A Novel SAR-Driven Approach for Identifying True High-Throughput Screening Hits
Modern drug discovery relies heavily on large-scale high-throughput screening (HTS) to identify potential starting points for medicinal chemistry optimization. The typical “top X” activity cutoff method used to generate hits from large amount of raw HTS data is intrinsically error-prone due to the noisy nature of single-dose HTS, which oftentimes leads to a large number of false positives. Here we propose a novel knowledge-based, SAR-driven statistical approach for primary HTS hit generation using ChemAxon technology for clustering and chemical fingerprints. The method is also implemented with SciTegic Pipeline Pilot. In a proof-of-concept study for an in-house HTS campaign, the new approach proved to be more effective in identifying confirmed active compounds in diverse chemical scaffolds containing valuable SAR information, as demonstrated by a significantly improved confirmation rate compared to the traditional “top X” cutoff method.