Toward the design of chemical libraries for mass screening biased against mutagenic compounds

Citation
O. Llorens et al., Toward the design of chemical libraries for mass screening biased against mutagenic compounds, J MED CHEM, 44(17), 2001, pp. 2793-2804
Citations number
34
Categorie Soggetti
Chemistry & Analysis
Journal title
JOURNAL OF MEDICINAL CHEMISTRY
ISSN journal
00222623 → ACNP
Volume
44
Issue
17
Year of publication
2001
Pages
2793 - 2804
Database
ISI
SICI code
0022-2623(20010816)44:17<2793:TTDOCL>2.0.ZU;2-#
Abstract
The ability to develop a chemical into a drug depends on multiple factors. Beyond potency and selectivity, ADME/PK and the toxicological profile of th e compound play a significant role in its evaluation as a candidate for dev elopment. Those factors are being brought into bear earlier in the discover y process and even into the design of libraries for screening. The purpose of our study is the comparative analysis of simple physical characteristics of compounds that have been reported to be mutagens and nonmutagenic ones. The analysis of differences can lead to the development of knowledge-based biases in the libraries designed for massive screening. For each of four S almonella strains, TA-98, TA-100, TA-1535, and TA-1537, an analysis of the statistical significance of the deviance of the averages for a number of gl obal properties was carried out. The properties studied included parameters , such as topological indices, and bit strings representing the presence or absence of certain chemical moieties. The results suggest that mutagens di splay a larger number of hydrogen bond acceptor centers for most strains. M oreover, the use of bit strings points to the importance of certain molecul ar fragments, such a nitro groups, for the outcome of a mutagenicity study. Development of multivariate models based on global molecular properties or bit strings point to a small advantage of the latter for the prediction of mutagenicity. The benefits of the bit strings are in accord with the use o f fragment-based approaches for the prediction of carcinogenicity and mutag enicity in methods described in the literature.