Herbicides, QSAR

Keywords Baseline toxicity Ecotoxicology Environmental transformation products Metabolites Mode of toxic action Pharmaceuticals Pesticides Herbicides QSAR... 

The correlations between chemical descriptors of molecular properties and biological activity, especially the activity of herbicides and/or plant growth regulators has been described (12). Several alternatives or improvements on the Hansch-Fujita QSAR system have been developed (13—15). 

MTD and MTD approaches will be discussed and compared using QSAR of insecticidal benzoylphenyl-ureas, DDT-type analogs and benzylchrysanthemates, herbicidal benzonitriles and nitrophenols, and plant-growth regulating phenoxypropionic acids. 

Soskic, M. and Sabljic, A. (1993). Herbicidal Selectivity of (E)-3-(2,4 Dichlorophenoxy)Acry-lates QSAR Study with Moleciilar Connectivity Indexes. Pestic.Sci.,39, 245-250. 

Finally, X-ray analysis helps to identify tautomers (93RJOC525) and was made the basis of QSAR investigations in the field of herbicides (97MI3, 98MI12). 

Metosulam (198) was C-radiolabeled in the 2-position or in the benzene ring by modified synthetic routes (97MI6). This way data on the pharmacokinetics in mammals could be provided (97MI4). Flumetsulam (197) was toxicologically examined (03MI5) and included in QSAR studies of herbicide toxicity (06BMC2779). 

Perez Gonzalez, M., Gonzalez, H., Molina Ruiz, R., Cabrera, M.A. and Ramos de Armas, R. (2003) TOPS-MODE based QSARs derived from heterogeneous series of compounds. Applications to the design of new herbicides. J. Chem. Inf. Comput. Scl, 43, 1192-1199. 

In the chapter of Pavan et al. the reader may leam more about the theoretical handling of partial order. Especially a useful description of partial order by matrices can be found here. The main topic, however, is devoted to the QSAR problem. The authors suggest and describe how molecular descriptors can be found in order to find useful partial orders. They describe genetic algorithms to find the best model poset and to derive from these unknown properties. "Experimental ranking and Model ranking" are at the heart of this chapter. The interpolation problem, already discussed in the first section by Klein Ivanciuc, and later within this section by Carlsen, plays an important role in the chapter of Pavan et al. A discussion of the prediction uncertainty rounds this chapter. As examples phenyl urea herbicides and their toxicity is chosen. 

Partial order ranking QSAR model for similarly acting phenylurea herbicides... 

Balance. The major use of in vitro systems is clearly to weed out totally inactive compounds. They are not very useful for look-alike chemistry around existing active herbicides except where QSAR data at the cellular level are needed. Then one needs not use an universal pre-screen but a dedicated one for the typical particular chemistry involved. The main use for the universal pre-screen is screening from random" syntheses and from directed syntheses for new chemistry. Dedicated screens should be used for biorational syntheses syntheses designed to inhibit a specific metabolic pathway in the plant. Still, a compound synthesized to inhibit one pathway may instead inhibit another... and thus, should also be tested in a universal pre-screen. 

Much better correlation coefficients are usually obtained with single system dedicated pre-screens. These entail QSAR relationships using related compounds on a single plant in situ vs. in vitro pre-screen (Figure Id), or use crop varieties having differential tolerance to a single herbicide (Figure lb). 

Two families of inhibitors interfere with the plastoquinone or herbicide binding site on the D-1 polypeptide, i.e. on one of the reaction center subunits of PS II. The phenol and urea/triazinone family of PS II inhibitors are different in their functional inhibitory pattern (reviewed in [1]), although they both bind to the D-1 polypeptide and displace each other from the binding site (1). Both QSAR studies (2) and - more refined - quantum mechanical calculations... 

Another class of PS II inhibitors are phenol-derivatives, liXe the herbicides ioxynil and dinoseb where the QSAR is governed by steric parameters (2), as well as hydroxypyridines (7,8) and Xetoni-triles (9). The two inhibitory families may also be designated as a serine and a histidine families, named after the amino acid in the D-1 polypeptide to which the inhibitor is predominantly oriented (though not necessarly bound) (10). 

Many herbicides, lilce ureas and triazines of the serine family share a common substructure a sp carbon attached to a nitrogen with a free electron pair and a positive n-charge (2,18,28). Their QSARs show usually a dependence on electronic and lipophilicity parameters. Individual compounds, chemically different, displace each other from the membrane (14.29). This family looses inhibitory potency in tris-treated cbloroplast membranes (7,18). Cross resistance studies of chloroplasts in triazine/triazinone or DCHU tolerant plants and algae have indicated subfamilies (reviewed in 13,18). None of these mutants are tolerant to phenol-type inhibitors. 

Extensive modeling and quantitative structure-activity relationship (QSAR) studies of Protox herbicides have been reported [12, 74, 75]. Earlier, it was postulated that Protox herbicides act by mimicking the protoporphyrinogen oxidase... 

A class of Protox inhibitors that redefined the accepted SARs and QSARs of the aromatic 4 position was the substituted benzyloxyphenyl heteroaryl area. As discussed earlier, SAR and QSAR studies of the phenyl ring of Protox herbicides demonstrated the need for halogens in the 2- and 4 positions of the phenyl ring, with the exception of the 4-chlorobenzyloxy group such as that of 4-chlorobenzyloxyphenyl tetrahydrophthalimide outlier 55 (Fig. 3.15) and reported by Ohta and coworkers in 1980 [79]. Chlorine at the para position of the benzy-loxy was reported to provide optimum biological activity. 

QSAR models describing phytotoxicity (Table 5.12) are limited to a few chemical classes, mostly those with relatively well-understood modes of action such as herbicidal compounds. 

The differences in sensitivity of organisms and test systems, although a possible complication for interspecies extrapolations, do not affect the reliability of these correlations. Much more critical are the actual limitations of their validity stemming from the different modes of toxic action of environmental contaminants in various species. Chemicals (e.g. herbicides and AChE inhibitors) that have different toxicity mechanisms in fish and algae, respectively (Figure 8.4), reveal distinct QSARs the interspecies correlations thus break down (e.g. Gehring and Rao, 1977 Smissaert and Jansen, 1984 Wallace and Niemi, 1988 Nendza and Wenzel, 1993). 

When the herbicidal activity of the four parent pyranopyridylimidazolinones are compared, all four compounds show excellent control of weeds with different degrees of safety on soybeans in preemergence tests. The two most active and most selective soybean compounds appear to be the ones with the oxygen atom bound to the pyridine ring (i.e. 5 and 6). The results of the herbicidal activity for these pyranopyridylimidazolinones are in agreement with a QSAR analysis (15). 

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