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Structural Alerts (structural + alert)

Distribution by Scientific Domains

Life Sciences	37%

Selected Abstracts

Xenoestrogenic gene exression: Structural features of active polycyclic aromatic hydrocarbons

ENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 4 2002
T. Wayne Schultz
Abstract Estrogenicity was assessed using the Saccharomyces cerevisiae -based Lac-Z reporter assay and was reported as the logarithm of the inverse of the 50% molar ,-galactosidase activity (log[EC50,1]). In an effort to quantify the relationship between molecular structure of polycyclic aromatic hydrocarbons (PAHs) and estrogenic gene expression, a series of PAHs were evaluated. With noted exceptions, the results of these studies indicate that the initial two-dimensional structural warning for estrogenicity, the superpositioning of a hydroxylated aromatic system on the phenolic A-ring of 17-,-estradiol, can be extended to the PAHs. This two-dimensional-alignment criterion correctly identified estrogenicity of 22 of the 29 PAHs evaluated. Moreover, the estrogenic potency of these compounds was directly related to the size of the hydrophobic backbone. The seven compounds classified incorrectly by this structural feature were either dihydroxylated naphthalenes or aromatic nitrogen-heterocyclic compounds; all such compounds were false positives. Results with dihydroxylated naphthalenes reveal derivatives that were nonestrogenic when superimposed on the phenolic A-ring of 17-,-estradiol had the second hydroxyl group in the position of the C-ring or were catechol-like in structure. Structural alerts for nitrogen-heterocyclic compounds must take into account the position of the hydroxyl group and the in-ring nitrogen atom; compounds with the hydroxyl group and nitrogen atom involved with the same ring were observed to be nonactive. [source]

Assessment of the sensitivity of the computational programs DEREK, TOPKAT, and MCASE in the prediction of the genotoxicity of pharmaceutical molecules

ENVIRONMENTAL AND MOLECULAR MUTAGENESIS, Issue 3 2004
Ronald D. Snyder
Abstract Computational models are currently being used by regulatory agencies and within the pharmaceutical industry to predict the mutagenic potential of new chemical entities. These models rely heavily, although not exclusively, on bacterial mutagenicity data of nonpharmaceutical-type molecules as the primary knowledge base. To what extent, if any, this has limited the ability of these programs to predict genotoxicity of pharmaceuticals is not clear. In order to address this question, a panel of 394 marketed pharmaceuticals with Ames Salmonella reversion assay and other genetic toxicology findings was extracted from the 2000,2002 Physicians' Desk Reference and evaluated using MCASE, TOPKAT, and DEREK, the three most commonly used computational databases. These evaluations indicate a generally poor sensitivity of all systems for predicting Ames positivity (43.4,51.9% sensitivity) and even poorer sensitivity in prediction of other genotoxicities (e.g., in vitro cytogenetics positive; 21.3,31.9%). As might be expected, all three programs were more highly predictive for molecules containing carcinogenicity structural alerts (i.e., the so-called Ashby alerts; 61% ± 14% sensitivity) than for those without such alerts (12% ± 6% sensitivity). Taking all genotoxicity assay findings into consideration, there were 84 instances in which positive genotoxicity results could not be explained in terms of structural alerts, suggesting the possibility of alternative mechanisms of genotoxicity not relating to covalent drug-DNA interaction. These observations suggest that the current computational systems when applied in a traditional global sense do not provide sufficient predictivity of bacterial mutagenicity (and are even less accurate at predicting genotoxicity in tests other than the Salmonella reversion assay) to be of significant value in routine drug safety applications. This relative inability of all three programs to predict the genotoxicity of drugs not carrying obvious DNA-reactive moieties is discussed with respect to the nature of the drugs whose positive responses were not predicted and to expectations of improving the predictivity of these programs. Limitations are primarily a consequence of incomplete understanding of the fundamental genotoxic mechanisms of nonstructurally alerting drugs rather than inherent deficiencies in the computational programs. Irrespective of their predictive power, however, these programs are valuable repositories of structure-activity relationship mutagenicity data that can be useful in directing chemical synthesis in early drug discovery. Environ. Mol. Mutagen. 43:143,158, 2004. © 2004 Wiley-Liss, Inc. [source]

Use of structural alerts to develop rules for identifying chemical substances with skin irritation or skin corrosion potential

MOLECULAR INFORMATICS, Issue 3 2005
Etje Hulzebos
Abstract In this paper structural alerts for acute skin lesions were categorized as irritation or corrosion or a combination of corrosion/irritation alerts. Categorizing the alerts according to their mechanisms of skin irritation and corrosion and connecting them with physicochemical property limits characterizing their domain of applicability provides strategies to save test animals and costs. These alerts can be used for positive classification of chemicals causing skin irritation or skin corrosion according to EU and OECD guidelines. This paper is the third in the series of four papers describing practical, user-friendly and mechanism-based approaches for predicting when chemicals are likely to irritate or corrode the skin. In the first paper the mechanisms of skin irritation and corrosion were described. In the second paper the physicochemical property limit values for chemicals not causing skin irritation and corrosion were given. In the third paper, described here, structural alerts associated with chemicals causing skin irritation and corrosion were identified and characterized. In the fourth paper, the Skin Irritation Corrosion Rules Estimation Tool (SICRET) was described that allows users to classify chemicals as either not causing skin irritation and corrosion based on physicochemical property limit values or irritating or corrosive to the skin based on structural alerts. [source]

(Q)SARs for Predicting Skin Irritation and Corrosion: Mechanisms, Transparency and Applicability of Predictions

MOLECULAR INFORMATICS, Issue 9 2004

Abstract This paper describes previously-developed (quantitative) structure-activity relationships [(Q)SARs]for predicting skin irritation and corrosion, proposes mechanisms of skin irritation and corrosion, and discusses the transparency and applicability of predictions. This paper was written to set the tone for companion papers that describe three applications of skin irritation and corrosion (Q)SARs. The first companion paper describes physicochemical property limits that can be used to develop rules for identifying chemical substances with no skin irritation or corrosion potential. The second companion paper describes structural alerts that can be used to develop rules for identifying chemical substances with skin irritation or corrosion potential. The third companion paper describes the Skin Irritation Corrosion Rules Estimation Tool (SICRET), a user-friendly tool that allows non-(Q)SAR experts to identify chemical substances with skin irritation or corrosion potential based on physicochemical property limits and structural alerts. [source]

Use of Physicochemical Property Limits to Develop Rules for Identifying Chemical Substances with no Skin Irritation or Corrosion Potential

MOLECULAR INFORMATICS, Issue 9 2004
Ingrid Gerner
Abstract This is believed to be the first paper to promote the use of rules based on (quantitative) structure-activity relationship [(Q)SAR] models for identifying chemicals that are not likely to cause a specific adverse health effect, viz., skin irritation or corrosion. The purpose of this paper is to describe limit values for specific physicochemical properties that are appropriate for identifying chemical substances that have no skin irritation or corrosion potential. These physicochemical properties include melting point, molecular weight, octanol-water partition coefficient, surface tension, vapour pressure, aqueous solubility and lipid solubility. Based on analyses of 1833 chemicals, physicochemical properties for limits were defined to determine that when a chemical's physicochemical properties were either greater or less than these limits that these chemicals would have no skin irritation or corrosion potential. To facilitate classification and labeling, the application domains of these limits were constructed to correspond with the European Union's risk phrases for chemicals classified for skin irritation/corrosion, viz., R 34, R35 or R38. This is the second paper of four companion papers. The first paper discussed mechanisms that can lead to significant skin irritation or corrosion after acute exposures to chemicals. The third paper described the application of structural alerts to identify chemical substances with skin irritation or corrosion potential. The fourth paper described the Skin Irritation Corrosion Rules Estimation Tool (SICRET), a user-friendly tool that allows non-(Q)SAR experts to identify chemical substances with skin irritation or corrosion potential based on physicochemical property limits and structural alerts. [source]