Quantifying the fingerprint descriptor dependence of structure-activity relationship information on a large scale
- PMID: 23968259
- DOI: 10.1021/ci4004078
Quantifying the fingerprint descriptor dependence of structure-activity relationship information on a large scale
Abstract
It is well-known that different molecular representations, e.g., graphs, numerical descriptors, fingerprints, or 3D models, change the numerical results of molecular similarity calculations. Because the assessment of structure-activity relationships (SARs) requires similarity and potency comparisons of active compounds, this representation dependence inevitably also affects SAR analysis. But to what extent? How exactly does SAR information change when alternative fingerprints are used as descriptors? What is the proportion of active compounds with substantial changes in SAR information induced by different fingerprints? To provide answers to these questions, we have quantified changes in SAR information across many different compound classes using six different fingerprints. SAR profiling was carried out on 128 target-based data sets comprising more than 60,000 compounds with high-confidence activity annotations. A numerical measure of SAR discontinuity was applied to assess SAR information on a per compound basis. For ~70% of all test compounds, changes in SAR characteristics were detected when different fingerprints were used as molecular representations. Moreover, the SAR phenotype of ~30% of the compounds changed, and distinct fingerprint-dependent local SAR environments were detected. The fingerprints we compared were found to generate SAR models that were essentially not comparable. Atom environment and pharmacophore fingerprints produced the largest differences in compound-associated SAR information. Taken together, the results of our systematic analysis reveal larger fingerprint-dependent changes in compound-associated SAR information than would have been anticipated.
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