StructureA ctivity Relationships

Several computer models have been developed to predict the sensitization potential of chemicals (Table 2). Most models assume that a putative contact allergen reacts with a protein either directly or following biotransformation (Anonymous, 1997).

The models propose structural alerts associated with parental electrophilic fragments or potential electrophiles (proelectrophiles) produced as a result of metabolism. A model such as DEREK (Deductive Estimation of Risk from Existing Knowledge) skin sensitization rule base has been useful in defining contact allergens. The rule base uses 50 structure-activity endpoints that correlate with toxicity endpoints (Barratt etal., 1994). In addition, some physiological characteristics of the chemicals are described (Roberts and Basketter, 1990). Although it is widely accepted that most sensitizers are electrophilic, the ability of a compound to penetrate the stratum corneum and partition into the skin tissue is important.

Skin penetration depends on the log of the octanol/water coefficient (log P) (Flynn, 1990). Compounds with high log P have greater lipophilicity and increased skin penetration. Permeability also decreases with increasing molecular weight or molecular volume. It follows that these endpoints are included in the DEREK decision making process.

DEREK's performance has been tested in two studies. In one study of 37 chemicals proposed by the European Centre for Ecotoxicology and Toxicology of Chemicals, DEREK was able to correctly identify 24 of 25 as sensitizers. Only two compounds, hydroxypropyl methacrylate and p-aminobenzoic acid, yielded false-positive reactions in the model. In another study of 84 contact allergens, the use of structural alerts showed an accuracy of 85% (Kayser and Schlede, 1995). Minor modification of existing rules giving structural alerts for phenols, thiols, and hydroxylamines may increase the accuracy rate to 95% (Barratt and Lan-

Table 2. A Comparison of the QSAR Models for Contact Allergens

Model

Chemicals

Source

Sensitivity

Specificity

DEREK

294

GPMTS

98%

82%

DEREK

93

Animal tests

58%

92%

MultiCASE

1034

GPMT human patch

78%

96%

ACD (Magee et al., 1994)

72

Ziegler data base (1989)

79%

88%

Modified from Quantitative StructureActivity Relationship, Graham et al., 1996, 151 — 7;with permission ofWiley VCH. John Wiley and Sons Ltd. aGuinea pig maximization test

Modified from Quantitative StructureActivity Relationship, Graham et al., 1996, 151 — 7;with permission ofWiley VCH. John Wiley and Sons Ltd. aGuinea pig maximization test gowski, 1997). The DEREK model has been useful in predicting moderate and strong sensitizers. Identification of weak sensitizers is still a problem.

A new model based on the MultiCASE system uses no preconceived mechanisms of sensitization (Klopman et al., 1992). MultiCASE fragments chemicals into subsets containing two or more nonhydrogen atoms. Structural alerts are generated by identification of fragments statistically associated with active sensitizers or biological activity.

Compounds containing the active fragments and other modulating descriptors are determined. These descriptors may be log P, highest occupied molecular orbital (HOMO), lowest occupied molecular orbital (LOMO), molecular weight, or water solubility (Anonymous, 1997). The concordance between model predictions and in vivo evidence of sensitization was 90% (Anonymous, 1997).

Using a large data base of over 1000 animal and human sensitizers, the model could identify four major structural alerts: (1) a nitrogen atom double bonded to a carbon or another nitrogen, (2) substituted aromatic structures, (3) electrophilic moieties, and (4) thiol or disulfide structures.

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