title: Toward the design of chemical libraries for mass screening biased against mutagenic compounds.
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 the compound play a significant role in its evaluation as a candidate for development. Those factors are being brought into bear earlier in the discovery 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 Salmonella 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 global 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 display a larger number of hydrogen bond acceptor centers for most strains. Moreover, the use of bit strings points to the importance of certain molecular 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 of fragment-based approaches for the prediction of carcinogenicity and mutagenicity in methods described in the literature.
authors.affiliation: Telik, Inc., Chemoinformatics Group, 750 Gateway Boulevard, South San Francisco, California 94080, USA.
authors.forename: O
authors.initials: O
authors.lastname: Llorens
authors.forename: J J
authors.initials: JJ
authors.lastname: Perez
authors.forename: H O
authors.initials: HO
authors.lastname: Villar
mesh_terms: D020650:Combinatorial Chemistry Techniques; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D015195:Drug Design; D009152:Mutagenicity Tests; D009153:Mutagens / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D012475:Salmonella
chemical_list: D009153:Mutagens