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Discovering the unintended 'off-targets' that predict adverse drug reactions is daunting by empirical methods alone. Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects. Here we use a computational strategy to predict the activity of 656(More)
We introduce SARANEA, an open-source Java application for interactive exploration of structure-activity relationship (SAR) and structure-selectivity relationship (SSR) information in compound sets of any source. SARANEA integrates various SAR and SSR analysis functions and utilizes a network-like similarity graph data structure for visualization. The(More)
Virtual screening using bioactivity profiles has become an integral part of currently applied hit finding methods in pharmaceutical industry. However, a significant drawback of this approach is that it is only applicable to compounds that have been biologically tested in the past and have sufficient activity annotations for meaningful profile comparisons.(More)
For chemical genetics and chemical biology, an important task is the identification of small molecules that are selective against individual targets and can be used as molecular probes for specific biological functions. To aid in the development of computational methods for selectivity analysis, molecular benchmark systems have been developed that capture(More)
Molecular Formal Concept Analysis (MolFCA), an adaptation of formal concept analysis from information theory, is introduced for the systematic comparison of the selectivity of a compound against multiple targets and the extraction of compounds with complex selectivity profiles from biologically annotated databases. In MolFCA, multiple selectivity queries(More)
From a medicinal chemistry point of view, one of the primary goals of high throughput screening (HTS) hit list assessment is the identification of chemotypes with an informative structure-activity relationship (SAR). Such chemotypes may enable optimization of the primary potency, as well as selectivity and phamacokinetic properties. A common way to(More)
We introduce a methodology for the systematic identification of feature combinations derived from fingerprints of bioactive compounds. Structural features were organized in co-occurrence networks from which reference set-based feature cliques were extracted. A similarity search strategy is presented that is based on frequency ranking of cliques. Three types(More)
We report the development and application of the Topological Fragment Index (ToFI), a measure for the complexity of the topological environment of defined molecular fragments in active compounds. On the basis of ToFI calculations, RECAP fragments are organized in dependency hierarchies that capture fragment co-occurrence and facilitate the identification of(More)
A new type of molecular representation is introduced that is based on activity class characteristic substructures extracted from random fragment populations. Mapping of characteristic substructures is used to determine atom match rates in active molecules. Comparison of match rates of bonded atoms defines a hierarchical molecular fragmentation scheme.(More)
To incorporate protein-ligand interaction information into conventional two-dimensional (2D) fingerprint searching, interacting fragments of active compounds were extracted from X-ray structures of protein-ligand complexes and encoded as structural key-type fingerprints. Similarity search calculations with fingerprints derived from interacting fragments(More)