Jeremy L. Jenkins

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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)
Target identification is a critical step following the discovery of small molecules that elicit a biological phenotype. The present work seeks to provide an in silico correlate of experimental target fishing technologies in order to rapidly fish out potential targets for compounds on the basis of chemical structure alone. A multiple-category(More)
Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from(More)
Hedgehog (Hh) signaling determines cell fate during development and can drive tumorigenesis. We performed a screen for new compounds that can impinge on Hh signaling downstream of Smoothened (Smo). A series of cyclohexyl-methyl aminopyrimidine chemotype compounds ('CMAPs') were identified that could block pathway signaling in a Smo-independent manner. In(More)
The results of previous preclinical and clinical studies have identified angiogenin (ANG) as a potentially important target for anticancer therapy. Here we report the design and implementation of a high-throughput screening assay to identify small molecules that bind to the ribonucleolytic active site of ANG, which is critically involved in the induction of(More)
High-content screening is transforming drug discovery by enabling simultaneous measurement of multiple features of cellular phenotype that are relevant to therapeutic and toxic activities of compounds. High-content screening studies typically generate immense datasets of image-based phenotypic information, and how best to mine relevant phenotypic data is an(More)
This study describes a method for mining and modeling binding data obtained from a large panel of targets (in vitro safety pharmacology) to distinguish differences between promiscuous and selective compounds. Two naïve Bayes models for promiscuity and selectivity were generated and validated on a test set as well as publicly available drug databases. The(More)
In the 1950s, the drug thalidomide, administered as a sedative to pregnant women, led to the birth of thousands of children with multiple defects. Despite the teratogenicity of thalidomide and its derivatives lenalidomide and pomalidomide, these immunomodulatory drugs (IMiDs) recently emerged as effective treatments for multiple myeloma and(More)
In silico target fishing is an emerging technology that enables the prediction of biological targets of compounds on the basis of chemical structure by using information from increasingly available biologically annotated chemical databases. We provide a comparative review of recent studies in which data mining, similarity, or docking of chemical structures(More)
Conventional similarity searching of molecules compares single (or multiple) active query structures to each other in a relative framework, by means of a structural descriptor and a similarity measure. While this often works well, depending on the target, we show here that retrieval rates can be improved considerably by incorporating an external framework(More)