Understanding False Positives in Reporter Gene Assays:  in Silico Chemogenomics Approaches To Prioritize Cell-Based HTS Data

Abstract

High throughput screening (HTS) data is often noisy, containing both false positives and negatives. Thus, careful triaging and prioritization of the primary hit list can save time and money by identifying potential false positives before incurring the expense of followup. Of particular concern are cell-based reporter gene assays (RGAs) where the number of hits may be prohibitively high to be scrutinized manually for weeding out erroneous data. Based on statistical models built from chemical structures of 650 000 compounds tested in RGAs, we created "frequent hitter" models that make it possible to prioritize potential false positives. Furthermore, we followed up the frequent hitter evaluation with chemical structure based in silico target predictions to hypothesize a mechanism for the observed "off target" response. It was observed that the predicted cellular targets for the frequent hitters were known to be associated with undesirable effects such as cytotoxicity. More specifically, the most frequently predicted targets relate to apoptosis and cell differentiation, including kinases, topoisomerases, and protein phosphatases. The mechanism-based frequent hitter hypothesis was tested using 160 additional druglike compounds predicted by the model to be nonspecific actives in RGAs. This validation was successful (showing a 50% hit rate compared to a normal hit rate as low as 2%), and it demonstrates the power of computational models toward understanding complex relations between chemical structure and biological function.

From in silico target prediction to multi-target drug design: Current databases, methods and applications

“…Also fingerprint-based target prediction models, based on the WOMBAT database and Naïve Bayes models, have been applied in practice, such as to the rationalization of false positives in reporter gene assays [93]. Here it was found that false positives in reporter gene assays very often are predicted to interact with kinases involved in cell cycle progressionhence, a mechanistic hypothesis for false positives could be generated.…”

“…cytotoxicity assays, where it was indeed shown that > 50% of false positives in reporter gene assays possess cytotoxic properties [93].…”

Knowledge‐Based and Computational Approaches to In Vitro Safety Pharmacology

“…For target prediction protocols, well annotated data of compound-target pairings derived from secondary assays with activity values (e.g., IC 50 , EC 50 , K d ) calculated from multiple concentration points are most useful. Single data points from highthroughput screening are less desirable, although such data has been successfully used [58,59]. Ideally, the database would have additional layers of annotation describing target family ontology (to truly be a chemogenomics database), normalized activity values, inactive as well as active compounds and data source (journal or patent citation).…”

Non-stoichiometric inhibition in integrated lead finding – a literature review

“…Although this concept has some similarity with socalled PAINS (pan-assay interfering compounds) [10] or the older term 'frequent hitter', [11,12] non-stoichiometric inhibition does not distinguish in any way between activity in one or several assays. One of the reasons is that polypharmacology nowadays is seriously pursued as a lead finding strategy.…”

“…The latter originally referred to compounds exceeding the hit threshold due to statistical variation in the assay signal [16,17] but now is also applied to reproducible hits with undesirable mode of action. [11,[18][19][20][21][22] Non-stoichiometric inhibition in this sense should not be confused with sub-stoichiometric inhibition, a term that has also been applied to chaperone proteins [23] or antibodies, [24] which are clearly out of scope for this review.…”