonisation of ready biodegradability tests. Chemosphere 14, 1805- 1820.

BOETHLING, R. S. (1986). Application of molecular topology to quantitative structure-biodegradability relationships. Environ. Toxicol. Chem. 5,797-806.

BRAUMANN, T. (1986). Determination of hydrophobic parameters by reversed-phase liquid chromatography: Theory, experimental techniques, and application in studies on quantitative structure-activity relationships. J. Chromatogr. 373, 19 l-225.

DEARDEN, J. C., AND NICHOLSON, R. M. (1986). The prediction ofbiodegradability by the use ofquantita- tive structure-activity relationships: Correlation of biological oxygen demand with atomic charge difference. Pestic. Sci. 17, 305-3 10.

DEARDEN, J. C., AND NICHOLSON, R. M. (1987a). Correlation of biodegradability with atomic charge difference and superdelocalizability. In QSAR in Environmental Toxicology, Vol. II (K. L. E. Kaiser, Ed.), pp. 83-89. Reidel, Dordrecht.

DEARDEN, J. C., AND NICHOLSON, R. M. (1987b). QSAR study of the biodegradability of environmental pollutants, In QSAR in Drug Design and Toxicology (D. Hadzi and B. Jerman-Blazic, Eds.), pp. 307- 3 12. Elsevier, Amsterdam.

DE VOCK+D, P., WEGENER, J. W. M., KLAMER, J. C., VAN ZIJL, G. A., AND GOVERS, H. (1988). Prediction of environmental fate and effects of heteroatomic polycychc aromatics by QSARs: The position of n- octanol/water partition coefficients. Biomed. Environ. Sci. 1, 194-209.

DORN, E., AND KNACKMUSS, H.-J. (1978). Chemical structure and biodegradability of halogenated aromatic compounds. Substituent effects on 1,2-dioxygenation of catechol. Biochem. J. 174,85-94.

DOUCETTE, W. J., AND ANDREN, A. W. (1987). Correlation of octanol/water partition coefficients and total molecular surface area for highly hydrophobic aromatic compounds. Environ. Sci. Technol. 21, 821-824.

DOUCETTE, W. J., AND ANDREN, A. W. (1988). Estimation of octanol/water partition coefficients: Evalua- tion of six methods for highly hydrophobic aromatic hydrocarbons. Chemosphere 17,345-359.

FLYNN, G. L., AND YALKOWSKY, S. H. (1972). Correlation and prediction of mass transport across membranes. I. Influence of alkyl chain length on flux-determining properties of barrier and diffusant. J. Pharm. Sci. 661,838-852.

FURUKAWA, K., TONOMURA, K., AND KAMIBAYASHI, A. (1978). Effect of chlorine substitution on the biodegradability of polychlorinated biphenyls. AppI. Environ. Microbial. 35,223-227.

GERIKE, P., AND FISCHER, W. K. (1979). A correlation study of biodegradability determinations with various chemicals in various tests. Ecotoxicol. Environ. Saf: 3, 159- 173.

GERIKE, P., AND FISCHER, W. K. (198 1). A correlation study of biodegradability determinations with various chemicals in various tests. II. Additional results and conclusions. Ecotoxicol. Environ. Saf: 5, 45-55.

GOVERS, H., AND DE VOOGD, P. (1988). Classification of molecular descriptors: Calculation of molecular volume and electronegativity from valence electron number. In QSAR 88, Proceedings ofthe 3rd Inter- national Workshop on QuantitativeStructure-Activity Relationships in Environmental Toxicology, May 22-26, Knoxville, USA (J. E. Turner, M. W. England, T. W. Schultz, and N. J. Kwaak, Eds.), pp. 181- 183. National Technical Information Service, US Dept. of Commerce, CONF-88-0520-(DE 88013 180).

HAMMETT, L. P. (1940). Physical Organic Chemistry, pp. 347-390. McGraw-Hill, New York. JONES, S. H., AND ALEXANDER, M. (1986). Kinetics of mineralization of phenols in lake water. Appl.

Environ. Microbial. 51,89 l-897. KANAZAWA, J. (1987). Biodegradability of pesticides in water by microbes in activated sludge, soil and

sediment. Environ. Monit. Assess. 9,57-70. K~ER, L. B., AND HALL, L. H. ( 1976) Molecular Connectivity in Chemistry and Drug Research. Academic

Press, New York. KLECKA, G. M. (1985). Biodegradation. In Environmental Exposure from Chemicals (W. B. Neely and

G. E. Blau, Eds.), pp. 109-155. CRC, Boca Raton, FL. LEHNINGER, A. L. (1970). Biochemistry. Worth Publishers, New York. NIEMI, G. J., VEITH, G. D., REGAL, R. R., AND VAISHNAV, D. D. (1987). Structural features associated

with degradable and persistent chemicals. Environ. Toxicol. Chem. 6, 5 15-527. NIKAIDO, H., AND VAARA, M. (1985). Molecular basis of bacterial outer membrane permeability. Micro-

biol. Rev. 49, I-32.


NIRMALAKHANDAN. N.. AND SPEECE, R. E. (1988). Structure-activity relationships. Environ. Sci. Tech- nol. 22,606-6 15.

OKAMOTO, Y.. AND BROWN, H. C. (1957). A quantitative treatment for electrophilic reactions ofaromatic derivatives. J. Org. Chrm. 22,485-494.

OPPERHUIZEN, A. ( 1987). Relationships between octan- I -al/water partition coefficients, aqueous activity coefficients and reversed phase HPLC capacity factors of alkylbenzenes, chlorobenzenes, chloronaptha- lenes and chlorobiphenyls. Toxicol. Environ. Chem. 15,249-264.

PARIS, D. F., STEEN, W. C., BAUGHMAN, G. L., AND BARNETT, J. T., JR. (1981). Second-order model to predict microbial degradation of organic compounds in natural waters. Appl. Environ. Microhiol. 41, 603-609.

PARIS, D. F., AND WOLFE, N. L. (1987). Relationship between properties of a series of anilines and their transformation by bacteria. Appl. Environ. Microbial. 53,9 1 l-9 16.

PARIS, D. F., WOLFE, N. L.. AND STEEN, W. C. (1982). Structure-activity relationships in microbial transformation of phenols. Appi. Environ. Microhiol. 44, 153-I 58.

PARIS. D. F., WOLFE, N. L.. AND STEEN, W. C. (1984). Microbial transformation of esters of chlorinated carboxylic acids. Appl. Environ. Microbial. 47,7- 1 I.

PARIS, D. F., WOLFE. N. L., STEEN. W. C., AND BAUGHMAN, Cl. L. (1983). Effect of phenol molecular structure on bacterial transformation rate constants in pond and river samples. Appl. Environ. Microbial. 45,1153-1155.

PARSONS, J. R.. OPPERHUIZEN. A., AND HUTZINGER, 0. (1987). Influence of membrane permeation on biodegradation kinetics of hydrophobic compounds. Chemosphere 16, 136 I- 1370.

PFAENDER, F. K., AND BARTHOLOMEW, G. W. (1982). Measurement of aquatic biodegradation rates by determining heterotrophic uptake of radiolabeled pollutants. Appl. Environ. Microhiol. 44, 159- 164.

PITTER, P. ( 1976). Determination of biological degradability of organic substances. Water Res. lo,23 I- 235.

PITTER, P. ( 1985). Correlation of microbial degradation rates with the chemical structure. .4cta Hydrochim. fl.vdrohiol. 13,453-460.

REINEKE. W.. AND KNACKMUSS. H.-J. (1978). Chemical structure and biodegradability of halogenated aromatic compounds. Substituent effects on I ,2-dioxygenation ofbenzoic acid. Biochim. Biophvs. Acta. 542,412-423.

SCHLEGEL, H. G. ( I98 I). .4llgemeine Mikrobiolugie. Thieme, Stuttgart. SHIU. W. Y.. AND MACKAY, D. (1986). A critical review ofaqueous solubilities. vapor pressures, Henry’s

Law constants, and octanol-water partition coefficients ofthe polychlorinated biphenyls. J. Phys. Chem. R@ Dala. 15,9 1 l-929.

SIMKINS, S.. AND ALEXANDER, M. (I 984). Models for mineralization kinetics with the variables of substrate concentration and population density. Appl. Environ. Microbial. 47, I299- 1306.

SIMKINS, S., AND ALEXANDER, M. (I 985). Nonlinear estimation ofthe parameters of Monod kinetics that best describe mineralization of several substrate concentrations by dissimilar bacterial densities. Appl. Environ. Micro/&l. 50, 8 16-824.

STEIN, W. D. ( 1986). Transporf atld D$usion across Cell Membranes. Chap. 2. Academic Press, New York.

URIJSHIGAWA, Y., AND YONEZAWA, Y. (1979). Chemico-biological interactions in biological purification systems. V. Relation between biodegradation rate constants ofdi-n-alkyl phthalate esters and their retention times in reversed phase partition chromatography. Chemosphere& 317-320.

VAISHNAV. D. D.. BOETHLING, R. S., AND BABEU, L. (1987). Quantitative structure-biodegradability relationships for alcohols, ketones and alicyclic compounds. Chemosphere 16,695-703.

WOLFE, N. L.. PARIS, D. F.. STEEN, W. C., AND BAUGHMAN, G. L. (1980). Correlation of microbial degradation rates with chemical structure. Environ. Sci. Technol. 14, 1143-l 144.

YALKOWSKY. S. H.. AND MOROZOWICH. W. (1980). A physical chemical basis for the design of orally active prodrugs. In Drug Design (E. J. Ariens, Ed.). Vol. IX, pp. I2 I-1 85. Academic Press, New York.

YONEZAWA, Y., AND URUSHIGAWA. Y. (1979). Chemico-biological interactions in biological purification systems. V. Relation between biodegradation rate constants of aliphatic alcohols by activated sludge and their partition coefficients in a I-octanol-water system. Chemosphere8. 139-142.

quantitative structure-activity relationships for biodegradation

Documents